Techniques for mixed reality theater

Abstract

Techniques are provided for mixed reality theater systems. A device may obtain first sensor measurements from biometric sensors during a first time period; generate a first set of features from the first sensor measurements; derive a baseline biometric profile representative of an initial physiological state of a participant from the first set of features; and provide a content sequence including content segments to the participant. The device may obtain, for a time period corresponding to presentation of at least one of the content segments, additional measurements from the biometric sensors; generate, from the additional sensor measurements, a second set of features corresponding to a physiological response to the presented content segment; provide the baseline biometric profile and the second set of features to a machine-learning model configured to output a physiological response score; and calculate an effectiveness score based on the physiological response score.

Description

PATENTAttorney Docket No. 130586-866348TECHNIQUES FOR MIXED REAEITY THEATERCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present patent application claims the benefit of U.S. Provisional Application No. 63 / 730,716, filed December 11. 2024, and of U.S. Provisional Application No. 63 / 800,973, filed May 6, 2025, the contents of which is incorporated herein for all purposes.FIELD

[0002] The present disclosure relates to techniques for mixed reality systems, and more specifically, but without limitation to techniques for mixed reality theater systems.BACKGROUND

[0003] As computing and display technologies have advanced, mixed reality systems have been developed to combine real-world environments with computer-generated imagery in real time. Such systems have found application in gaming, education, industrial training, and live entertainment, among other domains. Within performance venues. MR systems may provide digital overlays, environmental projections, or holographic augmentations that interact dynamically with live performers and stage elements, creating a hybrid experience that merges physical and virtual narratives.

[0004] In various entertainment settings, immersive technologies have been explored to enhance audience engagement and expand storytelling techniques. Different approaches exist along a spectrum of immersion. For instance, certain approaches may augment live performances by presenting additional digital information or effects within a viewer’s perception of the physical stage. Other approaches may provide audiences with entirely synthetic environments in which narratives unfold independently of the physical surroundings. Between these extremes, hybrid approaches have been contemplated that blend aspects of both augmentation and full immersion, allowing physical and digital elements to coexist and influence one another within the same performance environment.

[0005] Despite these advances, existing systems for mixed reality theater and performance integration face several challenges. Maintaining real-time synchronization between physical- 1 -107298845 1PATENTAttorney Docket No. 130586-866348 and virtual elements can be difficult due to rendering latency, tracking inaccuracies, and heterogeneous device capabilities. Current frameworks also provide limited personalization and contextual adaptation for individual audience members. Additionally, privacy, security, and regulatory compliance concerns arise when personal data or location-based content is incorporated into MR experiences. Accordingly, there is a need for improved systems and methods that provide adaptive, secure, and personalized mixed reality experiences for theatrical and performance environments.SUMMARY

[0006] The following presents a simplified summary relating to one or more aspects disclosed herein. Thus, the following summary should not be considered an extensive overview relating to all contemplated aspects, nor should the following summary’ be considered to identify key or critical elements relating to all contemplated aspects or to delineate the scope associated with any particular aspect. Accordingly, the following summary presents certain concepts relating to one or more aspects relating to the mechanisms disclosed herein in a simplified form to precede the detailed description presented below.

[0007] In some aspects, the techniques described herein relate to a computer implemented method for calculating an effectiveness score based on biometric sensor data, the method including: obtaining first sensor measurements from one or more biometric sensors during a first time period; generating a first set of features from the first sensor measurements; deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant; providing, to the participant, a content sequence including a plurality of content segments, each content segment associated with a label identifying a level of emotional intensify represented in the content segment; obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors; generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments; providing the baseline biometric profile and the second set of features to a machine-learning model configured to output a physiological response score; and calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence.- 2 -107298845 1PATENTAttorney Docket No. 130586-866348

[0008] In some aspects, the techniques described herein relate to a computer implemented method, wherein the one or more biometric sensors include at least one of a heart-rate monitor, galvanic skin response sensor, eye tracking camera, or facial expression recognition system.

[0009] In some aspects, the techniques described herein relate to a computer implemented method, wherein each content segment corresponds to a scene of a mixed reality, augmented reality, or virtual reality presentation.

[0010] In some aspects, the techniques described herein relate to a computer implemented method, wherein the labels are generated from prior testing sessions or annotated training data defining target engagement levels.

[0011] In some aspects, the techniques described herein relate to a computer implemented method, wherein the machine-learning model includes a neural network model trained to predict the physiological response score from the baseline biometric profile and the second set of features.

[0012] In some aspects, the techniques described herein relate to a computer implemented method, further including adjusting at least one presentation parameter of a subsequent content segment based on the calculated effectiveness score.

[0013] In some aspects, the techniques described herein relate to a computer implemented method, wherein the effectiveness score is transmitted to an analytics server for aggregation across multiple participants or sessions.

[0014] In some aspects, the techniques described herein relate to a computer implemented method, wherein the effectiveness score is displayed on a control interface to provide real-time feedback to an operator or automated orchestration system.

[0015] In some aspects, the techniques described herein relate to a virtual reality system including one or more memories and one or more processors coupled to the one or more memories and configured to perform operations including: obtaining first sensor measurements from one or more biometric sensors during a first time period; generating a first set of features from the first sensor measurements; deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant; providing, to the participant, a content sequence including a plurality of content segments, each content segment associated with a label identifying a level of emotional intensity represented in the content segment; obtaining, for a time penod corresponding to presentation of at least one of the content- 3 -107298845 1PATENTAttorney Docket No. 130586-866348 segments, second sensor measurements from the one or more biometric sensors; generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments; providing the baseline biometric profile and the second set of features to a machine-learning model configured to output a physiological response score; and calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence.

[0016] In some aspects, the techniques described herein relate to a virtual reality system, wherein the one or more biometric sensors include at least one of a heart-rate monitor, galvanic skin response sensor, eye tracking camera, or facial expression recognition system.

[0017] In some aspects, the techniques described herein relate to a virtual reality system, wherein each content segment corresponds to a scene of a mixed real ity. augmented real ity. or virtual reality presentation.

[0018] In some aspects, the techniques described herein relate to a virtual reality system, wherein the labels are generated from prior testing sessions or annotated training data defining target engagement levels.

[0019] In some aspects, the techniques described herein relate to a virtual reality system, wherein the machine-learning model includes a neural network model trained to predict the physiological response score from the baseline biometric profile and the second set of features.

[0020] In some aspects, the techniques described herein relate to a virtual reality system, further including adjusting at least one presentation parameter of a subsequent content segment based on the calculated effectiveness score.

[0021] In some aspects, the techniques described herein relate to a virtual reality system, wherein the effectiveness score is transmitted to an analytics server for aggregation across multiple participants or sessions.

[0022] In some aspects, the techniques described herein relate to a non-transitory computer- readable medium storing instructions that, when executed by one or more processors, cause a system to perform a method for generating an experience-effectiveness score, the method including: obtaining first sensor measurements from one or more biometric sensors during a first time period; generating a first set of features from the first sensor measurements; deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant; providing, to the participant, a content sequence including- 4 -107298845 1PATENTAttorney Docket No. 130586-866348 a plurality of content segments, each content segment associated with a label identifying a level of emotional intensity represented in the content segment; obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors; generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments; providing the baseline biometric profile and the second set of features to a machine-learning model configured to output a physiological response score; and calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence.

[0023] In some aspects, the techniques described herein relate to a non-transitory computer- readable medium, wherein the one or more biometric sensors include at least one of a heartrate monitor, galvanic skin response sensor, eye tracking camera, or facial expression recognition system.

[0024] In some aspects, the techniques described herein relate to a non-transitory computer- readable medium, wherein each content segment corresponds to a scene of a mixed reality, augmented reality, or virtual reality presentation.

[0025] In some aspects, the techniques described herein relate to a non-transitory computer- readable medium, wherein the labels are generated from prior testing sessions or annotated training data defining target engagement levels.

[0026] In some aspects, the techniques described herein relate to a non-transitory computer- readable medium, wherein the machine-learning model includes a neural network model trained to predict the physiological response score from the baseline biometric profile and the second set of features.

[0027] This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used in isolation to determine the scope of the claimed subject matter. The subject matter should be understood by reference to appropriate portions of the entire specification of this patent, any or all drawings, and each claim.

[0028] The foregoing, together with other features and aspects, wi 11 become more apparent upon referring to the following specification, claims, and accompanying drawings.- 5 -107298845 1PATENTAttorney Docket No. 130586-866348BRIEF DESCRIPTION OF THE DRAWINGS

[0029] FIG. 1 is a block diagram of an example device for mixed reality, in accordance with aspects of the present disclosure.

[0030] FIG. 2 is a diagram illustrating an example mixed reality environment, in accordance with aspects of the present disclosure.

[0031] FIG. 3 is a block diagram of an example topology’ for a mixed reality system, in accordance with aspects of the present disclosure.

[0032] FIG. 4A is a block diagram of an example interface and protocol layer of a core mixed reality engine, in accordance with aspects of the present disclosure.

[0033] FIG. 4B is a block diagram of an example control and orchestration layer of a core mixed reality engine, in accordance with aspects of the present disclosure

[0034] FIG. 5 depicts an example flow of a processing pipeline for a mixed reality system, in accordance with aspects of the present disclosure.

[0035] FIG. 6 depicts a flowchart of an example simultaneous location and mapping (SLAM) process for mixed reality7, in accordance with aspects of the present disclosure.

[0036] FIG. 7 depicts a flowchart of an example object occlusion and removal process for mixed reality7, in accordance with aspects of the present disclosure.

[0037] FIG. 8 depicts a flowchart of an example viewpoint manipulation process for mixed reality7, in accordance with aspects of the present disclosure.

[0038] FIG. 9 depicts a flowchart of an example virtual position movement process for mixed reality, in accordance with aspects of the present disclosure.

[0039] FIG. 10 depicts a flowchart of an example live camera feed integration process for mixed reality, in accordance with aspects of the present disclosure.

[0040] FIG. 11 depicts an example flow of a processing pipeline for a biometric- adaptive content system in mixed reality, in accordance with aspects of the present disclosure.

[0041] FIG. 12 depicts a flowchart of an example biometric data collection process for biometric-adaptive content in mixed reality, in accordance with aspects of the present disclosure.- 6 -107298845 1PATENTAttorney Docket No. 130586-866348

[0042] FIG. 13 depicts a flowchart of an example content mapping and anchor tracking process for biometric-adaptive content in mixed reality, in accordance with aspects of the present disclosure.

[0043] FIG. 14 depicts a flowchart of an example biometnc data processing and interpretation process for biometric-adaptive content in mixed reality, in accordance with aspects of the present disclosure.

[0044] FIG. 15 depicts a flowchart of an example scene effectiveness scoring process for biometric-adaptive content in mixed reality, in accordance with aspects of the present disclosure.

[0045] FIG. 16 depicts a flowchart of an example real-time adaptive feedback process for biometric-adaptive content in mixed reality, in accordance with aspects of the present disclosure.

[0046] FIG. 17 depicts a flowchart of an example privacy, consent, and data security process for biometric-adaptive content in mixed reality, in accordance with aspects of the present disclosure.

[0047] FIG. 18 depicts an example of a system architecture flow for a biometric-adaptive content system in mixed reality', in accordance with aspects of the present disclosure.

[0048] FIG. 19 depicts an example flow of a processing pipeline for personalized content in mixed reality, in accordance with aspects of the present disclosure.

[0049] FIG. 20 depicts a flowchart of an example secure device integration and consent process for personalized content in mixed reality, in accordance with aspects of the present disclosure.

[0050] FIG. 21 depicts a flowchart of an example data harvesting and metadata capturing process for personalized content in mixed reality7, in accordance with aspects of the present disclosure.

[0051] FIG. 22 depicts a flowchart of an example preprocessing and intelligent filtering process for personalized content in mixed reality7, in accordance with aspects of the present disclosure.- 7 -107298845 1PATENTAttorney Docket No. 130586-866348

[0052] FIG. 23 depicts a flowchart of an example data transmission and system integration process for personalized content in mixed reality, in accordance with aspects of the present disclosure.

[0053] FIG. 24 depicts a flowchart of an example rendering process for personalized content in mixed reality, in accordance with aspects of the present disclosure.

[0054] FIG. 25 depicts a flowchart of an example dynamic narrative adaptation loop for personalized content in mixed reality, in accordance with aspects of the present disclosure.

[0055] FIG. 26 depicts a flowchart of an example privacy, security, and opt-in control process for personalized content in mixed reality, in accordance with aspects of the present disclosure.

[0056] FIG. 27 depicts an example flow of a processing pipeline for personalized characters in mixed reality', in accordance with aspects of the present disclosure.

[0057] FIG. 28 depicts a flowchart of an example placeholder character designation and tracking process for personalized characters in mixed reality, in accordance with aspects of the present disclosure.

[0058] FIG. 29 depicts a flowchart of an example data harvesting for avatar generation process for personalized characters in mixed reality, in accordance with aspects of the present disclosure.

[0059] FIG. 30 depicts a flowchart of an example avatar and texture generation process for personalized characters in mixed reality, in accordance with aspects of the present disclosure.

[0060] FIG. 31 depicts a flowchart of an example character substitution process for personalized characters in mixed reality, in accordance with aspects of the present disclosure.

[0061] FIG. 32 depicts a flowchart of an example sty 1 i sti c filters and aesthetic harmonization process for personalized characters in mixed reality, in accordance with aspects of the present disclosure.

[0062] FIG. 33 depicts a flowchart of an example privacy and security process for personalized characters in mixed reality, in accordance with aspects of the present disclosure.

[0063] FIG. 34 depicts an example flow of a processing pipeline for location-based content in mixed reality, in accordance with aspects of the present disclosure.- 8 -107298845 1PATENTAttorney Docket No. 130586-866348

[0064] FIG. 35 depicts a flowchart of an example geolocation detection and context generation process for location-based content in mixed reality, in accordance with aspects of the present disclosure.

[0065] FIG. 36 depicts a flowchart of an example asset management system querying and metadata filtering process for location-based content in mixed reality, in accordance with aspects of the present disclosure.

[0066] FIG. 37 depicts a flowchart of an example secure asset retrieval and caching process for location-based content in mixed reality, in accordance with aspects of the present disclosure.

[0067] FIG. 38 depicts a flowchart of an example rendering process for location-based content in mixed reality, in accordance with aspects of the present disclosure.

[0068] FIG. 39 depicts a flowchart of an example content activation and campaign management process for location-based content in mixed reality, in accordance with aspects of the present disclosure.

[0069] FIG. 40 depicts a flowchart of an example compliance and governance process for location-based content in mixed reality, in accordance with aspects of the present disclosure.

[0070] FIG. 41 depicts an example of a process for training a machine learning model, in accordance with an aspect of the present disclosure.

[0071] FIG. 42 is a diagram illustrating an example of a computer system, in accordance with an aspect of the present disclosure.

[0072] In the appended figures, similar components and / or features can have the same reference label. Further, various components of the same type can be distinguished by following the reference label by a dash and a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.DETAILED DESCRIPTION

[0073] In the following description, for the purposes of explanation, specific details are set forth to provide a thorough understanding of certain inventive aspects. However, it will be- 9 -107298845 1PATENTAttorney Docket No. 130586-866348 apparent that various aspects may be practiced without these specific details. The figures and description are not intended to be restrictive. The word "exemplary” is used herein to mean “serving as an example, instance, or illustration.’’ Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs.

[0074] Reference to “one aspect” or “an aspect” means that a particular feature, structure, or characteristic described in connection with the aspect is included in at least one aspect of the disclosure. The appearances of the phrase “in one aspect” in various places in the specification are not necessarily all referring to the same aspect, nor are separate or alternative aspects mutually exclusive of other aspects. Moreover, various features are described which can be exhibited by some aspects and not by others.

[0075] The terms used in this specification generally have their ordinary7meanings in the art, within the context of the disclosure, and in the specific context where each term is used. Alternative language and synonyms can be used for any one or more of the terms discussed herein, and no special significance should be placed upon whether or not a term is elaborated or discussed herein. In some cases, synonyms for certain terms are provided. A recital of one or more synonyms does not exclude the use of other synonyms. The use of examples anywhere in this specification including examples of any terms discussed herein is illustrative only, and is not intended to further limit the scope and meaning of the disclosure or of any example term. Likewise, the disclosure is not limited to various aspects given in this specification.

[0076] Without intent to limit the scope of the disclosure, examples of instruments, apparatus, methods and their related results according to the aspects of the present disclosure are given below. Note that titles or subtitles can be used in the examples for convenience of a reader, which in no way should limit the scope of the disclosure. Unless otherwise defined, technical and scientific terms used herein have the meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. In the case of conflict, the present document, including definitions will control.

[0077] Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or can be learned by practice of the herein disclosed principles. The features and advantages of the disclosure can be realized and obtained by means of the instruments and combinations particularly pointed- 10 -107298845 1PATENTAttorney Docket No. 130586-866348 out in the appended claims. These and other features of the disclosure will become more fully apparent from the following description and appended claims, or can be learned by the practice of the principles set forth herein.

[0078] Mixed reality (MR) is an immersive computing paradigm spanning a continuum between augmented reality (AR) and virtual reality (VR). AR overlays digital content onto the user’s real-world view, enriching perception and interaction with physical surroundings. VR replaces that view7with a fully simulated environment, immersing the user and shifting perception and interaction entirely into the virtual world. MR situates the user in a unified experience where world-anchored digital content coexists and interacts with purely virtual elements; it maintains spatial awareness of the user and environment, renders content that respects real-world context and geometry7, and can incorporate fully virtual scenes that operate within a shared tracked coordinate frame and interaction model (including physics) — enabling user perception and interaction across both physical and virtual domains. This hybrid mode supports non-limiting applications in entertainment, education, training, design review-, and collaboration across diverse implementations — including head-mounted and handheld devices, projection or room-scale systems, and on-device, edge, or cloud processing — and is not limited to any particular hardware, software, or architectural pattern.

[0079] Augmented reality places digital information into the world the user already inhabits. Experiences unfold in homes, workplaces, classrooms, and outdoor spaces with continuous awareness of physical surroundings. Device-resident cameras and depth or other sensors, paired with detection, tracking, and localization algorithms, register content to the scene so perspective and occlusion read naturally. The content itself may span text annotations, 2D and 3D imagery, video, audio, and data visualizations anchored to objects, surfaces, or locations. Users interact by touch, gesture, gaze, controller, or voice to select, reposition, rotate, resize, and query virtual elements while remaining context-aware. Representative uses can include, without limitation, instructional overlays and guided procedures, in situ previews for planning or retail, inspection and measurement, and context-responsive information access. Shared sessions can synchronize anchors, state, and annotations for co-located or remote participants.

[0080] Virtual reality, by contrast, transports the user into a purpose-built, synthetic space. The physical environment is replaced by a rendered world, typically explored within a safe play area. Head-mounted displays (HMDs) provide stereoscopic imagery while tracked head and hands — optionally eyes or full body — yield low-latency presence and accurate parallax.- 11 -107298845 1PATENTAttorney Docket No. 130586-866348Digital content includes interactive environments, avatars, simulated tools and objects, spatial audio, and narrative or data-driven scenes. Interaction can rely on controllers, gesture, gaze, or voice for locomotion, selection, manipulation, inspection, and system commands, with haptics when available. Applications span skills training and simulation, architectural walkthroughs, therapy and rehabilitation, narrative exploration, visualization, and play. Social features enable multi-user presence through avatars, shared workrooms, and synchronized tasks and assets.

[0081] Complementary' in their immersive capabilities, AR and VR outline the bounds of a continuum that mixed reality can adaptively unite in real time. In MR, the surrounding environment remains part of the experience while virtual elements gain depth, persistence, and agency. Core technologies — spatial mapping, depth sensing, and scene understanding — establish a shared tracked coordinate frame and interaction model (including physics) so digital objects respect real -world geometry, lighting, and occlusion. The digital content can include volumetric models, interactive panels, simulated tools, and data visualizations that anchor to rooms, surfaces, or moving objects. Interaction spans touch-like hand gestures, tracked controllers, gaze and voice, and can incorporate haptics or spatial audio for feedback. Typical applications pair physical context with simulation: step-by-step guidance on real equipment, hybrid design reviews that juxtapose a physical prototype with virtual variants, or in-place analytics layered over live operations. Socially, MR supports co-located or remote participants who see shared anchors and synchronized state, enabling collaborative creation, instruction, and decision-making.

[0082] By weaving physical context and synthetic presence, MR enables fluid transitions along the continuum — emphasizing real-world alignment when context matters, or increasing immersion when focus is needed — without leaving the shared space. Digital objects can persist across sessions through world-locked anchors (fixed in an environment / global frame), follow users as task-locked tools (attached to a user, actor, or device), or remain view-locked as headsup elements (stabilized in display space). Depth-aware rendering enforces scale and occlusion; hand, object, and body tracking allow direct manipulation; and spatial audio situates cues where they are most informative or safe. Multi-user modes support shared workrooms and over-the- shoulder mentoring, while permissions and safety boundaries help manage sensitive data and physical hazards. Together, these capabilities let teams prototy pe, train, visualize, and operate with a common, reality-aligned frame of reference that complements both AR's contextual overlays and VR’s immersive simulations.- 12 -107298845 1PATENTAttorney Docket No. 130586-866348

[0083] The systems and methods (e.g., processes) described herein may employ any combination of computational, sensing, display, audio, input, networking, storage, and software technologies to capture environmental information, manage digital content, and render MR experiences. Additional modalities may also be supported, including, without limitation, brain-computer interfaces (BCIs), olfactory' displays, quantum-dot panels, or future sensory technologies. Connectivity, power delivery, compute locality (on-device, edge, or cloud), and physical form may vary by deployment. The inventive subject matter is not limited to any particular device class, component set, or architectural pattern. Further structural detail is provided below with reference to FIG. 1.

[0084] Turning now to the Figures, FIG. 1 illustrates an example of a device architecture suitable for implementing mixed reality functionality' in accordance with aspects of the present disclosure. As shown, the device is presented in a generalized form so as to encompass a range of use cases beyond any particular application environment. The depicted components may cooperate to capture information from the physical surroundings, process and render digital content, and facilitate interaction between real and virtual elements. While the aspect of FIG. 1 is described in the context of a representative mixed reality system, it will be understood that the arrangement is not limited to the illustrated form and may be adapted, rearranged, or supplemented with additional components without departing from the scope of the disclosure.

[0085] As shown in FIG. 1, a mixed reality (MR) device 100 may include a plurality' of coordinated components that together support immersive interaction with both real and virtual content. These components may include, without limitation, a display component 101, an imaging component 102, a sensor component 103, a tracking system component 104, an environment interaction component 105, a processor component 106, a software component 107, an input system component 108, an audio system component 109, a connectivity component 110, and a power supply (not show n). In some implementations, the mixed reality device 100 may further include additional components not specifically depicted or enumerated in FIG. 1 (e.g., memory’, thermal management, or a safety component, each not shown). A safety component may implement guardian and hazard-mitigation functions, and / or such functions may be embodied within software component 107. In various aspects, one or more of these components may be implemented in hardware, software, firmware, or any combination thereof. The components of device 100 are configured to capture information from the physical surroundings, process and render digital content, and facilitate interaction between real and- 13 -107298845 1PATENTAttorney Docket No. 130586-866348 virtual elements. In some implementations, functions attributed to a given component may be executed on the device, a companion device, or distributed across edge or cloud resources, and may be re-partitioned dynamically based on performance or power constraints.

[0086] The display component 101 may be embodied in any apparatus capable of presenting real-world imagery, computer-generated content, or a combination thereof. Implementations may include head-mounted displays (HMDs), optical or video see-through displays, stereoscopic displays, projection-based systems, or other visualization technologies. The display component 101 may be integrated into eyewear form factors. HMD housings, or handheld devices, and may incorporate optical assemblies such as waveguides, pancake lenses, or holographic combiners to adjust focus and provide a wide field of view suitable for immersive MR experiences. The display component 101 may employ any panel technology- capable of delivering high-quality visualization, such as OLED, micro-OLED, micro-LED, or LCD, and may be configured to support high-resolution rendering, high-frequency refresh rates, stereoscopic depth cues, varifocal or multifocal mechanisms (or software depth-of-field approximations) to present focus cues, adaptive brightness, user-adjustable blending of physical and virtual imagery, and dynamic spatial alignment of virtual elements with physical objects. The display component 101 is further configured to cooperate with the imaging component 102, tracking system component 104, and processor component 106 to ensure rendered imagery remains spatially aligned with physical objects and dynamically responsive to user movement. In representative implementations, displays may refresh at about 60-144 Hz (commonly 90-120 Hz), provide per-eye resolutions of about 1280x 1280 to 3840x3840, and deliver a diagonal field of view of about 70-120°. Varifocal or multifocal mechanisms may switch focal states in about 3-20 ms per transition. Temporal reprojection and alignment updates may operate at about 60-120 Hz to preserve visual stability- during head motion. Unless stated otherwise, all numerical values and ranges described throughout this disclosure are illustrative and non-limiting; 'about’ encompasses reasonable manufacturing and runtime tolerances as understood by persons of ordinary skill.

[0087] The imaging component 102 may include one or more sensors to capture visual information from the surrounding environment. Suitable sensors may include RGB cameras, depth cameras, LiDAR, structured-light sensors, stereoscopic camera pairs, infrared cameras, or any combination thereof. RGB and depth capture may operate at about 30-120 frames per second, with depth map resolutions of about 320x240 to 1024x768, and exposure integration- 14 -107298845 1PATENTAttorney Docket No. 130586-866348 times of about 1-10 ms. The imaging component 102 may be configured to supply captured frames to the processor component 106 and software component 107. which in turn employ the tracking system component 104 to anchor digital overlays in the physical environment. The captured data may be utilized for functions including, but not limited to, scene reconstruction, spatial mapping, anchoring of digital content, surface detection, object recognition, integration of live camera feeds into the rendered environment, or other operations that enable spatially accurate MR content. In some implementations, stereoscopic camera pairs, depth cameras, LiDAR, or structured-light sensors may be configured to generate distance estimates through trigonometric analysis, structured-light projection, or time-of-flight measurement for integration into the MR system. Depth latency from sensor to rendering may be maintained under about 15—35 ms to support depth-dependent operations within the rendering pipeline.

[0088] The sensor component 103 may include one or more sensors such as inertial measurement units (IMUs), environmental sensors, and biometric sensors. The sensors may output data, or sensor measurements (measurements). The one or more IMUs include sensors such as accelerometers, gyroscopes, magnetometers (e.g., electronic compasses), and are configured to provide motion, orientation, and position data for integration into the MR system, including but not limited to functions such as pose estimation, adaptive rendering, interaction, and safety monitoring. IMU fusion update rates may be about 400-1600 Hz. The one or more environmental sensors include devices such as barometers, ambient light sensors, proximity detectors, or temperature sensors, and are configured to provide environmental data for integration into the MR system, including but not limited to adaptive rendering, spatial mapping, safety monitoring, personalization, and multi-user synchronization. The one or more biometric sensors may include, without limitation, eye-tracking sensors (e.g., camera), heartrate photoplethysmography (PPG) monitors for physiological state detection, facial electromyography (EMG) electrodes for facial expression detection integrated into the facial interface (e.g., a removable gasket or padding) or provided via a supplemental wearable, electrodermal activity (EDA) sensors, electroencephalography (EEG), respiration and skintemperature sensors, microphones for voice-prosody features, other physiological sensors, alone or in any combination. The one or more biometric sensors may be configured to provide biometric data for integration into the MR system — including, but not limited to, the pipeline operations of FIG. 5 and additional processing pipelines of FIGS. 11, 19, 27, and 34, as further described herein. Sampling rates may be chosen from low, mid, or high-rate classes (e.g., about- 15 -107298845 1PATENTAttorney Docket No. 130586-8663481-50 Hz. 50-500 Hz, 500-2000 Hz, respectively) according to modality and latency budget, with all biometric data streams time-aligned to a common system clock. In certain eye-tracking implementations, LEDs and infrared cameras may be employed together with lens-adjustment mechanisms such as miniature motors to maintain optical alignment with individual eye positions, improving eye-tracking accuracy via calibration. Calibration may be performed initially and periodically (or continuously) to account for user movement and fit; biometric streams may be access-controlled and encrypted in transit and at rest. Sensor outputs from the sensor component 103 may be fused with imaging data by the tracking system component 104 to refine pose estimation and adaptive rendering, and may also be fused and / or synchronized with other system data streams for integration into any one or more processing pipelines within the MR system, as further described herein.

[0089] The tracking system component 104 may determine the position and orientation of the user’s head and body, the device, or objects within the environment. In some implementations, tracking may be performed using simultaneous localization and mapping (SLAM), which constructs and continuously updates a spatial map while estimating device pose, operating with visual inputs from the imaging component 102 and inertial inputs from the sensor component 103. Pose estimation may be refreshed at about 60-240 Hz, with map updates produced at about 10-60 Hz, and typical relocalization times of about 50-300 ms after transient loss. SLAM alone can provide robust performance for MR environments by maintaining alignment between real and virtual elements within a space. In other implementations, tracking may be achieved through inside-out techniques using onboard cameras and sensors, outside-in techniques using external cameras or beacons, marker-based approaches employing fiducial markers such as QR codes, markerless approaches relying on environmental features, inertial navigation, optical flow' analysis, or any combination thereof. Hybrid approaches are also contemplated, wherein inputs from cameras, inertial sensors, or external references are fused to estimate position, maintain an up-to-date spatial map, and align digital content with the physical environment. The tracking system component 104 may be configured to provide pose and map data for integration into the MR system, including but not limited to adaptive rendering, environment interaction, safety monitoring, and synchronization of virtual and real elements.

[0090] The environment interaction component 105 may provide multisensory feedback, interface with external devices, or both to enhance immersion. Implementations may include- 16 -107298845 1PATENTAttorney Docket No. 130586-866348 haptic wearables such as gloves, vests, or suits; handheld devices delivering haptic feedback; motion platforms; tactile surfaces; lighting control systems; projection surfaces or projectionmapping systems; environmental actuators, or any combination thereof. Spatial audio outputs, for example stage speakers and environmental actuators, may also be incorporated to generate context-aware soundscapes aligned with user position and orientation. In some implementations, the environment interaction component 105 may be configured to cooperate with the display component 101, the tracking system component 104, and other system components to ensure that non-visual feedback remains temporally and spatially synchronized with rendered content and physical movements, thereby maintaining coherent immersion across sensory channels. Haptic actuation latencies from command to perceptible response may be about 5-30 ms, and environmental actuator updates (e.g., lighting cues) may be frame- aligned within about ±10-25 ms of visual events.

[0091] The processor component 106 may include one or more CPUs, GPUs, system-on- chip (SoC) devices, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), neural processing units (NPUs), or any combination thereof. The processor component 106 may be configured to integrate neural network accelerators within SoC implementations to support Al-driven computer vision, machine learning inference, and related workloads. The processor component 106 may be configured to orchestrate data received from the imaging component 102, sensor component 103, and tracking system component 104, and to drive outputs to the display component 101, audio system component 109, and environment interaction component 105. In some aspects, the processor component 106 maintains or derives a common timebase to timestamp sensor, imaging, and audio data, enabling deterministic fusion and cross-device synchronization. Cross-stream skew between sensor, imaging, and audio timelines may be maintained within about ±0.5-2.0 ms following synchronization. Processing may be performed locally on the HMD, on a companion computing device, or distributed across an edge server or cloud system. In some implementations, processing may further be partitioned betw een the HMD, a local platform, and one or more networked servers to balance computational load, thermal constraints, and latency requirements. Representative motion-to-photon latency may be about <20-30 ms for on-device pipelines, about <35-50 ms with edge assistance, and about <60-90 ms with cloud assistance employing predictive smoothing. A dedicated co-processor can be incorporated for real-time sensor input processing. In addition, the processor component 106 may be configured to cooperate with system memory- 17 -107298845 1PATENTAttorney Docket No. 130586-866348(e.g., volatile RAM and non-volatile flash storage) to buffer captured frames, cache spatial maps, and store application data for retrieval during MR sessions, and may be supported by thermal management subsystems such as passive heat sinks, airflow channels, or active cooling elements to maintain comfort during prolonged use. Tasks performed by the processor component 106 include, but are not limited to, rendering graphics, processing and fusing sensor data, executing computer-vision and tracking algorithms, performing machine-learning inference, and coordinating interaction among device components.

[0092] The software component 107 may include operating systems, middleware, runtime engines, application frameworks, and application software, and in some implementations may further include software development kits (SDKs) and content libraries that collectively enable the execution of MR functions and the coordination of system components. In some implementations, the software component 107 may interoperate with standards such as OpenXR, WebXR, MPEG-I, or functional equivalents. Such interoperability is illustrative, and the inventive subject matter is not limited to any particular framework. MR functions executed by the software component 107 include, but are not limited to, rendering graphics, fusing data from the imaging component 102 and sensor component 103, executing tracking and recognition routines, implementing SLAM, managing removal and occlusion of real-world objects (e.g., segmentation / matting, depth-aware compositing, or masking), processing audio, and supporting user interface frameworks, while biometric analytics and adaptive content logic may be executed to tailor experiences based on user state or context. The software component 107 may also provide networking sendees to allow data exchange with remote servers, cloud platforms, or other MR devices. The software component 107 may coordinate with the processor component 106 to schedule computational tasks, interface with the input system component 108 and audio system component 109 to interpret user commands, and cooperate with the display component 101 and tracking system component 104 to maintain alignment between virtual and physical elements. In addition, the software component 107 may provide frameworks for three-dimensional user interfaces that are navigable through gesture input, gaze direction, voice commands, or multimodal combinations. Collectively, these capabilities allow the software component 107 to support higher-level system functions and ensure coordination across the MR system, including adaptive rendering, multimodal interaction, environmental adaptation, biometric-adaptive content, personalization, and multi-user synchronization. Software instructions implementing one or more of the foregoing functions may be stored on- 18 -107298845 1PATENTAttorney Docket No. 130586-866348 non-transitory computer-readable media and executed by one or more processors. In an example, multimodal information includes information, data, parameters, and / or attributes relating to one or more modals. Multimodal info may further include sensor measurements and / or environmental information.

[0093] The software component 107 may support a safety monitoring feature configured to provide user protection and safeguard physical well-being during MR operation. Such functionality may include guardian systems that define spatial limits, obstacle-detection mechanisms, collision-avoidance routines, and user alerts to prevent physical harm while immersed in MR activities. The safety monitoring feature may dynamically adapt its protective boundaries based on environmental conditions or user behavior, and may operate in coordination with the tracking system component 104 to monitor user position and orientation. The safety monitoring feature may further interact with the display component 101 to visually render boundary indicators, warning signals, or hazard overlays within the user’s field of view, thereby ensuring that protective cues remain perceptible and synchronized with the MR content. In some implementations, the safety monitoring feature may pause or modify rendered content when the user approaches a real-world hazard, and may adjust safety alerts in response to biometric signals, thereby maintaining immersive engagement while ensuring safe operation. In certain cases, the safety monitoring feature may initiate a controlled pause, fade, or transition to a pass-through state — in which real-world imagery' from the imaging component 102 is presented with minimal or no processing to preserve situational awareness — in response to signal loss, tracking degradation, or boundary violations. Safety’ monitoring may also operate under applicable compliance frameworks, including, without limitation, OSHA, ISO safety standards, or future equivalents.

[0094] The input system component 108 may include multimodal interfaces that facilitate user interaction within the MR environment and enable user transition between mixed, augmented, and fully virtual modes of immersion. Input modalities may be adaptive, supporting natural or device-based interaction, and may include handheld controllers with buttons or motion sensors, gesture-recognition systems, haptic gloves, touch-sensitive surfaces, microphones for voice input, or eye-tracking devices. Signals from the input system component 108 may be interpreted by the software component 107 and processed by the processor component 106 to update rendered content on the display component 101 and to trigger haptic, environmental, or stage-control effects through the environment interaction component 105. In- 19 -107298845 1PATENTAttorney Docket No. 130586-866348 some aspects, the user may be provided with input control over the proportion of virtual content versus real-world context displayed, expressed as a continuum ranging from minimal virtual overlays within a typical MR view to a complete perceptual replacement or occlusion of the physical background and surrounding environment.

[0095] The audio system component 109 may provide both output and input capabilities to support immersive interaction within the MR environment. Output functions may include the delivery' of spatially rendered audio, such as spatial, binaural, or ambisonic sound fields, to create directional and context-aware soundscapes that reinforce visual immersion. These functions are distinguished from environment-level audio delivered through the environment interaction component 105. Suitable output devices can include headphones, loudspeakers, earbuds, or bone-conduction transducers, each configured to reproduce audio cues that align with user position or scene dynamics. In some implementations, rendered playback may be individualized using head-related transfer function (HRTF) profiles derived from user measurements and updated using head-tracking data from the tracking system component 104. Input functions may include the capture of sound through one or more microphones or microphone arrays, enabling acquisition of user speech, ambient and environmental sounds, audience responses, or other audio signals for real-time processing, interaction, or communication. Spatialization updates (e.g., HRTF re-evaluation with head motion) may run at about 60-240 Hz, and audio output buffering may target about 5-20 ms end-to-end to preserve localization.

[0096] The audio system component 109 may operate in coordination with the tracking system component 104 to spatialize audio relative to user orientation and movement, and with the input system component 108 to enable or supplement voice-command interaction. In some implementations, the audio system component 109 may further integrate with the environment interaction component 105 to deliver stage audio or directional cues synchronized with physical or virtual events. In addition, the audio system component 109 may support multiuser synchronization so that audio experiences remain temporally and spatially coherent across multiple devices or audience members within the MR system. Inter-device audio skew- in multiuser sessions may be maintained within about <10-30 ms to ensure coherence with visual timing.

[0097] The connectivity' component 110 may provide wired and wireless communication pathways between the MR device 100 and external devices, services, or networks.- 20 -107298845 1PATENTAttorney Docket No. 130586-866348Communications may employ encryption, authentication, and time-synchronization protocols to protect data and align timestamps across devices. Supported interfaces may include Wi-Fi (e g., IEEE 802.11ax / 802.11be), Bluetooth (e g., 5.x), cellular, Ethernet, USB, HDMI, DisplayPort, ultra-wideband (UWB), optical links, or millimeter-wave channels (e.g., 60 GHz), each selectable to balance bandwidth, latency, and power consumption requirements. In some implementations, UWB may be used primarily for precise ranging and relative localization, while mmWave channels may be employed for high-throughput, low-latency data links. The connectivity component 110 may facilitate the exchange of spatial maps generated by the tracking system component 104 so that multiple MR devices 100 can maintain a consistent understanding of a shared environment. It may also enable the software component 107 to retrieve or stream remote content for rendering on the display component 101, and to communicate with cloud or edge servers for computational offloading and distributed rendering pipelines. In some implementations, the connectivity' component 110 may support low-latency, high-bandwidth communication suitable for real-time data exchange and multi-user synchronization, thereby ensuring coherent and responsive MR experiences across devices and locations. Network-contributed latency within the end-to-end motion-to-photon budget may be maintained within target thresholds suitable for immersive use. In addition, the connectivity component 110 may interface with external systems such as stage platforms, environmental sensors, or other networked infrastructure to coordinate digital content with physical elements of the MR environment.

[0098] The power supply (not shown) may furnish electrical energy required for operation of the MR device 100. Energy' delivery' may be provided through rechargeable batteries integrated into the device housing, auxiliary' battery' packs, tethered adapters, or standardized connectors such as USB-C or other standardized / proprietary power connectors. In some implementations, the power supply may further support swappable battery’ modules or wireless charging interfaces to extend operational availability and reduce downtime. Power management systems may distribute energy across system components — such as the processor component 106, display component 101, audio system component 109, environment interaction component 105, and connectivity component 110 — in order to balance performance requirements with runtime efficiency. Such management systems may implement techniques to regulate consumption, optimize allocation under vary ing workloads, extend operating- 21 -107298845 1PATENTAttorney Docket No. 130586-866348 duration, and maintain thermal stability- during prolonged MR sessions, optionally coordinating with passive or active cooling mechanisms integrated into the device.

[0099] By way of non-limiting example, the display component 101 may employ micro- OLED or micro-LED panels providing about 1280x 1280-3840x3840 pixels per eye at about 60-144 Hz, with waveguide optics configured to deliver a diagonal field of view of about 70- 120° and luminance of 1000 nits or more. The imaging component 102 may include dual 12- megapixel RGB cameras spaced about 55-70 mm apart for stereoscopic capture and a time-of- flight sensor generating 640 x 480 depth maps at about 30-120 fps and depth latency of about 15-35 ms. The sensor component 103 may deliver six-axis pose data at about 800 Hz or higher, with eye-tracking at about 120 Hz or higher, and biometric signals (e.g., heart rate) at about 60 Hz or higher. The processor component 106 may be a system-on-chip (SoC) with multi-core CPU. GPU with ray-tracing acceleration, NPU for machine-learning inference, and a dedicated sensor co-processor, with at least 8 GB of LPDDR5 memory. Ray-tracing may be selectively enabled or offloaded to edge resources subject to power / thermal budgets. Depending on compute locality7, motion-to-photon latency may be less than about 20-90 ms, and inter-user skew may be bounded at less than or equal to about 10-40 ms. The audio system component 109 may include wireless in-ear devices or similar outputs for ambisonics or other spatial cues, with integrated microphones capturing user voice or ambient sound. The connectivity component 110 may support Wi-Fi 6 / 6E or later, Bluetooth 5.x, or millimeter -wave links; WiFi and mmWave may provide effective throughput of about 1-4 Gbps with round-trip latencies of about 5-20 ms, while Bluetooth 5.x may support low-power control and peripheral connections. The power supply (not shown) may include a rechargeable lithium-ion battery pack for multi-hour operation, supplemented by power management circuitry. These values are illustrative only and not limiting; actual performance figures may vary7by implementation.

[0100] While illustrated in the context of a representative device, the arrangement of FIG. 1 is not limited to the specific components or interconnections shown. The device architecture may be embodied in HMDs, wearable devices, handheld controllers, computing platforms, or distributed or cloud-edge systems, and may be adapted, reconfigured, combined, omitted, or supplemented with additional elements without departing from the scope of the disclosure. In various aspects, the described architecture may be implemented as a standalone unit, integrated into multi-device ecosystems, or partitioned across local, edge, or cloud infrastructure, thereby underscoring the modularity and flexibility of the system.- 22 -107298845 1PATENTAttorney Docket No. 130586-866348

[0101] Having described an example of an MR device architecture with reference to FIG. 1, attention is now directed to FIG. 2. which illustrates an example of a mixed reality environment in accordance with aspects of the present disclosure. In this aspect, the device architecture may be deployed to support a theatrical production in which live performance elements are combined with interactive digital content. The illustrated mixed reality environment (hereinafter, “MR theater environment"’) is shown in generalized form to demonstrate how physical and digital elements may be coordinated within a live performance venue, with device components such as the tracking component 104, environment interaction component 105, and connectivity component 110 of FIG. 1 cooperating with environmental systems to maintain spatial and temporal coherence. Although described in the context of theater, it will be understood that the device architecture described with reference to FIG. 1 and the MR environment of FIG. 2 may likewise be adapted for personal, enterprise, educational, entertainment, or other contexts without departing from the scope of the present disclosure.

[0102] As shown in FIG. 2, the MR theater environment may include a theater 200 having a stage 210 occupied by one or more actors 212 and one or more physical props 214. The stage 210 may further host digital elements, such as a digital backdrop 216 and one or more interactive elements 218, which may include digital props, holographic characters, visual overlays, or other computer-generated assets rendered through MR devices and, in some implementations, configured to respond dynamically to actor input or performance cues, stage conditions, and / or audience interaction. The MR theater environment 200 may also include an audience seating area 220 including one or more seats 222, each of which may optionally be equipped with a seat sensor 224 configured to detect audience presence, movement, engagement, biometric signals, and / or combinations thereof. Above the seating area 220, an auditorium environment 230 may incorporate one or more environmental sensors 232, an advanced lighting system 234, and a spatial audio speaker array 236, each of which may cooperate with or be synchronized to digital content to augment the live performance. A backstage 240 may include a computer server room 242 that houses a mixed reality theater production server 244, which may orchestrate, synchronize, and distribute MR content across the environment. While FIG. 2 illustrates a representative arrangement, the MR theater environment 200 is exemplary and not limited to the form shown, and variations in the number, placement, or configuration of the elements — including adaptations, rearrangements,- 23 -107298845 1PATENTAttorney Docket No. 130586-866348 substitutions, or supplementation with additional components — are contemplated without departing from the scope of the present disclosure.

[0103] The stage 210 may serve as a performance area in which physical and digital elements are combined. The stage 210 may support projection systems, motion capture systems, or MR displays that enable integration of live performance with digital overlays. One or more actors 212 may occupy the stage 210 to perform alongside digital content rendered in real time, including holograms, animated characters, and / or augmented visual effects. The one or more actors 212 may interact with and / or manipulate physical props 214, digital props rendered via the interactive elements 218 of the MR theater environment, or hybrid props incorporating physical and digital features, any of which may be configured to respond dynamically to actor input, performance cues, stage conditions, and / or audience interaction. The physical props 214 may include tangible objects manipulated by actors, and may be supplemented or substituted with digital objects generated in the MR theater environment. Physical props 214 may further serve as tracked anchors for spatially registered digital content. The digital backdrop 216 may present imagery, video, or three-dimensional environments projected, displayed, or rendered via MR devices, and may dynamically update in real time in response to stage action, audience interaction, or production control inputs to augment or replace portions of the physical scenery. Tn some aspects, the digital backdrop 216 may integrate both pre-rendered graphics and live video feeds composited in real time to provide dynamic scenery. The one or more interactive elements 218 may include any combination of physical and / or virtual objects responsive to actor and / or audience input, including projected effects, virtual characters, or digital interfaces anchored in stage space, each capable of influencing narrative progression or visual presentation. The interactive elements 218 may be spatially registered and aligned with the physical stage using tracking and rendering techniques. Registration and alignment may be maintained using SLAM and spatial mapping operations, enabling persistent anchoring of the digital backdrop 216 and interactive elements 218 relative to the stage 210 and audience seating area 220 (see FIG. 6). To that end, interactive elements 218 and related stage operations may utilize one or more core MR operations as further described herein with reference to FIGS. 7- 10, including, without limitation, object removal and occlusion, viewpoint manipulation, virtual position movement, and live camera feed integration, and combinations thereof.

[0104] The audience seating area 220 may accommodate one or more spectators arranged in rows, tiers, or alternative layouts. The audience seating area 220 may be fixed, modular, or- 24 -107298845 1PATENTAtorney Docket No. 130586-866348 adaptive, permiting both traditional seating and immersive configurations. The audience seating area 220 may include one or more seats 222. each of which may optionally include seat sensors 224 configured to detect occupancy, movement, interaction inputs, biometric signals, or other engagement data. Data collected by the seat sensors 224 may be provided to the mixed reality' theater production server 244, which may execute adaptive algorithms configured to analyze one or more of audience interaction, biometric data, and engagement paterns, thereby enabling real-time content adaptation, personalization, synchronized audience effects, and other collective interaction-driven responses. Audience members may engage through MR devices (e.g., HMDs or AR glasses), companion devices (e.g., smartphones or tablets), wearable devices, mobile applications, and / or networked controllers operable to capture votes, preferences, or direct interactions with the MR theater environment, thereby enabling subgroup-specific or geolocation -based content delivery. These devices may receive synchronized content, interaction prompts, or supplemental narrative elements and may accept audience gesture inputs or voice commands as interaction modalities in addition to seat sensors and applications. In certain aspects, such data collection, interactions, and analyses may interoperate with the biometric-adaptive content framework as further described herein with reference to FIGS. 11-16. See also FIGS. 19-26 for user personalized content and FIGS. 34- 39 for location-based pipelines.

[0105] The auditorium environment 230 may include environmental instrumentation, immersive feedback systems, and infrastructure arranged above, around, or otherwise integrated with the audience seating area 220, and / or elsewhere within the theater. One or more environmental sensors 232 may detect audience movement, gestures, biometric signals, and / or physical conditions such as light levels, sound levels, temperature, motion, atmospheric properties, or other contextual conditions, in any combination. The environmental sensors 232 may further include optical cameras or depth-sensing arrays configured to track performer and / or audience gestures and positions across the stage, thereby supporting real-time interaction between physical actors and digital elements. The advanced lighting system 234 may include controllable illumination devices configured to modulate color, intensity', direction, and / or focus in real time, and may dynamically adapt stage or auditorium illumination in coordination with digital effects. The spatial audio speaker array 236 may provide audience-wide delivery, seat-specific targeting, and / or audio output rendered relative to individual user positions (e.g., spatial audio, directional audio, ambient sound cues, or- 25 -107298845 1PATENTAttorney Docket No. 130586-866348 immersive soundscapes) aligned with virtual and physical content within the MR theater environment. In some implementations, the spatial audio system may further provide individualized or narrative-specific audio streams delivered to personal MR devices or headsets, enabling audience members to access supplementary information such as character motivations, scene context, or background narrative elements. In some aspects, the auditorium environment 230 may also include atmospheric or haptic feedback systems, such as fog generators, temperature-control devices, or vibratory actuators integrated into seating or flooring, configured to deliver kinesthetic or environmental cues synchronized with MR effects.

[0106] The backstage 240 may include infrastructure configured to support MR production, orchestration, and synchronization. A computer server room 242 may house one or more servers, including the mixed reality theater production server 244. The production server 244 may be configured to coordinate rendering pipelines, manage content and effects, and render and maintain shared spatial maps; synchronize digital content and physical stage effects with live performance cues; process sensor data from audience, stage, and environmental sources; and distribute rendered media streams to MR devices worn by audience members and / or to stage display systems. In some implementations, assets (e.g., models, textures, materials, audiovisual elements) may be retrieved from an asset management system (AMS) and integrated into a rendering engine, with SLAM-based registration executed by the production sen- er 244 and / or by MR devices to maintain alignment relative to the stage 210 and audience seating area 220. The production server 244 may further facilitate multi-user synchronization, adaptive scene logic, and coordination between physical and digital effects. The production server 244 may operate locally within the theater, remotely via cloud services, or in a hybrid arrangement. In some aspects, the production server 244 (e.g., operating as an analytics server) may execute analytics, including biometric analytics loops configured to adapt pacing or intensity of digital content in response to audience physiological responses, to perform scene scoring based on aggregated audience and performance data, and to derive analytics indicative of engagement levels or narrative effectiveness, and may further support auxiliary logic layers for sponsorship, monetization, or other context-specific enhancements. In some aspects, the production server 244 may also enable social or collaborative audience features, including sharing of reactions, ratings, and / or votes across networked devices, thereby allowing collective audience input to influence narrative progression or production control. In certain- 26 -107298845 1PATENTAttorney Docket No. 130586-866348 aspects, one or more of the foregoing analytics and audience-interaction features are implemented with opt-in consent controls and data protection safeguards (e.g., access controls, pseudonymization, and encrypted transport and storage), as further illustrated in FIG. 17, in accordance with applicable privacy requirements. In some implementations, the production server 244 forms part of the system topology of FIG. 3 and interfaces with the MR engine and operations pipeline of FIG. 5, as further described herein. Consent controls and privacy safeguards configured for the MR theater environment are evaluated and enforced during adaptive operation as described with reference to the consent / privacy controls of FIG. 4B. Consent controls and privacy safeguards may be evaluated and enforced in accordance with compliance frameworks, including, without limitation, GDPR, HIPAA, or future equivalents.

[0107] By way of non-limiting example, the stage 210 may include projection mapping systems capable of projecting 4K imagery at 120 Hz onto surfaces, synchronized with actor positions from motion capture sensors. The digital backdrop 216 may be a real-time 3D scene rendered by a game engine (e.g., Unity or Unreal Engine), updated dynamically with actor gestures or narrative progression. Interactive elements 218 may include holographic characters or virtual props responsive to actor gestures or audience inputs. Seat sensors 224 may include accelerometers, pressure pads, infrared occupancy detectors, or biometric contact sensors to measure posture, heart rate variability, or motion levels. Environmental sensors 232 may include depth cameras, LiDAR, or thermal sensors to track audience movement and engagement. Advanced lighting system 234 may employ programmable LED arrays to vary intensity, color, or directionality in sync with MR effects, and / or motorized spotlights with frame-accurate synchronization. Spatial audio speaker array 236 may include distributed speakers or earbuds, delivering spatial audio, Ambisonics, or binaural cues localized by tracked user position, seating zone, or seat. The mixed reality theater production server 244 may be an edge server with multi-core CPUs. GPUs with ray-tracing acceleration, and NPUs, configured to manage distributed rendering pipelines, synchronize MR content with live cues, execute adaptive scene logic, and in some aspects maintain sub-20 ms end-to-end latency between performance actions and MR effects. These values are illustrative only and not limiting; actual performance figures may vary by implementation.

[0108] While the aspect of FIG. 2 is described in the context of a representative mixed reality theater environment, it will be understood that the illustrated arrangement is not limiting. The elements shown — including stage 210, actors 212, physical props 214, digital backdrop 216,- 27 -107298845 1PATENTAttorney Docket No. 130586-866348 interactive elements 218, audience seating area 220, seat sensors 224, auditorium environment 230, environmental sensors 232, advanced lighting system 234. spatial audio speaker array 236, backstage 240, server room 242, and production server 244 — may be rearranged, substituted, omitted, or supplemented in alternative configurations to suit other performance venues, entertainment formats, or collaborative environments. Accordingly, the disclosure encompasses not only the particular arrangement depicted but also variations that provide comparable functionality in different physical or digital contexts and / or arrangements. Subsequent figures illustrate example system topologies and processing pipelines that may be employed within the environment of FIG. 2.

[0109] Having described a representative MR device architecture with reference to FIG. 1 and an example MR theater environment with reference to FIG. 2, attention is now directed to FIG. 3, which illustrates an example topology of a mixed reality system, in accordance with aspects of the present disclosure. As shown, the topology may include a core mixed reality engine 301 communicatively coupled with multiple subsystems that, in concert, support execution of functional operations and algorithms for enabling and adapting the MR theater experience. The arrangement of FIG. 3 is presented in generalized form to demonstrate how inputs from audience members, stage elements, and environmental systems can be orchestrated by the core mixed reality engine 301 to produce synchronized MR outputs for MR devices and supporting systems. Although described in the context of a theater environment, the system topology of FIG. 3 may likewise be implemented in personal, enterprise, educational, entertainment, or other contexts without limitation.

[0110] The core mixed reality engine 301 may coordinate and orchestrate functionality across the subsystems 302-305 to maintain global runtime state (e.g., spatial representations and context signals), manage timing and synchronization across MR devices and environmental systems, and broker data exchange among subsystems and / or their respective components. In some aspects, the core mixed reality engine 301 maintains persistent spatial maps that may be updated dynamically to stabilize anchoring, occlusion handling, and viewpoint control across the MR experience.

[0111] An audience interface and interaction subsystem 302 may be configured to provide client-facing functions. The audience interface and interaction subsystem 302 may enable spectators or participants to access, view, and interact with MR content through HMDs, AR glasses, handheld devices, or other client platforms, and may support multimodal input —- 28 -107298845 1PATENTAttorney Docket No. 130586-866348 including gaze, gesture, voice, and controller / touch — while providing per-user interface elements, personalized overlays, and per-user audio streams with cross-device continuity of interactions for each user and their respective devices (e.g., a user’s HMD, smartphone, and other companion devices).

[0112] A physical environment instrumentation subsystem 303 may be configured to provide sensor-data ingestion from a variety of environmental sensors including optical cameras, depth cameras, LiDAR, motion-capture inputs, motion detectors, seat-embedded sensors, acoustic sensors, infrared sensors, thermal sensors, other environmental sensors, or any combination thereof. The physical environment instrumentation subsystem 303 may supply sensor inputs capturing stage conditions, environmental context, audience engagement signals, and / or other environmental data. Captured sensor data may be supplied to the core mixed reality engine 301 for fusion into spatial representations (e.g., global spatial maps) and audience-engagement profiles, and for feature detection and tracking of physical elements within the environment and alignment with live performance cues.

[0113] A mixed reality processing and rendering subsystem 304 may be configured to provide core runtime execution. The mixed reality processing and rendering subsystem 304 may execute real-time graphics and audio pipelines together with spatial mapping and synchronization (e.g., via SLAM) and other core MR operations described herein — including object removal / occlusion, viewpoint manipulation, virtual position movement, and live camera feed integration (see FIGS. 5-10), to maintain low-latency, frame-aligned operation relative to system timing references and coherent multi-user synchronization (e.g., viewpoint updates at least 60 Hz and live-feed integration less than 100 ms). As used herein, ‘‘system timing references” include one or more of display refresh cycles, sensor-sampling cadences, cameraintegration windows, and / or external timing triggers. In some aspects, SLAM constructs and updates a persistent three-dimensional point-cloud or voxel map while localizing the HMD for stable anchoring and occlusion handling. Spatial-mapping data, computer- vision outputs (e.g., feature detection / segmentation). and / or object-recognition results may be semantically fused to inform decision logic governing whether detected elements are occluded, removed, emphasized, or otherwise transformed within the rendered scene. In some aspects, outputs of these operations are emitted as contract-bound messages carrying presentation timing and synchronization metadata that downstream orchestration modules may admit or reject for deterministic, frame-aligned rendering.- 29 -107298845 1PATENTAttorney Docket No. 130586-866348

[0114] A content and experience management subsystem 305 may be configured to provide media management, adaptive control, and other control logic operable to tailor the MR experience. The content and experience management subsystem 305 may manage media assets, execute adaptive scene logic including narrative progression, audience-driven branching, and modulation of audiovisual salience; it may further derive engagement analytics (e.g., biometric-driven metrics and scene scoring), perform biometric-driven adaptation, provide peruser content personalization, and govern location-based content integration, including sponsorship overlays, targeted delivery (e.g., region-specific or group-specific), and / or monetization logic, with secure retrieval and caching of assets to help ensure consistent presentation across audience devices. In some aspects, user preference profiles may be maintained across sessions to adapt future performances. Adaptive decisions may be expressed as selectors — validated parameter sets identifying scope, target module, value set, lifetime, and provenance — which are applied under policy, consent, and capability checks as further detailed with reference to FIGS. 4A-4B.

[0115] Through the coupling shown in FIG. 3, the core mixed reality engine 301 may integrate inputs and outputs from subsystems 302-305 to analyze real-world conditions, adapt content dynamically, and deliver synchronized MR effects throughout the theater environment. Tn later figures, the core mixed reality engine 301 is shown internally as 401, with interface surfaces of the audience interface and interaction, physical environment instrumentation, mixed reality processing and rendering, and content and experience management subsystems 302-305 depicted as 402-405. While the system topology of FIG. 3 is described in the context of a theater environment, it will be understood that the illustrated arrangement is non-limiting. The depicted subsystems may be rearranged, subdivided, omitted, or supplemented with additional components (e.g., cloud / edge orchestration layers or dedicated analytics sendees) without departing from the scope of the present disclosure. Accordingly, the disclosure encompasses not only the particular configuration depicted in FIG. 3, but also variations that provide comparable functionality in different physical, digital, or hybrid environments. Details of engine internals may be further described with reference to FIGS. 4A-4B, and example MR software operations are illustrated in FIGS. 5-10.

[0116] Having described device architecture with reference to FIG. 1, environment context with reference to FIG. 2, and a system topology with reference to FIG. 3, attention is now directed to FIGS. 4A-4B, which respectively illustrate an interface and protocol layer and a- 30 -107298845 1PATENTAttorney Docket No. 130586-866348 control and orchestration layer of a core mixed reality engine 401. The interface and protocol layer defines standardized surfaces and exchange contracts through which all subsystems interact. The control and orchestration layer governs timing, traffic, policy, and synchronization, which control how sensor inputs, spatial maps, and media streams are admitted into core processing, how adaptive logic is applied, and how outputs are distributed to audience HMDs. The control and orchestration layer bridges lower-level capture and fusion processes with higher-level adaptive operations (e.g., biometric-adaptive content, personalized content, personalized characters, and location-based content integration).

[0117] In various aspects, the software operations and adaptive control processes described herein (e.g., SLAM, object removal and occlusion, viewpoint manipulation, virtual position movement, live camera feed integration, biometric-adaptive content, personalized content, personalized characters, and location-based content integration) may be coordinated not only through direct module interfaces, but also through standardized exchange semantics. Outputs of these operations may be normalized into structured update sets carrying identifiers, timing tokens, and synchronization metadata, providing a convenient formalism for module flows that feed data forward through rendering and analytics pipelines described throughout this disclosure. In certain aspects, these update sets may be referred to as ‘"authenticated parameter sets” and may be exchanged within a logical interface and protocol layer. Constructs such as lane classification, present-by windows, render beacons, selectors, and inter-user skew correction should therefore be understood as exemplary control-plane mechanisms for implementing the timing, arbitration, and coordination already implicit in the described pipelines. These constructs provide a convenient vocabulary for ensuring determinism, bounded latency, and policy compliance, without limiting the invention to any particular nomenclature, algorithm, or architectural partition. As such, the foregoing is non-limiting, and functionally equivalent mechanisms may be substituted without departing from the scope of the present disclosure.

[0118] As used herein, a “lane” denotes a logical priority class applied to authenticated parameter sets that can determine ordering and arbitration policies for admitted traffic; a “lane source” denotes a producer of engine-managed traffic that can inject parameter sets into a designated lane; a “lane endpoint” denotes a consumer or sink that can process traffic admitted to a lane; a “present-by window” denotes a delivery deadline relative to a system timing reference that can govern presentation of content at a rendering endpoint; a “render beacon”- 31 -107298845 1PATENTAttorney Docket No. 130586-866348 denotes a periodic frame-level timing beacon or event-driven signal that can establish or reinforce a shared system timing reference among subsystems; a "selector’ denotes a validated parameter set that can govern adaptive behavior for imminent frames; and a ‘Tender contract” denotes a presentation-level declaration, carried as an authenticated parameter set, that can specify one or more of timing and delivery constraints, resource requirements, or quality obligations governing outputs to one or more endpoint modalities or classes (e.g., visual, audio, haptic, environmental actuator, or network stream). Such contracts are not limited to per-frame scope and may be issued per-frame, per-buffer, per-segment, per-scene, or for a bounded continuous interval. Control-plane services shown in FIG. 4B, via modules 430-447, collectively implement and enforce the interface and protocol mechanisms introduced herein — including lane classification, present-by windows, render beacons, selectors, and inter-user skew correction — and admit, order, and synchronize adaptations with bounded latency across subsystems, without limitation.

[0119] Each module enumerated in FIG. 4A participates in the interface and protocol layer, either as a producer or consumer of authenticated parameter sets. Each authenticated parameter set carries a normalized header including metadata primitives including, without limitation: identification fields; ordering disciplined to system timing references (e.g., timing token , lane and priority classification (e.g., traffic lane tag} version and integrity metadata; synchronization markers (e.g., sync marker}, and a delivery' term such as a present-by window or expiry (e.g., present by window The normalized header may further include extensible fields such as time-to-live (e.g., TTL), provenance metadata (e.g., provenance} capability declarations (e.g., capability descriptor), policy flags (e.g., policy Jlag), and selector identifiers (e.g., selector id). These metadata primitives are admitted, enforced, and synchronized by the control and orchestration layer of FIG. 4B to govern timing, traffic, policy, selector application, and multi-user synchronization. The control plane distributes render beacons and admits the authenticated parameter sets with consent validation and capability negotiation. Traffic on engine-managed lanes is classified (e.g., critical, interactive, background) with bounded queue depths and back-pressure signaling to enable graceful degradation under load.

[0120] Turning now to FIG. 4A, the audience interface and interaction subsystem 402 provides ingress for audience inputs, encompassing device states, gestures, and preferences. It exchanges normalized interaction events w ith the content and experience management- 32 -107298845 1PATENTAttorney Docket No. 130586-866348 subsystem 405, which curates narrative logic: and with the mixed reality processing and rendering subsystem 404, which applies the events to viewpoint and spatial transformations. The physical environment instrumentation subsystem 403 integrates venue-level signals, including stage tracking 412, spatial mapping 413, and environmental sensors 411, each of which emits schema-bound updates carry ing coordinate frames and temporal tokens to anchor digital overlays to the live environment.

[0121] The mixed reality' processing and rendering subsystem 404 encompasses the primary mixed reality software operations. It includes SLAM 414 for spatial anchoring, removal and occlusion 415 for hiding real-world objects, viewpoint manipulation 416, virtual position movement 417, and live camera feed integration 418. Each operation emits contract-bound outputs to the rendering engine 419, which sen es as the sink for all visual and compositing flows. The rendering pipeline may issue per-frame render contracts that declare budgets and present-by deadlines; participating modules may return timing reports that the control plane uses for budget governance and lane arbitration. For example, SLAM 414 provides updated maps with synchronization markers; removal and occlusion 415 emits segmentation masks with present-by deadlines; and camera feed integration 418 delivers encoded video textures carrying latency and blending descriptors.

[0122] The content and experience management subsystem 405 serves as the locus of narrative control and selector generation. It may consume biometric analytics via the biometric system 423, personalization inputs from personal devices 408 via personalization module 424, and asset retrievals via content asset management 420. It may emit selectors that specify scope, target module, value set, lifetime, and provenance. These selectors become authenticated parameter sets under the interface and protocol layer and are eligible for deterministic application by the selector broker and policy modules of FIG. 4B. The content and experience management subsystem 405 may also interface the analytics module 421 for scene effectiveness scoring and the socialization module 422 for coordinating collaborative or audience-influenced plot directions.

[0123] The audience-facing hardware and input modalities are explicitly incorporated into FIG. 4A to demonstrate ingress pathways. HMDs 406, input modalities 407 (e.g., gestures, voice, controllers), and personal devices 408 (e.g., smartphones) are authenticated through the interface and protocol layer and provide raw input streams. Adaptive seating 409, seat- embedded sensors 410, and environmental sensors 411 capture contextual, physiological, and- 33 -107298845 1PATENTAttorney Docket No. 130586-866348 positional data from audience members, each producing contract-bound outputs with privacy and consent metadata. Stage tracking 412 and spatial mapping 413 similarly feed positional anchors into the mixed reality processing pipeline, where SLAM 414 consolidates them into a consistent map. Control signaling may include flow-control advisories, lane assignment notices, acknowledgments, policy updates, and production cue updates aligned to external show-control timelines.

[0124] Downstream of processing, the rendering engine 419 executes composite scene generation by consuming the outputs of SLAM 414. removal and occlusion 415, viewpoint manipulation 416, virtual position movement 417, and camera feed integration 418, together with adaptive overlays authorized by selectors from the content and experience management subsystem 405. Rendering engine 419 may consume and honor present-by windows and synchronization markers as admitted and enforced by the control plane of FIG. 4B (including system timing service 430, render beacon 431, and present-by manager 444), so that adaptive content is visually aligned with live performance and / or stage cues. Content asset management 420 supplies the rendering engine 419 with approved digital assets, including props, backgrounds, sponsor material, and location-based content retrieved via secure queries and caching pipelines.

[0125] The content and experience management subsystem 405 may also enable enhanced interaction within an MR theater environment. In some aspects, the analytics module 421 receives biometric, interaction, and content-outcome data to generate effectiveness scores, which are distributed through the control and orchestration layer of FIG. 4B (via event router 446) for audit and adaptation. The socialization module 422 enables multi-user experiences, distributing shared state so that personalized renderings still maintain global narrative coherence. The biometric system 423 captures and normalizes biometric and physiological parameters such as heart rate, gaze, facial expression, and head motion signals, binding them to anchors for scene scoring and adaptive feedback. The personalization module 424 admits smartphone-derived media under consent, preprocessing it into narrative-ready assets. The character personalization module 425 manages per-user avatar substitution, isolating private textures and meshes while providing consistent global animation vectors. Inter-user timing offset (also referred to herein as inter-user skew) is constrained within declared bounds so that personalized renderings preserve global narrative coherence. The location-based assets module 426 receives geolocation context objects, queries content asset management 420 or an external- 34 -107298845 1PATENTAttorney Docket No. 130586-866348 asset management system, and supplies region-specific content such as props, scenery, and sponsored content, each tagged with compliance and campaign metadata. Consent and privacy metadata embedded at this layer are evaluated and enforced by the control and orchestration layer of FIG. 4B (via consent / privacy 439), whereby inputs and selectors are gated (via capability / negotiation module 440) prior to selector commitment or adaptive rendering.

[0126] These modules interact through the interface and protocol layer by exchanging authenticated parameter sets rather than ad hoc data streams. For example, biometric system 423 may output gaze vectors tagged with anchor IDs. which may be consumed by the content and experience management subsystem 405 and scored by the analytics module 421. Personalization module 424 may output curated media objects tagged with provenance, which may be routed to rendering engine 419 via content asset management 420. Character personalization module 425 may consume avatar textures from personalization module 424 and may apply them to placeholder actors mapped by stage tracking 412. Location-based assets module 426 may retrieve content from content asset management 420 and deliver it to rendering engine 419 with compliance flags that are evaluated and enforced by policy controls downstream. In each case, the interaction may be mediated by standardized contracts that encode timing, priority, and policy markers, ensuring orchestration by FIG. 4B remains deterministic and compliant. Lane policies may include acknowledgments, retry and deduplication rules to ensure ordered, exactly-once or at-least-once delivery as declared by the contract. Specific arbitration policies (e.g., weighted-fair queuing, deadline-aware dropping) may be employed; such policies are implementation-dependent and non-limiting.

[0127] Accordingly, FIG. 4A demonstrates how the core mixed reality engine 401, together with subsystems 402-405 and modules 406-426. establishes an interface and protocol layer that normalizes all signals and assets into authenticated parameter sets. By defining schemas, tokens, and metadata fields for subsystem interactions — including those supporting biometric analytics, per-user personalization, per-user avatar substitution, and location-based content — this layer provides the foundation for the control and orchestration layer of FIG. 4B to enforce timing discipline, traffic shaping, policy conformance, and synchronization across the collective MR theater experience.

[0128] In various aspects, these exchanges may occur over wired or wireless transports (e.g., Wi-Fi, BLE, UWB), with processing partitioned across HMD, edge, or cloud nodes. Functions attributed to the core mixed reality engine 401 may execute on device, at the edge, or in the- 35 -107298845 1PATENTAttorney Docket No. 130586-866348 cloud; the interface contracts and timing semantics remain invariant to such deployment variations. Although described with reference to a theater environment, the disclosed interface and protocol layer of FIG. 4A applies broadly to any multi-user mixed reality environment, including but not limited to industrial training, classroom learning, remote collaboration, and consumer entertainment settings. Variations in hardware, deployment topology, sensor configuration, and device class remain within the scope of the present disclosure.

[0129] Turning now to FIG. 4B, the control and orchestration layer may be organized into four operational control-plane groups: (i) timing, (ii) traffic-management, (iii) policy and selector, and (iv) synchronization and observability. This layer translates declarative contracts into executable schedules that preserve frame-aligned operation, mitigate inter-user skew, and ensure deterministic selector application across subsystems 402-405. In operation, controlplane signaling within these groups applies contract metadata from the interface and protocol layer — timing tokens and present-by windows, lane tags, selector / policy flags, and synchronization markers — to admit, order, and enforce adaptations deterministically across the subsystems. A core engine control fabric (a unified bus) couples modules 430-447 with subsystems 402-405, and control-plane signaling traverses that fabric to propagate timing, traffic, policy, and synchronization decisions with bounded latency, enabling deterministic enforcement of present-by windows and inter-user skew bounds. As used herein for controlplane operation, a “lane” denotes a logical priority class; “lane sources” and “lane endpoints” denote producers and consumers of engine-managed traffic.

[0130] The timing group of modules establishes a common temporal and spatial foundation for all operations. A system timing service 430 may provide globally consistent clocking signals that align input capture with rendering deadlines. A render beacon 431 may emit frame- aligned pulses that coordinate software operations such as removal and occlusion, viewpoint manipulation, virtual position movement, and camera feed integration, ensuring that adaptive updates enter the pipeline without frame drops. A coordinate-frame sen ice 447 may bind temporal ticks to spatial reference frames, ensuring that SLAM maps, anchor positions, and lines of sight (e.g., audience gaze vectors) remain coherent when biometric feedback or personalized overlays are applied. Representative operations may include: distributing render beacons; applying validated selectors; issuing per-frame render contracts; receiving acknowledgments and timing reports; applying flow-control advisories when budgets tighten; and correcting inter-user skew.- 36 -107298845 1PATENTAttorney Docket No. 130586-866348

[0131] The traffic-management group ensures that heterogeneous flows from capture, fusion, and rendering stages are delivered within bounded latency, admitting, ordering, and enforcing present-by semantics via present-by manager 444 so that late or stale items are dropped before they reach the rendering engine 419. A lane manager 432 may separate traffic such as biometric signals, live video feeds, and adaptive content streams into prioritized lanes (e.g., critical, interactive, background). A flow-control manager 433 regulates throughput and may issue back-pressure advisories to upstream lane sources based on queue-depth and timing-slack assessments relative to present-by manager 444, thereby mitigating overload at downstream processing stages (e.g., sensor fusion, spatial mapping). Watermark / hy steresis 434 may stabilize insertion of adaptive overlays, preventing oscillation when multiple biometric or policy events occur in close succession. A deadline dropper 435 may perform deadline-aware dropping by discarding expired frames or late-arriving updates, as declared in the present-by windows defined at

[0094] with reference to FIG. 4A; this preserves synchronization in operations such as removal and occlusion, viewpoint manipulation, and virtual position movement. Deadline Dropper 435 may also discard items whose present-by window expires prior to the next render beacon 431, preventing stale masks or camera textures from corrupting composite timing. A queue manager 436 may order remaining packets for processing by adaptive logic, while a present-by manager 444 may further enforce hard timing bounds so that scene adaptations are delivered in sync with live performance and / or stage cues. Illustratively, per-lane queue depths may be about 1-3 frames for critical lanes, 2-6 frames for interactive lanes, and 4-12 frames for background lanes, with deadline drop policies discarding items that cannot meet their present-by windows.

[0132] The policy and selector group provides the decision layer through which adaptive behaviors are admitted. A session / authenti cation (sess / auth) surface 437 validates each user session and may establish the trust context for downstream processing. A selector broker 438 receives validated selectors generated by the content and experience management subsystem 405 and may arbitrate their deterministic order of application across (i) target modules (e.g., SLAM 414, removal and occlusion 415, camera feed integration 418) and (ii) control-hook logic within subsystem 405 (e.g., narrative-branching or pace-adjustment hooks). Consent / privacy 439 may enforce user permissions before biometric features, personal media, or avatar data are acted upon. A capability / negotiation module 440 may evaluate whether a device can safely perform operations such as high-resolution removal and occlusion or- 37 -107298845 1PATENTAttorney Docket No. 130586-866348 character substitution. A policy engine 441 may apply production rules to govern, for example, whether location-based content such as sponsored assets may be inserted at a given location, or whether adaptive scene pacing can be invoked. A show-control adapter 442 may allow directors to trigger, override, or condition selector application in real time, linking theatrical direction with automated orchestration logic.

[0133] The synchronization and observability' group maintains coherence across distributed participants and provides instrumentation for adaptive decision-making. An inter-user sync service 443 may ensure that anchor alignment, placeholder character animations, and scene timing remain consistent across the audience, even as each HMD may render different personalized avatars or overlays. Inter-user sync service 443 may also maintain presentation skew within an exemplary bound of about 10-30 ms, without limitation. A telemetr / health module 445 may collect metrics on latency, sensor fidelity, and selector outcomes, enabling proactive adjustments and providing audit logs for compliance. An event router 446 may distribute system events, revocations, and effectiveness scores derived from analytics module 421 and biometric system 423 to the relevant modules, according to lane priority' and policy, ensuring that adaptive feedback is both localized to the individual viewer and harmonized across the collective audience experience.

[0134] Collectively, the modules of FIG. 4B demonstrate how the control and orchestration layer of the core mixed reality engine 401 overlays timing discipline, traffic shaping, selector governance, and multi-user synchronization onto the mixed reality software operations described herein. By structuring these modules into timing, traffic-management, policy and selector, and synchronization and observability groups, the system enables object removal and occlusion, viewpoint manipulation, virtual position movement, camera feed integration, and SLAM to execute within a policy-compliant adaptive logic layer. This arrangement permits biometric-adaptive content and feedback, per-user personalized content, per-user personalized characters, and location-based assets to be orchestrated in real time, with rendering engine 419 honoring the timing, priority, and policy decisions admitted by this control plane, thereby delivering a theater experience that adapts to individual users while maintaining collective narrative coherence.

[0135] Taken together, the interface and protocol layer of FIG. 4A governs the authenticated parameter sets that subsystems 402-405 follow' and supplies contracts that are admitted, enforced, and synchronized by the control and orchestration layer of FIG. 4B to govern timing,- 38 -107298845 1PATENTAttorney Docket No. 130586-866348 traffic, policy, selector application, and multi-user synchronization across the subsystems, thereby enabling the core mixed reality engine 401 to provide a coherent, low-latency multiuser mixed reality experience during execution of the pipeline operations of FIG. 5 and additional processing pipelines of FIGS. 11, 19, 27, and 34, as further described herein. Although described with reference to a theater environment, the disclosed control and orchestration layer applies broadly to any multi-user mixed reality environment, including but not limited to industrial training, classroom learning, remote collaboration, and consumer entertainment settings. Variations in hardware, deployment topology, sensor configuration, and device class remain within the scope of the present disclosure.

[0136] Having described an example of an interface and protocol layer and a control and orchestration layer of a core mixed reality engine 401 with reference to FIGS. 4A-4B, attention is now directed to FIG. 5, which illustrates an example of a mixed reality operations pipeline 500 in accordance with aspects of the present disclosure. As shown, the operations pipeline 500 may be implemented as a method (e.g., a process) executed by the core mixed reality engine, wherein discrete block may be performed to transform real-world inputs into synchronized mixed reality outputs. In particular, the pipeline 500 may include input capture block501, data fusion and spatial mapping block block502, core mixed reality processing block block503, adaptive logic layer block block504, and output distribution block block505. In operation, inputs from audience members, stage instrumentation, and environmental systems may be captured and fused, processed through core rendering and synchronization functions, adapted by higher-level logic, and distributed as synchronized outputs across devices and venue systems. In certain aspects, the pipeline is configured to maintain frame-aligned, motion-to- photon latency targeting less than about 20 ms end-to-end, while upstream video ingestion may operate under about 100 ms, preserving coherent multi-user synchronization across subsystems. The arrangement of FIG. 5 is presented in generalized form to demonstrate how functional modules described with reference to FIGS. 4A-4B may cooperate in sequence to execute mixed reality experiences in real time. Although described in the context of a theater environment, the operations pipeline of FIG. 5 may likewise be implemented in other live performance venues, enterprise deployments, educational contexts, or collaborative environments without departing from the scope of the present disclosure. Operations may be performed on an MR device, a local venue server, a cloud service, or any combination thereof. The order of blockthe operations is illustrative unless expressly stated.- 39 -107298845 1PATENTAttorney Docket No. 130586-866348

[0137] At block 501, multimodal inputs may be captured by acquiring data from a wide variety of sources, thereby providing the foundation for the mixed reality experience. Such data may include, without limitation, visual, depth, inertial, positional, audio, biometric, interaction, environmental, network, and system information. Data sources may include, without limitation, cameras, depth sensors, IMUs, positioning systems, microphones, biosensors, physiological sensors, user interfaces, venue systems, stage systems, network devices, control devices, and the like. In the representative MR theater environment, the acquired data may include user interactions such as gestures, voice commands, gaze interactions, biometric responses, or digital selections, as well as environmental data such as seat-embedded sensors, adaptive seating systems, environmental monitors, and stage-tracking instrumentation. The acquired data may further include audiovisual content such as live video from fixed or mobile cameras, performer-worn cameras, or motion-capture systems. This diverse data may be acquired continuously, in real time, near real time, or in buffered form, and provided to dow nstream blockoperations of the pipeline for further analysis, integration, or rendering. In certain implementations, block 501 may further include normalizing heterogeneous data into a common representation, such as a synchronized frame structure, thereby allowing information from different modalities to be meaningfully combined in later blocks.

[0138] At block 502, multimodal data may be fused and spatial mappings may be generated by combining heterogeneous inputs into a unified representation, thereby providing a coherent spatial model of the mixed physical and digital environment. In some aspects, semantic fusion algorithms may integrate the multimodal inputs captured in block 501, while SLAM processes may maintain an up-to-date global spatial map. Object-recognition modules may classify and register real-world elements to serve as anchors for digital overlays, with temporal alignment ensuring that heterogeneous data streams remain synchronized. In the representative MR theater environment, fusing and mapping may include combining audience biometric data, stage-tracking signals, and environmental sensor outputs into a coherent spatial context model. In some implementations, predictive mapping algorithms may forecast audience or performer movement to enable proactive rendering adjustments, while error-correction logic may reconcile discrepancies between redundant sensors such as LiDAR and optical tracking, thereby maintaining a consistent environment model under variable conditions.

[0139] At block 503, mixed reality content may be processed by executing core rendering, transformation, and synchronization operations, thereby regulating interactions between- 40 -107298845 1PATENTAttorney Docket No. 130586-866348 physical and digital elements within the mixed reality environment. Core operations may include, without limitation, combining captured real-world data with computer-generated elements, generating graphics and audio outputs, aligning digital content with the spatial model generated in block 502, performing object removal and occlusion operations of FIG. 7 to selectively control the visibility of objects, performing viewpoint manipulation operations of FIG. 8 to reposition or reorient user perspectives, performing virtual position movement operations of FIG. 9 to enable relocation within the MR environment independently of physical motion, and performing live camera-feed integration operations of FIG. 10 to merge dynamic video sources into rendered scenes. In the representative MR theater environment, core operations may additionally involve coordinating visual effects with performer motion, stage instrumentation, or audience interaction signals. The rendering pipeline may generate high- fidelity graphics and audio outputs synchronized with live performance cues. In certain implementations, block 503 may further include maintaining system performance by employing multi-user synchronization protocols to ensure that participants perceive coherent, temporally aligned content, and by applying dynamic resource allocation logic to balance GPU, CPU, and NPU workloads across rendering tasks, thereby sustaining performance under peak demand conditions.

[0140] At block 504, adaptive logic may be applied by analyzing audience, environmental, and contextual states and generating control directives, thereby dynamically tailoring the mixed reality experience in response to changing conditions. Adaptive logic may be applied by processing multimodal data, applying analytic and decision-making logic to audience, environmental, and contextual states, and generating control directives that govern how mixed reality content is adapted, managed, or orchestrated in real time. Multimodal data may include, without limitation, visual, depth, inertial, positional, audio, biometric, interaction, environmental, network, and system information, as well as performance, narrative, and telemetry data. Control directives may include, without limitation, modifications to any functional, operational, experiential, or contextual aspect of the mixed reality’ system or the mixed reality environment. In some aspects, block 504 may further include interfacing with higher-level adaptive content pipelines such as a biometric-adaptive content pipeline with reference to FIG. 11, a personalized mixed reality content pipeline with reference to FIG. 19, a personalized character pipeline with reference to FIG. 27, and a location-based content pipeline with reference to FIG. 34, as further described herein. In the representative MR theater- 41 -107298845 1PATENTAttorney Docket No. 130586-866348 environment, adaptive logic may incorporate feedback loops that adjust pacing or emphasis based on audience responses, clustering of audience interactions into subgroups whose collective inputs influence narrative progression or synchronized effects, or scoring logic that evaluates engagement and scene effectiveness based on audience data. In certain implementations, machine learning models may be trained on prior interactions to enable predictive personalization and context-aware branching, while conflict-resolution algorithms may reconcile divergent subgroup inputs using thresholds, weighted scoring, tie-break rules, deterministic rules, or overrides to ensure coherent progression.

[0141] At block 505, outputs may be distributed by delivering synchronized mixed reality content across devices and systems associated with the mixed reality environment, thereby providing coherent immersive experiences to participants and venues. Output distribution may include, without limitation, transmitting or rendering mixed reality content through HMDs, personal devices, stage systems, lighting systems, projection systems, holographic systems, venue systems, or environmental systems. Distributed outputs may include, without limitation, visual data, audio data, haptic effects, environmental modulation, control signals, network communications, or other forms of content or system instructions suitable for rendering, synchronization, or coordination. In some aspects, quality-of-service (QoS) logic may be applied to adapt output fidelity, resolution, frame rate, or latency to accommodate heterogeneous devices and network conditions, thereby maintaining coherent synchronization and continuity. In the representative MR theater environment, outputs may be delivered to audience HMDs, to stage-level systems such as projection surfaces, lighting arrays, or holographic rigs, and to venue-level systems such as spatial audio speaker arrays, haptic feedback systems, or atmospheric modulation systems.

[0142] While the aspect of FIG. 5 is described in the context of a representative mixed reality operations pipeline, it will be understood that the illustrated arrangement is not limiting. The block shown — including input capture block 501, data fusion and spatial mapping block 502, core mixed reality processing block 503. adaptive logic block 504, and output distribution block 505 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the pipeline may further maintain coherence by collecting telemetry, updating spatial and semantic states as conditions evolve, and re-invoking block 501-505 in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular- 42 -107298845 1PATENTAttorney Docket No. 130586-866348 sequencing of functions depicted in FIG. 5, but also variations that achieve comparable orchestration of mixed reality content in different physical, digital, or hybrid environments. Unless stated otherwise, the methods of FIGS. 5-10 can be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0143] Having described an example of a mixed reality operations pipeline with reference to FIG. 5, attention is now directed to FIG. 6, which illustrates an example of a simultaneous localization and mapping (SLAM) method 600 in accordance with aspects of the present disclosure. In some aspects, the SLAM method 600 may provide inputs to, and operate in coordination with, the data fusion and spatial mapping block 502 of FIG. 5. At a high level, the method may include acquiring multimodal sensor data, aggregating and synchronizing heterogeneous inputs, detecting features and landmarks, estimating device poses, constructing and updating a global three-dimensional spatial map, semantically annotating features, and distributing synchronized map data to devices and systems. The blocks are presented in generalized form to demonstrate how inputs from MR devices and environmental sensors may be processed to generate and maintain a coherent global spatial model that anchors mixed reality content to the real-world environment. While described in the context of a representative MR theater environment, the method of FIG. 6 may likewise be implemented in personal, enterprise, educational, or other performance or collaborative contexts, without departing from the scope of the present disclosure.

[0144] At block 601, multimodal sensor data may be acquired by capturing input from diverse sensing modalities, thereby providing raw observations of the physical environment for spatial mapping. Such data may include, without limitation, visual, depth, inertial, positional, audio, environmental, or other contextual information. Signal sources may include, without limitation, cameras, depth sensors, IMUs providing accelerometer, gyroscope, or magnetometer data, positioning systems, microphones, environmental sensors, or other venue- deployed or user-worn devices. In the representative MR theater environment, sensor acquisition may involve capturing image frames from RGB cameras, depth maps from LiDAR systems, and motion data from performer-mounted IMUs, along with venue-level sensor inputs such as lighting conditions, temperature, atmospheric variation, or audience-area sensors. Acquired data may be collected continuously, in real time, near real time, or buffered for synchronization, and provided downstream for subsequent aggregation, synchronization, calibration, and spatial mapping.- 43 -107298845 1PATENTAttorney Docket No. 130586-866348

[0145] At block 602, multimodal sensor data may be aggregated and synchronized by aligning heterogeneous inputs into a unified spatiotemporal framework, thereby preparing consistent data for subsequent mapping operations. Aggregation and synchronization may include, without limitation, normalizing data formats, applying time-stamping or interpolation logic, compensating for latency differences, and reconciling frame-rate mismatches or sensor jitter. In the representative MR theater environment, block block602 may include aligning video frames from multiple cameras, depth maps from LiDAR or structured light systems, and inertial readings from IMUs to a common timeline and reference frame. In some aspects, interpolation processes may align IMU samples to image timestamps or depth frames to camera exposure times, while fusion algorithms may combine redundant or overlapping data sources, such as reconciling LiDAR depth with stereo vision, to improve accuracy and robustness. Buffering and fusion processes may be applied to produce a standardized multimodal data stream that maintains temporal and spatial consistency across all inputs.

[0146] At block 603, features and landmarks may be detected by identifying salient points or patterns within the aggregated multimodal data, thereby enabling downstream pose estimation and spatial mapping. Detected features may include, without limitation, edges, comers, fiducials, structural boundaries, or other stable reference points in the environment. In the representative MR theater environment, landmarks may include seating rows, stage boundaries, comers of stage elements, or static props that provide consistent anchors for spatial alignment. Feature detection may be performed through computer vision techniques, depth analysis, or other recognition algorithms, and may be applied across successive frames to establish correspondences useful for motion and stmcture estimation. In some aspects, feature detection may employ feature description or tracking algorithms such as Oriented FAST and Rotated BRIEF (ORB), Scale-Invariant Feature Transform (SIFT), or optical-flow-based methods such as Lucas-Kanade. and other suitable techniques.

[0147] At block 604, poses may be estimated by fusing detected features with inertial and positional data, thereby determining the relative position and orientation of mixed reality devices or sensors with respect to the mapped environment. Pose estimation may include, without limitation, calculating translation, rotation, or trajectory parameters in six degrees of freedom (6DoF) and refining them through optimization techniques that minimize error between predicted and observed feature locations. In the representative MR theater environment, pose estimation may enable an audience member’s HMD to maintain alignment- 44 -107298845 1PATENTAttorney Docket No. 130586-866348 with stage and seating geometry, or may allow performer tracking systems to register motion within the shared spatial map. In some aspects, pose estimation may employ filtering or optimization methods such as extended Kalman filters, bundle adjustment, or other suitable smoothing or predictive logic to stabilize motion and reduce jitter under real-time conditions, thereby supporting accurate registration of digital content with the physical environment.

[0148] At block 605, three-dimensional structures may be constructed by triangulating detected features and combining them into spatial representations, thereby generating or updating a map of the physical environment. Spatial representations may include, without limitation, point clouds, voxel grids, polygonal meshes, or other geometric models. In the representative MR theater environment, map construction may capture static structures such as walls, stage elements, and seating, as well as dynamic elements such as movable props or performers. The spatial map may be updated incrementally as new features are observed, expanding coverage to newly sensed areas and refining existing regions to improve accuracy, or optimized globally to improve overall consistency, and may be maintained persistently across sessions to provide a stable foundation for content anchoring. Spatial representations may be stored or transmitted in standard formats such as PLY, OBJ, or glTF, or encoded using hierarchical data structures such as octrees or surfel-based models to balance fidelity with efficiency.

[0149] At block 606, environmental changes may be detected and the spatial map may be updated by comparing new observations with previously constructed models, thereby maintaining accuracy and responsiveness under dynamic conditions. Change detection may include, without limitation, identifying additions, removals, movements, or transformations of real -world objects or regions within the mapped environment. Change detection techniques may include, without limitation, iterative closest point (ICP) alignment, frame differencing, probabilistic occupancy filtering, or other scene analysis methods operable to identify and reconcile deviations in spatial structure. Updating may involve expanding the map to incorporate newly observed regions, refining existing map structures to improve fidelity, or both, and may be performed incrementally or through global optimization. In some aspects, only affected regions may be selectively refreshed to conserve computational resources while preserving continuity7of the mixed reality7experience. In the representative MR theater environment, changes may include prop movements, stage set adjustments, performer- 45 -107298845 1PATENTAttorney Docket No. 130586-866348 repositioning, or audience entry and exit, each of which may trigger corresponding updates to the spatial map.

[0150] At block 607. semantic context may be integrated by annotating mapped features with semantic labels, thereby enriching the spatial model with higher-level meaning. Such semantic labels may include, without limitation, zone identifiers, object classifications, surface classifications, or anchor designations applied to selected objects or surfaces for digital overlays. In the representative MR theater environment, semantic context integration may include labeling seating rows as audience zones, classifying stage areas as active performance regions, or registering props as interactive or occludable objects. In some aspects, semantic labels may be assigned using trained classifiers or rule-based systems, which can improve the adaptability of downstream operations such as removal and occlusion, interactive element alignment, adaptive content placement, or narrative-driven scene management. Classifier implementations may include, without limitation, convolutional neural networks (CNNs) for image-based segmentation, recurrent or transformer-based models for temporal labeling, or graph-based approaches for context-aware annotation. While the SLAM process may operate without semantic context integration, the inclusion of block 607 may improve the accuracy, richness, and adaptability of mixed reality experiences.

[0151] At block 608, spatial map data may be distributed and synchronized by propagating updated models, semantic annotations, and pose information across devices and systems, thereby ensuring that participants and subsystems maintain a coherent and consistent understanding of the environment. The operations of block 608 may be performed via low- latency networking and may include, without limitation, broadcasting global maps, distributing incremental updates, synchronizing semantic layers, and transmitting pose and trajectory information across local networks, cloud infrastructures, or hybrid distribution channels, such that all devices and servers operate on a shared global spatial map. In some aspects, synchronization may extend across both local and remote environments to preserve continuity in collaborative or distributed sessions. Distribution may occur through venue networking (e.g., sub-frame synchronization over UDP multicast), cloud-based services (e.g., WebRTC data channels, QUIC over UDP), or hybrid arrangements, each configured to maintain low-latency transmission. In the representative MR theater environment, synchronized map data may be delivered to performer tracking systems, projection and lighting arrays, audience HMDs, venue-level control networks, and production servers, thereby ensuring a coherent registration- 46 -107298845 1PATENTAttorney Docket No. 130586-866348 and alignment of virtual and physical elements throughout the MR theater environment simultaneously for each audience member. In some implementations, distribution protocols may enforce sub-frame latency and reliability guarantees while further applying quality-of- service policies, adaptive compression techniques, or differential update protocols to balance fidelity, latency, and bandwidth usage across heterogeneous devices and network conditions.

[0152] While the aspect of FIG. 6 is described in the context of a representative SLAM method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including multimodal sensor acquisition block 601, data aggregation and synchronization block 602, feature detection and landmark extraction block 603, pose estimation block 604, 3D structure triangulation and map construction block 605, environmental change detection and map update block 606, semantic integration block 607, and distribution and synchronization block 608 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In certain aspects, portions of the SLAM process may be pre-computed for static venue features, executed locally on individual devices, or offloaded to cloud services, thereby allowing flexible distribution of spatial mapping workloads depending on deployment constraints. In continued operation, the method may further maintain coherence by collecting telemetry, updating spatial and semantic states as conditions evolve, and re-invoking blocks block601-608 in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 6, but also variations that achieve comparable generation, maintenance, and distribution of spatial models in different physical, digital, or hybrid environments, while ensuring that virtual and physical elements remain coherently aligned across participants and devices in real time. Unless stated otherwise, the methods of FIG. 6 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0153] Having described an example of a SLAM and spatial mapping method with reference to FIG. 6, attention is now directed to FIG. 7, which illustrates an example method 700 for object removal and occlusion in accordance with aspects of the present disclosure. As shown, the method 700 may include discrete blocks for acquiring scene data, reconstructing three- dimensional environments, detecting and segmenting objects, fusing spatial and semantic features, and applying decision logic to determine whether objects should be removed or occluded. Downstream blocks may perform removal processing or occlusion handling.- 47 -107298845 1PATENTAttorney Docket No. 130586-866348 followed by rendering, output integration, and distribution of synchronized outputs to devices and systems. The method may further incorporate continuous environmental monitoring to detect changes and loop back for real-time updating. The arrangement of FIG. 7 is presented in generalized form to demonstrate how object visibility may be dynamically controlled to maintain visual coherence and to selectively hide, mask, or substitute real- world objects with digital content for adaptive mixed reality experiences. Although described in the context of a representative MR theater environment, the method of FIG. 7 may likewise be implemented in enterprise, educational, personal, or collaborative contexts without departing from the scope of the present disclosure.

[0154] At block 701, scene data may be acquired by capturing multimodal observations of the physical environment, thereby establishing raw inputs for subsequent reconstruction. The operations of block 701 may include, without limitation, acquiring RGB frames, depth maps, LiDAR point clouds, inertial readings, stage-tracking feeds such as motion capture outputs, audience-facing video feeds for contextual awareness, or environmental signals from fixed and mobile sensors, and in certain implementations may further include acquiring synchronized color-depth frames from RGB-D cameras or depth disparity maps from stereo imaging systems. In some aspects, the operations of block 701 may further include synchronizing data streams to system timing references, thereby enabling consistent downstream processing. In the representative MR theater environment, block 701 may include collecting live video from cameras oriented toward the stage, depth scans of performers and props, and audience-area signals from seat sensors or environmental arrays. The data acquired in block 701 may provide the foundation for spatially accurate object detection and subsequent environment reconstruction.

[0155] At block 702, three-dimensional projection and environment reconstruction may be performed by projecting captured data into volumetric representations and updating environment models in real time. The operations of block 702 may include, without limitation, processing raw sensor inputs into point clouds, voxel grids, or polygonal meshes representing the physical scene. In the representative MR theater environment, reconstruction may capture the stage boundary, audience seating, actor positions, and prop geometries in real time, thereby providing the geometric context necessary' for subsequent object detection and occlusion handling operations and a foundation for aligning digital overlays. In some aspects, block 702 may employ GPU-accelerated reconstruction pipelines, truncated signed distance functions- 48 -107298845 1PATENTAttorney Docket No. 130586-866348(TSDF), or surfel-based integration techniques to maintain low-latency volumetric updates suitable for interactive use.

[0156] At block 703. objects may be detected and segmented within reconstructed environments, thereby identifying candidate elements for removal or occlusion. The operations of block 703 may include, without limitation, applying computer vision or machine learning algorithms to classify7pixels, voxels, or regions according to object boundaries and to generate segmentation masks aligned with the reconstructed geometry from block 702. thereby yielding a consistent representation of object boundaries. In the representative MR theater environment, block 703 may segment performers, physical props, set pieces, audience members, or environmental fixtures, such that digital elements can be layered appropriately. In some aspects, segmentation may employ convolutional neural networks (CNNs), transformer-based vision models, optical-flow analysis, or models such as Mask R-CNN or DeepLab, optionally supplemented with fiducial markers or depth discontinuities to improve accuracy.

[0157] At block 704. spatial-semantic fusion and classification may be performed by integrating segmentation outputs from block 703 with the reconstructed geometry from block 702, thereby generating a unified spatial-semantic scene model. The operations of block 704 may include, without limitation, assigning semantic labels to surfaces or volumes (e.g., “seat row,” “stage boundary,” “movable prop”) and classifying objects as removable, occludable, interactive, or anchor elements based on rule sets, machine learning classifiers, or production scripts. In the representative MR theater environment, block 704 may classify a stage prop as removable, a performer as occludable, and an audience member as a background element, while also designating certain props as digital anchors, thereby enabling differential visibility control. In some aspects, probabilistic fusion algorithms, graph-based classifiers, or scene graph encodings may be employed to merge geometric and semantic data, and this contextualization may further enable downstream rendering decisions that preserve narrative coherence.

[0158] At block 705, objects may be evaluated for removal or occlusion by decision logic operating on the spatial-semantic scene model generated in block 704, thereby determining whether each object should undergo removal processing or occlusion handling. Decision criteria may include, without limitation, object type, semantic label, narrative context, performance cues, production logic, audience interaction signals, or adaptive directives. In the representative MR theater environment, block 705 may determine whether a holographic- 49 -107298845 1PATENTAttorney Docket No. 130586-866348 character should be occluded behind a physical curtain (occlusion handling), whether a physical stage prop or background element should be digitally erased to clear stage visibility or enable a virtual overlay (removal processing), or whether an actor may be temporarily occluded to allow a digital character substitution. In some aspects, decision logic may operate dynamically in response to evolving performance conditions and may be governed by adaptive policies referencing timing constraints, user consent settings, or director overrides.

[0159] At block 706a, object removal processing may be performed by selectively excluding identified objects from rendered outputs, thereby reconstructing scene continuity in regions where objects were previously detected. The operations of block 706a may include, without limitation, background inpainting, depth inpainting, texture synthesis, geometry-based substitution, or replacement with interpolated scene geometry. In the representative MR theater environment, block 706a may digitally erase a prop from the stage while reconstructing the background to maintain a coherent scene, thereby making space for a holographic substitute. In some aspects, block 706a may further employ learned image-completion techniques, neural rendering models, deep generative models, texture libraries, real-time depth-aware hole filling, or depth re-projection techniques to preserve visual continuity.

[0160] At block 706b, occlusion handling may be performed by ensuring that digital overlays respect the depth ordering and visibility of real-world elements. The operations of block 706b may include, without limitation, applying z-buffer or depth-buffer masking techniques, depth- aware compositing, stencil buffering, layered compositing, or occlusion masks derived from segmentation outputs. In the representative MR theater environment, block 706b may ensure that a holographic dragon appears behind a physical curtain or performer when appropriate, thereby preserving natural layering cues, realism, and immersion. In some aspects, occlusion may further be enhanced using multi-view consistency checks, predictive occlusion estimation, per-pixel depth blending, or multi-camera viewpoints to anticipate visibility changes and reduce artifacts during motion. In certain implementations, occlusion masks may be pregenerated for static props or stage structures, while dynamic occlusion may be computed in real time, permitting hybrid approaches that balance computational load with responsiveness. In some implementations, removal block 706a and occlusion block 706b may further be combined or interleaved within a single frame to accommodate mixed real-and-virtual staging.

[0161] At block 707, scene rendering and output integration may be performed by compositing processed imagery that incorporates the removal and occlusion results generated- 50 -107298845 1PATENTAttorney Docket No. 130586-866348 in blocks 706a and 706b. and generating rendered video frames for output distribution to downstream devices and systems. The operations of block 707 may include, without limitation, producing composite frames that integrate real-world imagery with computer-generated overlays, updating projection surfaces, or transmitting composite image frames to display endpoints. In the representative MR theater environment, block 707 may produce composite image frames showing actors, stage elements, and digital overlays with appropriate removals and occlusions, and distribute these outputs to HMDs, handheld devices, projection systems, or venue displays. In some aspects, block 707 may further incorporate quality-of-service logic to adjust resolution, frame rate, or latency depending on device class and network conditions, and may coordinate outputs with the global spatial map of FIG. 6 and adaptive logic of FIG.5.

[0162] At block 708, environmental changes may be detected and the method 700 may loop back to block 701, thereby maintaining real-time responsiveness and accuracy in dynamic conditions. The operations of block 708 may include, without limitation, monitoring for object additions, removals, movements, or environmental variations, with updates applied to the spatial-semantic scene model. In the representative MR theater environment, block 708 may detect changes such as actor repositioning, audience entry or exit, stage prop manipulation, or lighting variations, and may trigger re-segmentation and reclassification to ensure accurate removal or occlusion handling. In some aspects, block 708 may employ continuous monitoring pipelines, incremental map updates, change-detection algorithms, or suitable refresh rates to preserve coherence across iterations of the loop.

[0163] While the aspect of FIG. 7 is described in the context of a representative method for object removal and occlusion, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including scene data acquisition block 701, three-dimensional projection and environment reconstruction block 702, object detection and segmentation block 703, spatial-semantic fusion and classification block 704, decision logic block 705. object removal processing block 706a. occlusion handling block 706b. scene rendering and output integration block 707, and environmental change detection and loopback block 708 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by updating scene representations, refining classifications, and re-invoking blocks 701-708 as environmental conditions evolve. Accordingly, the disclosure encompasses- 51 -107298845 1PATENTAttorney Docket No. 130586-866348 not only the particular sequencing of functions depicted in FIG. 7 , but also variations that achieve comparable visibility management and removal / occlusion functionality in different physical, digital, or hybrid environments. Unless stated otherwise, the methods of FIG. 7 may be implemented by one or more processors executing instructions stored on non-lransitory computer-readable media.

[0164] Having described the object removal and occlusion operations of FIG. 7, attention is now directed to FIG. 8, which illustrates an example of a viewpoint-manipulation method 800 in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks 801-808 for initializing, acquiring, transforming, adjusting, validating, and synchronizing viewpoint data to produce a real-time, collision-safe virtual camera pose. The arrangement of FIG. 8 is presented in generalized form to demonstrate how dynamic viewpoint control may be achieved within mixed reality (MR) environments while maintaining spatial alignment with physical and digital elements. Although described in the context of a representative MR theater environment, method 800 may likewise be implemented in enterprise, educational, collaborative, or personal MR applications without departing from the scope of the present disclosure.

[0165] At block 801, a baseline viewpoint may be initialized by establishing an origin pose for the user's virtual camera relative to the MR coordinate frame, thereby defining the default field of view and reference orientation for subsequent transformations. The operations of block 801 may include, without limitation, referencing calibration data, user-profile presets, or system-level defaults to determine a neutral pose that aligns with physical seating or audience placement. In the representative MR theater environment, block 801 may initialize each audience member’s viewpoint to correspond with their assigned seat position and nominal head height, ensuring that all virtual overlays appear co-registered with the live stage. In some aspects, the baseline viewpoint may be fused with a global spatial map generated according to the method of FIG. 6, thereby ensuring that the initialization aligns both the digital coordinate frame and the physical venue geometry. In some aspects, block 801 may employ spatial- mapping routines or homography alignment to reconcile real-world and virtual coordinate systems with sub-centimeter accuracy.

[0166] At block 802, orientation data may be acquired by polling head-mounted sensors or external tracking devices, thereby obtaining the instantaneous quaternion or Euler-angle representation of the user’s head pose. The operations of block 802 may include, without- 52 -107298845 1PATENTAttorney Docket No. 130586-866348 limitation, collecting data from IMUs, optical markers, or SLAM estimates at sample rates exceeding 100 Hz. In certain implementations, depth-sensing cameras may also be employed to enhance pose estimation accuracy under low-texture or occluded conditions. In the representative MR theater environment, block 802 may capture each viewer’s subtle head tilts as they follow a performer across the stage, enabling natural parallax and depth perception. In some aspects, block 802 may implement a sensor-fusion filter, such as a complementary’ or extended-Kalman filter, to minimize drift and latency between IMU and optical data streams.

[0167] At block 803, the orientation data may be transformed by applying head-tracking transformations, thereby mapping user movement into the virtual scene through computation of a scene-relative camera matrix. The operations of block 803 may include, without limitation, coordinate-frame conversion, smoothing, interpolation, and pose prediction for low-latency rendering. In the MR theater environment, block 803 may translate a viewer's lateral head movement into a corresponding shift of the virtual viewpoint, revealing occluded stage elements. In some aspects, block 803 may employ predictive tracking using autoregressive filters or recurrent neural models to compensate for motion-to-photon delays below’ 20 milliseconds. Alternative implementations may utilize complementary filtering in conjunction with Kalman-based prediction to further smooth rapid head movements.

[0168] At block 804, user-initiated viewpoint adjustments may be processed by interpreting input signals, thereby modifying the desired camera framing based on gesture, gaze, or controller interaction. The operations of block 804 may include, without limitation, parsing multimodal input streams, filtering noise, and mapping control signals to translation or rotation deltas. In the representative MR theater environment, block 804 may enable a viewer to gesture to zoom in on a performer or tilt upward to follow a flying prop, with such inputs captured and normalized in real time. In some aspects, voice commands may additionally be supported as a hands-free modality for triggering viewpoint adjustments. In some aspects, block 804 may include temporal smoothing or adaptive gain control to ensure stable, intuitive response curves across heterogeneous input devices.

[0169] At block 805, user-adjustment inputs may be transformed by applying offset matrices, thereby generating updated orientation and position vectors for rendering. The operations of block 805 may include, without limitation, computing transformation matrices, weighting user input against system constraints, and blending orientation deltas. In the MR theater environment, a gentle tilt of the head combined with a controller twist may yield a smooth pan-- 53 -107298845 1PATENTAttorney Docket No. 130586-866348 and-zoom effect toward the stage’s focal point. In some aspects, block 805 may implement quaternion slerp interpolation and clamped translation scaling to prevent cumulative rotational error.

[0170] At block 806, the transformed viewpoint may be validated by performing collision and boundary safety checks, thereby ensuring that the camera remains within allowable spatial limits and does not penetrate virtual or physical geometry. The operations of block 806 may include, without limitation, bounding-volume intersection tests, floor-plane validation, and occlusion-mask integrity checks. In the MR theater environment, block 806 may prevent a virtual camera from moving backstage or below the stage floor, maintaining narrative coherence. By way of example, viewpoint adjustments may be constrained within a configurable spatial envelope, such as within a radius of approximately five meters from an assigned seating location, while preserving narrative boundaries and audience immersion. In some aspects, block 806 may employ hierarchical bounding-box collision detection and adaptive safety-region expansion based on user-proximity data.

[0171] At block 807, the validated pose data may be applied by updating the virtual camera’s position and orientation, thereby committing the viewpoint transformation for the next render cycle. The operations of block 807 may include, without limitation, refreshing the camera transform buffer, broadcasting pose updates to dependent rendering modules, and triggering event callbacks. In the MR theater environment, block 807 may synchronize each audience member’s adjusted viewpoint to shared stage coordinates, ensuring visual alignment during collaborative scenes. In some aspects, block 807 may utilize double-buffered camera matrices or atomic swap operations to maintain frame coherence under parallel rendering conditions.

[0172] At block 808, updated visual frames may be generated by executing rendering and synchronization operations, thereby maintaining low-latency correspondence between physical motion and virtual imagery. The operations of block 808 may include, without limitation, GPU pipeline submission, frame-rate regulation, frame-timing adjustment, and cross-device synchronization. In the MR theater environment, block 808 may ensure that when multiple viewers shift viewpoints simultaneously, all stage projections remain time-aligned with the live performance. Rendered outputs may be distributed across heterogeneous display devices, including HMDs, augmented-reality glasses, handheld spectator screens, and projection systems visible to performers and audiences. In some aspects, adaptive quality-of-service (QoS) controls may dynamically balance rendering fidelity with available device or network- 54 -107298845 1PATENTAttorney Docket No. 130586-866348 bandwidth, maintaining consistent synchronization at refresh rates of about 90 Hz or higher. In some aspects, block 808 may employ asynchronous time-warp or late-latching techniques to correct final image orientation immediately before display refresh.

[0173] While the aspect of FIG. 8 is descnbed in the context of a representative viewpointmanipulation method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 801-808 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, method 800 may maintain coherence by collecting telemetry, updating pose states as conditions evolve, and re-invoking blocks 802-808 in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 8, but also variations that achieve comparable viewpoint control in different physical, digital, or hybrid environments. Unless stated otherwise, the methods of FIG. 8 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0174] Having described the viewpoint manipulation operations of FIG. 8, attention is now directed to FIG. 9, which illustrates an example of a virtual position movement method 900 in accordance with aspects of the present disclosure. As show n, the method may include discrete blocks 901-909 for capturing environmental data, maintaining spatial awareness, acquiring user navigation input, processing navigation requests, enforcing safety and boundary constraints, applying virtual transformations, adjusting collision and occlusion conditions, synchronizing multi-user viewpoints, and rendering final outputs for distribution to MR devices. The arrangement of FIG. 9 is presented in generalized form to demonstrate how user- driven navigation through mixed reality environments may be achieved while maintaining spatial coherence, safety, and synchronization across distributed participants, such that users may relocate within a mixed reality environment independently of their physical movement. Although described in the context of a representative MR theater environment, method 900 may likewise be implemented in enterprise, educational, or collaborative experiences where spatial repositioning of viewpoints is performed under real-time constraints.

[0175] At block 901, environmental data may be captured by acquiring sensor inputs from the mixed reality scene, thereby generating an updated spatial model of the performance environment. The operations of block 901 may include, without limitation, collecting depth maps, spatial meshes, lighting information, and actor telemetry data from stage-mounted or- 55 -107298845 1PATENTAttorney Docket No. 130586-866348 headset-mounted sensors. In the representative MR theater environment, block 901 may involve volumetric scanning of the stage, props, and audience seating areas to maintain up-to- date environmental awareness. Additional environmental inputs may include seating maps, stage geometry, and ambient conditions such as lighting or sound-field data, thereby providing a richer dataset for maintaining accurate spatial awareness. In some aspects, block 901 may employ depth cameras, structured-light scanners, or LiDAR units operating in tandem with photometric-correction algorithms to produce metrically consistent reconstructions suitable for collision detection and navigation planning.

[0176] At block 902, spatial awareness may be maintained by continuously updating the environmental model, thereby ensuring that virtual and physical coordinate frames remain aligned during user navigation. In some aspects, the maintained spatial model may be integrated with a global SLAM map generated according to the method of FIG. 6, thereby ensuring continuity of coordinate registration across all navigation operations. The operations of block 902 may include, without limitation, performing incremental SLAM updates, applying spatial anchoring, and fusing data from multiple users’ devices to preserve shared spatial context. In the MR theater environment, block 902 may maintain awareness of moving stage elements, lighting changes, and performer positions so that navigation remains coherent with live action. In some aspects, block 902 may incorporate dynamic mesh updates or voxel-based occupancy tracking to sustain low-latency awareness of evolving spatial geometry.

[0177] At block 903, user navigation input may be captured by detecting one or more control actions corresponding to a desired change in position within the MR scene, thereby initiating a navigation event. Navigation directives may include, without limitation, instantaneous teleportation to new virtual positions, continuous walking trajectories, viewpoint scaling, or rotational reorientation consistent with user intent. The operations of block 903 may include, without limitation, interpreting gestures, controller movements, eye-gaze trajectories, or joystick-displacement vectors. In the representative MR theater environment, a viewer may gesture toward a distant part of the stage or select a teleportation marker to reposition their virtual vantage point. In some aspects, block 903 may include adaptive input filtering and confirmation prompts to prevent unintentional viewpoint jumps caused by transient gestures or misrecognized movements.

[0178] At block 904, the navigation request may be processed by interpreting the captured input within the context of the current spatial model, thereby determining a valid navigation- 56 -107298845 1PATENTAttorney Docket No. 130586-866348 target and trajectory. The operations of block 904 may include, without limitation, mapping requested movements into the MR coordinate frame, checking scene topology, and computing a feasible motion path that preserves user orientation and continuity. In the MR theater environment, block 904 may determine whether a user’s requested movement is along the seating plane or involves elevation changes to access balcony perspectives. In some aspects, block 904 may include predictive navigation assistance in which the system recommends or automatically executes viewpoint transitions consistent with narrative pacing, actor blocking, or audience flow patterns. In some aspects, block 904 may further distinguish between individual-user navigation and subgroup-based directives, thereby allowing coordinated movement among selected participants within multi-user sessions.

[0179] At block 905, safety and boundary constraints may be evaluated by assessing the computed navigation path against predefined spatial limits, thereby preventing collisions or unsafe movements. The operations of block 905 may include, without limitation, verifying user paths relative to stage geometry, audience zones, and restricted backstage areas. In the MR theater environment, block 905 may ensure that a user navigating virtually through the stage area cannot intersect physical props or enter performer-only regions. In some aspects, block 905 may employ real-time collision prediction using swept-volume analysis or constraintsatisfaction solvers to maintain safe trajectories even under concurrent multi-user navigation.

[0180] At block 906, virtual transformations may be applied by updating the user’s virtual pose to reflect the approved navigation movement, thereby translating the user viewpoint within the MR coordinate frame. In some aspects, virtual position updates may be applied as instantaneous teleportation events or interpolated walking simulations, with motion-smoothing functions ensuring visual stability. The operations of block 906 may include, without limitation, generating transformation matrices, computing interpolated waypoints, and reorienting the user’s virtual camera relative to the scene’s anchor points. In the MR theater environment, block 906 may cause the viewer’s virtual position to glide from one seating zone to another, simulating continuous motion while maintaining focus on the performance stage. In some aspects, block 906 may include path-smoothing algorithms or motion-easing curves to minimize user disorientation during rapid repositioning events.

[0181] At block 907, collision and occlusion adjustments may be performed by recalibrating rendering parameters based on the updated viewpoint, thereby ensuring that visual elements correctly reflect new spatial relationships. In some aspects, block 907 may interface with the- 57 -107298845 1PATENTAttorney Docket No. 130586-866348 object-removal and occlusion method of FIG. 7, ensuring that repositioned viewpoints respect dynamic occlusion masks and maintain physical realism. The operations of block 907 may include, without limitation, performing occlusion culling, reprojecting depth buffers, and updating visibility masks to maintain consistent visual layering between physical and digital components. In the MR theater environment, block 907 may dynamically hide backstage scenery when the user moves into areas that would otherwise expose production artifacts. In some aspects, block 907 may employ hierarchical Z-buffer management and dynamic occlusion meshes to sustain real-time visual fidelity at frame rates exceeding 90 Hz.

[0182] At block 908, multi-user synchronization may be executed by aligning the spatial states of all participating users, thereby ensuring consistent shared experiences across networked MR sessions. Subgroup-specific synchronization may also be supported, enabling subsets of users to navigate cooperatively or observe alternate perspectives while maintaining overall narrative and timing alignment. The operations of block 908 may include, without limitation, transmitting updated position and orientation data, synchronizing scene anchors, and resolving discrepancies among distributed clients. In the MR theater environment, block 908 may ensure that multiple audience members viewing the same scene perceive identical performer positions and lighting conditions despite individual navigation adjustments. In some aspects, block 908 may employ network-time protocols, state-reconciliation buffers, or consensus-based synchronization schemes to maintain alignment within latency budgets below 50 milliseconds.

[0183] At block 909, rendering and output distribution may be performed by generating final composited frames based on synchronized user states, thereby delivering real-time mixed reality visuals to all connected devices. The operations of block 909 may include, without limitation, GPU-pipeline rendering, tone mapping, compression, and adaptive quality scaling for heterogeneous displays. In the MR theater environment, block 909 may provide synchronized outputs to HMDs, augmented-reality glasses, handheld screens, or venue-scale projection systems visible to both performers and spectators. In some aspects, adaptive quality - of-service controls may dynamically adjust resolution, frame rate, or encoding parameters under varying bandwidth conditions, maintaining continuity across heterogeneous MR devices. In some aspects, block 909 may employ distributed rendering architectures or cloud-assisted encoding pipelines to ensure consistent frame delivery’ across high-density multi-user deployments operating at refresh rates of about 90 Hz or greater.- 58 -107298845 1PATENTAttorney Docket No. 130586-866348

[0184] While the aspect of FIG. 9 is described in the context of a representative virtual position-movement pipeline, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 901-909 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In certain aspects, navigation may be realized through instantaneous teleportation, interpolated walking simulations, or Al-assisted pathfinding routines, providing flexible and context-aware repositioning capabilities across mixed reality venues. In continued operation, method 900 may maintain coherence by updating environmental data, refreshing spatial maps, and re-invoking blocks 902-909 in accordance with temporal and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 9, but also variations that achieve comparable navigation, safety, and synchronization performance in physical, digital, or hybrid MR environments. Unless stated otherwise, the methods of FIG. 9 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0185] Having described the virtual position movement operations of FIG. 9, attention is now directed to FIG. 10, which illustrates an example of a live camera feed integration method 1000 in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks 1001-1010 for acquiring live camera feeds, compressing and encoding video streams, synchronizing temporal frames, interpreting projection geometry, performing spatial registration and surface mapping, executing visual blending and segmentation, conducting live content analysis and feature detection, fusing depth and feature information, controlling synchronization latency, and rendering output frames for distribution to MR devices. The arrangement of FIG. 10 is presented in generalized form to demonstrate how live real-world imagery may be incorporated into mixed reality scenes in real time while maintaining geometric, photometric, and temporal consistency. This process enhances immersion, audience engagement, and performance interactivity by dynamically merging real-world imagery into mixed reality experiences. Although described in the context of a representative MR theater environment, method 1000 may likewise be implemented in enterprise telepresence, broadcast production, or collaborative visualization systems without departing from the scope of the present disclosure.

[0186] At block 1001, live camera feeds may be acquired by capturing optical data from one or more imaging devices positioned within or around the performance venue, thereby- 59 -107298845 1PATENTAttorney Docket No. 130586-866348 generating raw image frames for integration into the MR scene. The operations of block 1001 may include, without limitation, obtaining color and depth imagery, capturing multi-angle viewpoints, and recording intrinsic and extrinsic calibration parameters. In the representative MR theater environment, block 1001 may involve capturing multiple stage-mounted or ceilingmounted camera feeds showing performers, props, and audience regions to enable real-time video compositing. Additional sources may include mobile cameras operated backstage, performer-worn devices, or handheld audience cameras configured for perspective capture. In some aspects, block 1001 may employ synchronized RGB-D cameras or stereoscopic capture arrays operating at frame rates of about 60-120 Hz, each equipped with timing markers or genlock signals to facilitate downstream synchronization. In certain implementations, video streams may be captured at resolutions ranging from about 720p to about 4K, depending on network capacity and rendering pipeline constraints.

[0187] At block 1002, stream compression and encoding may be applied to the captured video feeds by executing encoding pipelines, thereby reducing data bandwidth while preserving visual fidelity' suitable for real-time MR rendering. In some aspects, adaptive bitrate streaming, hardware-accelerated encoding, or low-latency codec modes such as H.265 / HEVC or AVI may be employed. The operations of block 1002 may include, without limitation, performing intra- and inter-frame compression, chroma subsampling, and temporal frame prediction. In the MR theater environment, block 1002 may compress multiple high-definition stage feeds for transmission to localized MR processing nodes or cloud-rendering systems. Compression may maintain transmission of high-resolution video streams across local or remote networks without introducing disruptive delays, thereby preserving the real-time nature of MR experiences. In some aspects, block 1002 may implement codecs such as H.265, AVI, or equivalent low-latency encoders configured with motion-vector prediction and region-of- interest prioritization to maintain clarity on performer regions while minimizing total throughput.

[0188] At block 1003. video stream synchronization may be performed by aligning frame timestamps and network-delivery sequences, thereby ensuring temporal coherence among distributed camera feeds and other MR data streams. In some aspects, video stream synchronization may be coordinated with spatial mapping data generated according to the SLAM process of FIG. 6, as well as with stage cues, actor gestures, and environmental sensor outputs to maintain temporal alignment across performance elements. The operations of block- 60 -107298845 1PATENTAttorney Docket No. 130586-8663481003 may include, without limitation, clock synchronization, buffer alignment, and packetdelay compensation. In the MR theater environment, block 1003 may synchronize multiple camera perspectives such that performer movements appear continuous across adjacent projections or headset views. In some aspects, block 1003 may utilize precision time protocol (PTP), frame-count alignment, or motion-vector correlation to reconcile temporal offsets within a tolerance of less than 5 milliseconds.

[0189] At block 1004, projection geometry' may be interpreted by computing the spatial relationships between captured camera viewpoints and the surfaces onto which imagery will be projected, thereby enabling accurate reprojection within the MR coordinate frame. The operations of block 1004 may include, without limitation, performing camera calibration, estimating lens distortion, and solving for extrinsic parameters relative to the MR scene. In the MR theater environment, block 1004 may model the geometry of stage screens, floor panels, or curved projection surfaces so that live camera feeds can be rendered with correct perspective alignment. In some aspects, block 1004 may use homography estimation, bundle-adjustment algorithms, or marker-based calibration routines to compute transformation matrices mapping camera pixels to real-world coordinates.

[0190] At block 1005, spatial registration and surface mapping may be executed by aligning the interpreted projection geometry with the mixed reality environment, thereby establishing correspondence between live imagery and physical surfaces. The operations of block 1005 may include, without limitation, generating UV-mapping coordinates, refining surface normals, and anchoring projection planes to tracked spatial anchors. In the MR theater environment, block 1005 may align live performer feeds onto stage walls or props that serve as interactive display surfaces. In some aspects, live video feeds may be mapped onto virtual projection screens, digital stage backdrops, or other designated surfaces visible to audience members. Calibration may further involve registration against venue anchors or performer-tracking beacons to maintain spatial alignment during dynamic stage configuration changes. In some aspects, block 1005 may employ iterative-closest-point (ICP) algorithms or photogrammetric refinement techniques to maintain registration accuracy as physical elements shift or deform during the performance.

[0191] At block 1006, visual blending and segmentation may be applied by compositing live camera imagery with virtual scene elements, thereby achieving seamless integration of real and synthetic content. The operations of block 1006 may include, without limitation, background- 61 -107298845 1PATENTAttorney Docket No. 130586-866348 subtraction, alpha-mask generation, color balancing, and light-field adjustment. In the MR theater environment, block 1006 may segment performers from background curtains and blend them into digital environments or holographic extensions of the stage. In some aspects, block 1006 may utilize neural-network-based semantic segmentation models or GPU-accelerated chroma-keying pipelines to maintain low-latency compositing at high resolution.

[0192] At block 1007, live content analysis and feature detection may be performed by extracting contextual information from incoming video frames, thereby enabling responsive interactions and adaptive scene control. The operations of block 1007 may include, without limitation, detecting performer positions, gestures, lighting cues, or object movements within the captured feed. In the MR theater environment, block 1007 may identify hand gestures or stage lighting changes to trigger corresponding digital effects within the MR presentation. In some aspects, block 1007 may employ convolutional neural networks (CNNs) or transformerbased vision models to detect semantic features and temporal motion patterns, generating metadata streams that inform subsequent compositing or synchronization stages. Where live feeds include personally identifiable imagery7such as audience faces, processing may adhere to opt-in consent protocols, employ on-device filtering where feasible, and ensure encrypted transport with limited retention to defined analysis periods.

[0193] At block 1008. feature binding and depth fusion may be performed by combining detected features with depth or spatial information, thereby reconstructing a volumetric representation of live scene elements. The operations of block 1008 may include, without limitation, merging multi-camera depth data, fusing optical-flow7fields, and reconstructing sparse or dense 3D meshes. In the MR theater environment, block 1008 may generate volumetric performer models that can be dynamically illuminated or repositioned within digital stage sets. In some aspects, block 1008 may employ voxel-carving, multi-view stereo reconstruction, or neural radiance-field (NeRF) fusion to synthesize consistent volumetric results while maintaining real-time frame rates.

[0194] At block 1009, synchronization and latency control may be executed by adjusting frame delivery timing and processing pipelines, thereby maintaining temporal alignment between live-camera imagery and virtual scene rendering. The operations of block 1009 may include, without limitation, managing render queues, buffering frames, and compensating for encoder-decoder latency. In the MR theater environment, block 1009 may ensure that performer movements in the live feed coincide precisely with corresponding holographic- 62 -107298845 1PATENTAttorney Docket No. 130586-866348 overlays or virtual lighting cues. In some aspects, block 1009 may include predictive latency compensation algorithms or adaptive buffer management to sustain perceptual synchronization across heterogeneous rendering systems. In certain implementations, video-pipeline latencies may be maintained under approximately 100 milliseconds, with motion-to-photon response targets of about 20 milliseconds or less, thereby sustaining perceptual coherence across live and virtual layers.

[0195] At block 1010, rendering and output distribution may be performed by generating final composited frames incorporating both live and virtual content, thereby producing synchronized mixed reality outputs across all viewing devices. The operations of block 1010 may include, without limitation, GPU-based rasterization, shader-driven compositing, colorspace correction, and frame encoding for delivery to MR headsets, projection systems, or broadcast channels. In the MR theater environment, block 1010 may render integrated imagery of live performers and virtual scenery projected seamlessly onto physical surfaces visible to both the audience and remote viewers. Adaptive quality-of-service (QoS) logic may dynamically balance resolution, frame rate, and audio fidelity7across heterogeneous devices, gracefully reducing visual quality under bandwidth constraints while preserving synchronization and narrative coherence. In some aspects, block 1010 may utilize distributed rendering clusters or cloud-based pipelines employing parallelized GPU encoding to sustain frame rates of at least 90 Hz with end-to-end latency below 50 milliseconds.

[0196] While the aspect of FIG. 10 is described in the context of a representative live-camera integration pipeline, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 1001-1010 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In certain aspects, live video feeds may7be distributed in raw form, partially pre- processed with computer-vision overlays, or fully composited prior to integration, thereby accommodating a range of device capabilities and production conditions. In continued operation, method 1000 may maintain coherence by recalibrating cameras, refreshing synchronization parameters, and re-invoking blocks 1002-1010 as environmental conditions evolve. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 10, but also variations that achieve comparable live-feed integration and synchronization across physical, digital, or hybrid MR environments. Unless stated- 63 -107298845 1PATENTAttorney Docket No. 130586-866348 otherwise, the methods of FIG. 10 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0197] In view of the foregoing, the operations described with reference to FIGS. 6-10 illustrate representative techniques by which a mixed reality system may capture, interpret, and render a hybrid environment with frame-aligned latency. The operations include, without limitation, SLAM, removal and occlusion handling, viewpoint manipulation, virtual position movement, and live camera-feed integration, each presented as a method flow within the generalized pipeline of FIG. 5. In certain implementations, portions of these operations may be pre-computed, executed locally on mixed reality devices, or offloaded to cloud or edge servers, thereby allowing flexible distribution of processing workloads depending on latency, bandwidth, and deployment constraints. These operations are non-limiting and may execute in whole or in part, sequentially or concurrently, and may be reordered or fused, provided they conform to the interface and protocol layer of FIG. 4A and the control and orchestration layer of FIG. 4B. Building on this foundation, the disclosure now turns to higher-level adaptive content-management functions, including a biometric-adaptive content pipeline w ith reference to FIG. 11, a personalized mixed reality content pipeline with reference to FIG. 19, a personalized character pipeline with reference to FIG. 27, and a location-based content pipeline with reference to FIG. 34.

[0198] Having established the core mixed reality operations with reference to FIGS. 5-10, attention is now directed to higher-level adaptive content functions, illustrated in FIGS. Ills. These functions, which may operate in conjunction with the pipeline described in FIG. 5 and the subsystems of the core mixed reality engine (301-305), leverage biometric, contextual, and interaction-based inputs to guide real-time adaptation of mixed reality content. The following figures illustrate example method flows for these adaptive functions, each described in a non-limiting manner to demonstrate how feedback and contextual data may be integrated into mixed reality theater experiences and other deployment contexts.

[0199] Turning now to FIG. 11, an example biometric-adaptive content pipeline is illustrated in accordance with aspects of the present disclosure. As shown, the pipeline may include discrete blocks for biometric data collection, content mapping and anchor tracking, biometric data processing and interpretation, scene effectiveness scoring, and adaptive feedback. The arrangement of FIG. 11 is presented in generalized form to demonstrate how biometric and contextual inputs may be captured, analyzed, and applied to adjust mixed reality content in real- 64 -107298845 1PATENTAttorney Docket No. 130586-866348 time, thereby enabling personalized, audience-aware, and dynamically responsive experiences. In the representative MR theater environment, the pipeline may monitor physiological signals such as heart rate, gaze, or galvanic skin response to infer engagement and emotional state, and may adjust narrative pacing, visual emphasis, or environmental cues accordingly. Although described in the context of a theater-based audience engagement system, the pipeline of FIG. 11 may likewise be implemented in enterprise, educational, entertainment, or collaborative contexts without departing from the scope of the present disclosure. Unless stated otherwise, the blocks shown — including biometric data collection, content mapping, biometric interpretation, scene scoring, and adaptive feedback — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 11, but also variations that achieve comparable orchestration of adaptive mixed reality content in different physical, digital, or hybrid environments.

[0200] At block 1101, biometric data may be collected by acquiring physiological, behavioral, or interaction-based signals from one or more audience members, thereby providing real-time indicators of engagement, emotion, or attention within the mixed reality environment. For example, operations at block 1101 may involve obtaining first sensor measurements from one or more biometric sensors during a first time period. The operations of block 1101 may include, without limitation, capturing heart rate, electrodermal activity, facial expression, gaze direction, pupil dilation, voice inflection, gesture dynamics, body posture, or motion telemetry, as well as contextual data such as environmental lighting or seat- embedded sensor readings. In the representative MR theater environment, block 1101 may involve audience seats equipped with heart-rate and galvanic-skin-response sensors, cameras monitoring facial expressions and gaze, and wearable or near-field devices transmitting biometric telemetry’ to a local venue server. In some aspects, data collection may occur locally on mixed reality headsets or through venue infrastructure using privacy -preserving aggregation, anonymization, or differential encoding protocols. In some aspects, the raw signals may be filtered to remove noise, normalized against session baselines, and validated for data integrity prior to downstream analysis. Block 1101 may thus establish a continuous feedback layer through which audience state data is captured and made available for adaptive content orchestration.- 65 -107298845 1PATENTAttorney Docket No. 130586-866348

[0201] At block 1102, biometric and contextual data may be mapped to content anchors by correlating audience responses with spatial, temporal, or narrative elements of the mixed reality experience, thereby enabling alignment between physiological states and specific content segments. Device pose and gaze vectors may be resolved to determine the user’s instantaneous field of view, enabling spatially accurate binding of biometric samples to visible content elements. The operations of block 1102 may include, without limitation, associating biometric response data (e.g., vectors) with scene identifiers, digital object IDs, narrative beats, or environmental triggers, and maintaining anchor tracking across changing spatial or temporal contexts. In the representative MR theater environment, block 1102 may associate spikes in heart rate or gaze concentration with the activation of particular holographic projections or soundscapes, enabling correlation between emotional engagement and content regions. In some aspects, anchor tracking may employ tagging structures or scene graph mappings to maintain persistent associations between content and response data, while synchronization protocols ensure frame- accurate correspondence between audience telemetry and system events. Block 1102 may thus maintain dynamic linkage between measured audience reactions and corresponding mixed reality stimuli for downstream interpretation. In an aspect, operations may include generating a first set of features from the first sensor measurements. A baseline biometric profile representative of an initial physiological state of a participant may be derived from a first set of features.

[0202] At block 1103, biometric data may be processed and interpreted by analyzing collected signals and derived features, thereby inferring individual or collective audience states. Examples of audience states (e.g., user states) include, but are not limited to, engagement, attention, arousal, sentiment, or fatigue. The operations of block 1103 may include, without limitation, filtering noise, normalizing sensor data, extracting statistical or frequency-domain features, and classifying user states using trained models or rule-based systems. In the representative MR theater environment, block 1103 may involve machine-learning models trained on prior audience sessions to interpret patterns of heart-rate variability, gaze dwell time, or micro-expression dynamics, generating inferred emotional states such as surprise, anticipation, or disinterest. Confidence scores or uncertainty estimates may be computed for each inferred state, with low-confidence inferences filtered or flagged prior to publication to the adaptive logic layer. In some aspects, block 1103 may include fusion logic combining multimodal biometric signals — such as physiological, visual, and vocal features — to enhance- 66 -107298845 1PATENTAttorney Docket No. 130586-866348 interpretive accuracy under varied environmental conditions. Block 1103 may thus yield individual or aggregated emotional-state vectors suitable for adaptive scene scoring and realtime feedback.

[0203] In an aspect, the operations may involve providing, to the participant, a content sequence including a plurality of content segments. Each content segment may be associated with a label identifying a level of emotional intensify, engagement demand, or cognitive load represented in the segment. In an aspect, the operations may involve obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors. In an aspect, the operations may involve generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments. In an aspect, the operations may involve providing the baseline biometric profile and the second set of features to a machine-learning model configured to output a physiological response score.

[0204] At block 1104, scene effectiveness may be scored by evaluating biometric and contextual interpretations against defined performance metrics, thereby quantifying audience engagement and informing adaptive control logic. Scene scores may be computed as weighted aggregates of anchor-linked responses, where weighting factors include exposure duration, dwell time, response intensity, and cohort size. The operations of block 1104 may include, without limitation, computing scene-level engagement scores, generating effectiveness heatmaps, or evaluating temporal trends in audience response strength. In the representative MR theater environment, block 1104 may analyze engagement patterns across seating zones to identify scenes that sustain or diminish audience attention, enabling producers or automated logic to dynamically adjust pacing, visual complexity, or sensory intensity. In some aspects, scoring functions may apply weighted averages of biometric indicators, machine-learning regression models, or reinforcement-learning reward structures to derive normalized effectiveness scores. Block 1104 may thus generate real-time quantitative metrics that guide scene optimization and adaptive decision-making within mixed reality performances. For instance, operations may include calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the presented content.

[0205] At block 1105, adaptive feedback may be generated by applying scene effectiveness results and inferred audience states to modify or control mixed reality content, thereby achieving real-time adaptation of the user experience. The operations of block 1105 may- 67 -107298845 1PATENTAttorney Docket No. 130586-866348 include, without limitation, adjusting visual, auditory', or environmental parameters; modifying narrative pacing or branching; selecting alternative content paths; or orchestrating synchronized system-wide responses. In the representative MR theater environment, block 1105 may cause lighting color shifts, dynamic sound adjustments, or alternate holographic overlays in response to aggregate audience engagement trends, creating an evolving performance that adapts in real time to collective sentiment. Feedback monitoring may be performed to evaluate post-adaptation biometric responses, enabling iterative refinement of the adjustment logic. In certain aspects, rollback mechanisms may revert adaptive changes upon detection of adverse audience responses. In some aspects, adaptive feedback logic may be governed by hierarchical control models, wherein local modules handle individual user adjustments while global controllers coordinate venue-wide responses. Block 1105 may thus close the adaptive loop by transforming biometric intelligence into synchronized, data-driven modulation of mixed reality content.

[0206] While the aspect of FIG. 11 is described in the context of a representative biometric- adaptive content pipeline, it will be understood that the illustrated arrangement is not limiting. As shown, FIG. 11 illustrates a globalized adaptive content pipeline in which biometric data collection block 1101, content mapping and anchor tracking block 1102, biometric data processing and interpretation block 1103, scene effectiveness scoring block 1104, and adaptive feedback block 1105 are integrated into a continuous process that enables real-time adaptation of mixed reality content. Each of these operations may likewise be understood as a constituent method within the larger adaptive framework, operable independently or in coordinated fashion to achieve comparable responsiveness and personalization across deployment contexts. In continued operation, the pipeline may maintain coherence by collecting telemetry, updating interpretive models as conditions evolve, and re-invoking blocks 1101-1105 in accordance with timing, policy, or adaptive control constraints. The subsequent FIGS. 12-16. which illustrate example localized method flows described in a non-limiting manner, are intended to further demonstrate how the global method of FIG. 11 may be decomposed into modular operations without departing from the scope of the present disclosure. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 11, but also variations that achieve comparable orchestration of adaptive, biometric-responsive mixed reality content in physical, digital, or hybrid environments. Unless stated otherwise, the- 68 -107298845 1PATENTAttorney Docket No. 130586-866348 methods of FIG. 11 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0207] Certain aspects relate processes for calculating effectiveness scores from data such as biometric data. In an aspect, a process involves obtaining first sensor measurements from one or more biometric sensors during a first time period. The process may further involve generating a first set of features from the first sensor measurements. The process may further involve deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant. The process may further involve providing, to the participant, a content sequence including a plurality of content segments, each content segment associated with a label identifying a level of emotional intensify, engagement demand, or cognitive load represented in the segment; The process may further involves obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors. . The process may further involve generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments. The process may further involve providing the baseline biometric profile and the second set of features to a machinelearning model configured to output a physiological response score. The process may further involve calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence. Processes 1200, 1300, 1400, and / or 1500 of FIGs. 12-15 provide further examples and detail.

[0208] Having described the globalized adaptive content pipeline with reference to FIG. 11, attention is now directed to FIG. 12, which illustrates an example of a biometric-data- collection method 1200 in accordance with aspects of the present disclosure. As shown, the method 1200 may include discrete blocks for acquiring biometric input signals, block 1201, calibrating baseline and session parameters, block 1202, filtering, de-noising, and normalizing signals, block 1203, timestamping and synchronizing biometric samples, block 1204, and validating signal quality and buffering to an intake queue, block 1205. The arrangement of FIG. 12 is presented in generalized form to demonstrate how physiological and behavioral data may be captured, conditioned, and prepared for downstream fusion within an adaptive mixed reality content system. In the representative MR theater environment, the method may enable audience-seat, wearable, and venue-mounted sensors to capture signals such as heart rate, galvanic skin response, or gaze position while maintaining alignment across thousands of- 69 -107298845 1PATENTAttorney Docket No. 130586-866348 simultaneous participants. Although described in the context of a theater-based deployment, the method of FIG. 12 may likewise be implemented in enterprise, educational, or collaborative environments without departing from the scope of the present disclosure.

[0209] At block 1201, biometnc input signals may be acquired by capturing physiological or behavioral data from one or more sensing devices, thereby establishing the foundational data stream for adaptive content generation. The operations of block 1201 may include, without limitation, acquiring electrodermal activity, heart-rate variability, respiration rate, pupil dilation, gaze trajectory, micro-expression dynamics, voice tonality, gesture motion, or posture information from fixed, wearable, or near-field sensors. In the representative MR theater environment, block 1201 may include seat-embedded electrodes for galvanic skin response, infrared cameras capturing facial expressions, and HMDs detecting gaze and blink frequency. In some aspects, acquisition may be governed by session-level privacy and consent parameters that restrict collection to opted-in participants and may implement anonymization or local preprocessing at the sensor endpoint prior to transmission. Signals may be acquired continuously or within defined sampling windows, depending on system configuration and latency targets. The signals acquired in block 1201 may thus constitute the raw multimodal biometric dataset for subsequent calibration and conditioning.

[0210] At block 1202, baseline and session parameters may be calibrated by measuring and storing reference values representative of each participant’s neutral or resting state, thereby enabling accurate normalization of subsequent measurements. Calibration may include, without limitation, determining baseline heart-rate variability, skin-conductance level, or gazestability thresholds, and may further include environmental adjustments such as ambient-light correction or temperature normalization. In the representative MR theater environment, block 1202 may occur during a pre-show calibration phase in which the system records each audience member’s baseline physiological responses under neutral lighting and audio conditions. In some aspects, dynamic recalibration may be performed periodically throughout the session to compensate for environmental drift or sensor offset. Calibration data may be stored locally or in a venue server and associated with anonymized participant identifiers for use in real-time interpretation.

[0211] At block 1203, biometric signals may be filtered, de-noised, and normalized by applying signal-processing algorithms, thereby enhancing data integrity and ensuring comparability across heterogeneous sensors. The operations of block 1203 may include,- 70 -107298845 1PATENTAttorney Docket No. 130586-866348 without limitation, band-pass or low-pass filtering, outlier rejection, baseline detrending, interpolation of missing samples, and conversion to normalized z-scores or unitless indices. Filtering may involve applying low-pass, band-pass, or wavelet-based adaptive filters, including machine-leaming-based denoising models where suitable. In the representative MR theater environment, block 1203 may apply rolling-window smoothing to heart-rate telemetry, adaptive noise reduction to galvanic-skin-response readings, and illumination compensation to facial-video inputs captured under dynamic stage lighting. In some aspects, block 1203 may employ GPU-accelerated filtering pipelines or embedded DSP units within wearable devices to maintain sub-frame processing latency. The resulting conditioned data may be stored in a common multimodal format compatible with downstream synchronization routines.

[0212] At block 1204, biometric samples may be timestamped and synchronized by assigning precise temporal identifiers and aligning multimodal data streams to a unified reference clock, thereby enabling coherent fusion with environmental or content-event data. The operations of block 1204 may include, without limitation, applying network-time-protocol (NTP) synchronization, interpolating delayed frames, and aligning sensor sampling rates through resampling or buffer adjustment. In the representative MR theater environment, block 1204 may synchronize heart-rate and gaze data to stage-cue triggers or projection-frame timestamps to ensure frame-accurate correlation between audience reactions and live performance events. In some aspects, synchronization accuracy may be maintained within a tolerance of about five milliseconds, achieved through hardware genlock or precision-time- protocol (PTP) alignment. Block 1204 may thus ensure that all biometric samples remain temporally consistent for use in subsequent mapping and interpretation stages.

[0213] At block 1205. signal quality may be validated and biometric data may be buffered to an intake queue by evaluating integrity metrics, thereby ensuring that only reliable data proceeds to analytic or adaptive layers. Validation may include, without limitation, checking for sensor dropout, saturation, or baseline drift, applying confidence scoring, and discarding low-quality samples. In the representative MR theater environment, block 1205 may identify and flag defective seat sensors or noisy optical feeds for exclusion, while aggregating validated data streams into a rolling buffer accessible to the adaptive pipeline described with reference to FIG. 11. In some aspects, the intake queue may be implemented as a low-latency circular buffer with priority tagging to ensure real-time throughput while accommodating heterogeneous sensor arrival times. Block 1205 may thereby complete the acquisition and- 71 -107298845 1PATENTAttorney Docket No. 130586-866348 conditioning phase of the biometric-adaptive feedback loop, yielding high-quality, time- aligned datasets ready for contextual mapping.

[0214] While the aspect of FIG. 12 is described in the context of a representative biometric- data-collection method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including acquisition block 1201, calibration block 1202, filtering and normalization block 1203, synchronization block 1204, and validation and buffering block 1205 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method 1200 may maintain coherence by collecting telemetry, updating calibration baselines as conditions evolve, and re-invoking blocks 1201-1205 in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 12, but also variations that achieve comparable acquisition, conditioning, and preparation of biometric data for adaptive mixed reality systems in physical, digital, or hybrid environments. Unless stated otherwise, the methods of FIG. 12 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0215] Turning now to FIG. 13, an example content-mapping and anchor-tracking method 1300 is illustrated in accordance with aspects of the present disclosure. Biometric samples collected as described with reference to FIG. 12 are mapped to content anchors within the mixed reality environment, thereby enabling correlation of biometric responses with specific digital or physical elements of a scene. As shown, the method may include discrete blocks for ingesting scene anchors and content identifiers, resolving device pose and gaze vectors, projecting anchors into the user’s field of view, binding biometric samples to anchors or content elements, and updating anchor tracking to compensate for occlusion or relocation. The arrangement of FIG. 13 is presented in generalized form to demonstrate how spatial, temporal, and contextual relationships between biometric signals and mixed reality content may be established and maintained in real time. In the representative MR theater environment, the method may align each audience member’s field of view and biometric telemetry with specific holographic, stage, or environmental elements, enabling individualized yet synchronized mapping of physiological responses to corresponding content features. Although described in the context of a theater-based deployment, the method of FIG. 13 may likewise be implemented in enterprise, educational, entertainment, or collaborative environments without- 72 -107298845 1PATENTAttorney Docket No. 130586-866348 departing from the scope of the present disclosure. Unless stated otherwise, the blocks shown — including anchor ingestion, pose resolution, field-of-view projection, biometric binding, and anchor updating — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure.

[0216] At block 1301, scene anchors and content identifiers may be ingested by retrieving spatial references, object identifiers, and metadata describing digital or physical elements within the mixed reality environment. The operations of block 1301 may include, without limitation, acquiring anchor descriptors from scene graphs, rendering engines, or tracking databases, and registering each anchor with a unique identifier suitable for subsequent mapping operations. In the representative MR theater environment, block 1301 may collect anchor definitions corresponding to stage boundaries, performer positions, projection surfaces, or holographic overlays, together forming a structured reference set for alignment with audience telemetry. In some aspects, anchors may further include semantic tags designating narrative function, emotional tone, or sensory modality, enabling downstream correlation between biometric reactions and content intent.

[0217] At block 1302, device pose and gaze vectors may be resolved by determining the viewer's instantaneous position and orientation relative to the mixed reality coordinate frame. The operations of block 1302 may include, without limitation, polling IMUs, optical trackers, or SLAM-based localization data to compute six-degree-of-freedom pose estimates and gazevector traj ectories. In the representative MR theater environment, block 1302 may resolve each audience member’s head orientation and eye gaze to establish the portion of the stage or projection surface presently visible. In some aspects, pose and gaze data may be continuously updated at rates exceeding about 90 Hz to maintain sub-frame spatial coherence between user perspective and anchor position, with predictive smoothing applied to compensate for low- latency rendering intervals.

[0218] At block 1303, anchors may be projected into the field of view by transforming anchor coordinates into the viewer's perspective space, thereby determining which content elements are visible, peripheral, or occluded at a given instant. The operations of block 1303 may include, without limitation, computing camera-space transformations, performing frustum culling, and generating field-of-view masks representing anchor visibility. In the representative MR theater environment, block 1303 may project stage-level holographic overlays into audience viewpoints, ensuring that only anchors within each viewer’s visual frustum are linked- 73 -107298845 1PATENTAttorney Docket No. 130586-866348 to corresponding biometric readings. In some aspects, projection updates may be synchronized with frame rendering cycles, ensuring that anchor visibility remains time-aligned with biometric sampling windows derived from the method of FIG. 12.

[0219] At block 1304, biometric samples may be bound to anchors or content elements by associating time-synchronized physiological responses with the anchor identifiers projected into the user’s field of view. The operations of block 1304 may include, without limitation, matching biometric sample timestamps to content-frame timestamps, performing spatial crossreferencing between gaze vectors and anchor positions, and storing linkage records describing which biometric responses correspond to which scene elements. In the representative MR theater environment, block 1304 may associate elevated heart-rate or skin-conductance readings with specific visual or auditory cues, such as a lighting change or performer motion, thereby enabling high-resolution mapping of emotional or attentional reactions. In some aspects, binding operations may incorporate probabilistic matching or weighting factors to account for partial gaze overlap or concurrent stimuli, ensuring stable correlation under complex sensory' conditions.

[0220] At block 1305, anchor tracking may be updated to account for occlusion, relocation, or scene dynamics, thereby preserving valid associations between biometric data and content references as conditions evolve. The operations of block 1305 may include, without limitation, monitoring anchor visibility states, recomputing transformations following performer movement or camera changes, and applying re-registration logic when anchors shift within the scene. For example, if a digital overlay is temporarily hidden behind a physical prop, the anchor state may be updated to reflect its occluded condition. In the representative MR theater environment, block 1305 may update anchor mappings when stage props are repositioned, holographic overlays animate, or audience viewpoints change due to head movement. In some aspects, occlusion-handling logic may reference depth maps or scene-layer hierarchies to maintain continuity between visible and hidden anchors, preventing the propagation of invalid mappings during rapid transitions.

[0221] While the aspect of FIG. 13 is described in the context of a representative contentmapping and anchor-tracking method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including ingestion block 1301, pose resolution block 1302, projection block 1303, binding block 1304, and tracking update block 1305 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without- 74 -107298845 1PATENTAttorney Docket No. 130586-866348 departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by collecting telemetry, refreshing anchor states, and re-invoking blocks 1301-1305 in accordance with timing, policy, or rendering constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 13, but also variations that achieve comparable spatial mapping and content-association performance across physical, digital, or hybrid MR environments. Unless stated otherwise, the methods of FIG. 13 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0222] Turning now to FIG. 14, an example biometric data processing and interpretation method 1400 is illustrated in accordance with aspects of the present disclosure. Biometric samples mapped to content anchors as described with reference to FIG. 13 are processed to extract features and infer user states. As shown, the method may include discrete blocks for windowing biometric signals and extracting features, normalizing features to personal or cohort baselines, inferring user states of arousal, attention, or fatigue, assigning confidence or uncertainty7values, and publishing interpreted states to an analytics layer. The arrangement of FIG. 14 is presented in generalized form to demonstrate how raw biometric and contextual inputs may be transformed into structured, interpretable user-state information suitable for adaptive control. In the representative MR theater environment, the method may analyze audience telemetry' streams to infer real-time engagement and emotional states, such as excitement, boredom, or anticipation, and communicate these metrics to adaptive orchestration systems. Although described in the context of a theater-based environment, the method of FIG. 14 may likewise be implemented in enterprise, educational, entertainment, or collaborative applications without departing from the scope of the present disclosure. Unless stated otherwise, the blocks shown — including feature extraction, normalization, inference, confidence assignment, and publishing — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure.

[0223] At block 1401, biometric signals may be collected (e.g., windowed) and processed to extract discriminative features, thereby transforming continuous sensor streams into quantifiable indicators of physiological or behavioral state. For example, at block 1401, first sensor measurements from one or more biometric sensors during a first time period may be obtained. In some cases, windowing may be used. Windowing may be performed over fixed or- 75 -107298845 1PATENTAttorney Docket No. 130586-866348 adaptive time intervals, depending on the dynamics of the content being presented. The operations of block 1401 may include, without limitation, applying temporal or frequencydomain windowing, computing feature vectors representing amplitude, variance, frequency energy, or entropy, and generating derived metrics such as heart-rate variability or blink rate. In the representative MR theater environment, block 1401 may process synchronized inputs from heart-rate monitors, eye-tracking sensors (e.g.. camera), and galvanic skin sensors to compute micro-window features aligned with the timing of specific visual or auditory events. In some aspects, sliding or overlapping window functions may be employed to improve temporal granularity' and reduce the likelihood of aliasing across stimulus transitions. In an aspect, a first set of features (e.g., biometric features) may be generated or derived from the first sensor measurements.

[0224] At block 1402. the extracted biometric features may be normalized to personal or cohort baselines, thereby accounting for inter-user variability and establishing consistent reference frames for interpretation. The operations of block 1402 may include, without limitation, computing z-scores, percent-change metrics, or statistical deviations relative to presession or dynamically updated baselines. In the representative MR theater environment, block 1402 may normalize audience heart-rate and gaze-dwell features against each viewer’s initial calibration values or the median values of the surrounding cohort, ensuring that inferred responses reflect relative engagement rather than absolute sensor output. In some aspects, adaptive normalization techniques may be used to update baseline references continuously as session conditions evolve, maintaining accuracy under varying environmental or physiological conditions.

[0225] At block 1403. user states such as arousal, attention, or fatigue may be inferred by analyzing normalized features through model-based or data-driven classification methods, thereby generating interpretable cognitive or affective indicators. Inference may be performed using rule-based thresholds, statistical models, or machine-learning classifiers trained on labeled biometric datasets. The operations of block 1403 may include, without limitation, applying rule-based heuristics, supervised learning classifiers, or multimodal fusion models to identify user-state categories. In the representative MR theater environment, block 1403 may employ ensemble machine-learning models trained on multimodal audience datasets to infer collective emotional states and attention shifts in real time, enabling adaptive control systems to recognize when engagement wanes or intensifies. In various aspects, multiple features may- 76 -107298845 1PATENTAttorney Docket No. 130586-866348 be fused to improve robustness of state estimation. In some aspects, inference algorithms may incorporate temporal smoothing, probabilistic state transitions, or contextual priors derived from narrative timing or scene complexity.

[0226] At block 1404, confidence or uncertainty values may be assigned to each inferred user state to quantify interpretive reliability and support downstream decision weighting. Confidence scoring may be based on feature quality', signal-to-noise ratio, model certainty, or consistency across modalities. The operations of block 1404 may include, without limitation, computing posterior probabilities, Bayesian confidence intervals, or entropy-based uncertainty estimates. In the representative MR theater environment, block 1404 may assign higher confidence scores to states inferred from strong, multi-sensor agreement (e.g., simultaneous spikes in heart rate and gaze fixation) and lower confidence scores where signals diverge or degrade. In some aspects, adaptive weighting models may re-balance confidence metrics in real time based on historical system performance, sensor integrity, or user calibration fidelity.

[0227] At block 1405, the interpreted user states may be published to an analytics or adaptive control layer for integration with scene-scoring and feedback -generation processes, thereby completing the interpretation pipeline. This publication may occur through a standardized data bus, shared memory, or message-passing system within the MR engine, ensuring that user state information is available to other subsystems for real-time content adjustment. The operations of block 1405 may include, without limitation, transmitting structured user-state vectors, logging interpretive metadata, or updating shared memory spaces accessible to adaptive systems. In the representative MR theater environment, block 1405 may forward aggregated emotional-state vectors to a scene orchestration engine, where engagement metrics drive dynamic adjustments to pacing, lighting, or narrative flow. In some aspects, publishing may occur through low-latency^ data channels or distributed message buses that preserve temporal ordering and enable synchronization with content timelines.

[0228] While the aspect of FIG. 14 is described in the context of a representative biometric data processing and interpretation method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including feature extraction block 1401. normalization block 1402, inference block 1403, confidence assignment block 1404, and publication block 1405 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by collecting telemetry, refining inference models as new data- 77 -107298845 1PATENTAttorney Docket No. 130586-866348 becomes available, and re-invoking blocks 1401-1405 in accordance with timing, policy, or adaptive control constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 14, but also variations that achieve comparable interpretive and analytical performance across physical, digital, or hybrid MR environments. Unless stated otherwise, the methods of FIG. 14 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media. The following figure therefore turns to scene effectiveness scoring, which demonstrates how the interpreted states may be aggregated and evaluated at a scene level to quantify audience engagement.

[0229] Turning now to FIG. 15, an example scene effectiveness scoring method 1500 is illustrated in accordance with aspects of the present disclosure. Interpreted biometric states described with reference to FIG. 14 are aggregated and evaluated at a scene level to generate quantitative indicators of audience engagement. As shown, the method may include discrete blocks for aggregating anchor-linked biometric responses, applying weighting factors, computing scene or beat-level effectiveness scores, comparing scores against thresholds or benchmarks, and outputting results to an adaptive logic layer. The arrangement of FIG. 15 is presented in generalized form to demonstrate how aggregated biometric data may be synthesized into quantitative engagement metrics that inform adaptive control and content optimization. In the representative MR theater environment, the method may continuously evaluate audience reactions across multiple spatial zones, correlating biometric activity with specific narrative beats or visual compositions to generate dynamic indicators of scene resonance. Although described in the context of a theater-based deployment, the method of FIG. 15 may likewise be implemented in enterprise, educational, entertainment, or collaborative environments without departing from the scope of the present disclosure. Unless stated otherwise, the blocks shown — including response aggregation, weighting, computation, comparison, and output — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure.

[0230] At block 1501, anchor-linked biometric responses may be aggregated by collecting the interpreted user states and physiological signals associated with each content anchor, thereby producing a dataset suitable for higher-level analysis. The operations of block 1501 may include, without limitation, grouping biometric samples by anchor identifier, temporal segment, or scene index, and computing aggregate metrics such as mean arousal, variance of- 78 -107298845 1PATENTAttorney Docket No. 130586-866348 attention, or cumulative response intensity. In the representative MR theater environment, block 1501 may aggregate audience responses across different seating zones or projection areas, creating a synchronized view of how distinct content regions contribute to overall engagement. In some aspects, aggregation may include temporal smoothing or clustering algorithms that align asynchronous responses to shared scene boundaries.

[0231] At block 1502, weighting factors may be applied to the aggregated biometric responses to account for exposure duration, dwell time, response intensity, and cohort size, thereby refining the contribution of each response to the computed effectiveness score. The operations of block 1502 may include, without limitation, calculating duration-weighted averages, assigning higher weights to sustained attention or strong emotional responses, and normalizing across variable audience participation levels. In the representative MR theater environment, block 1502 may assign greater influence to responses recorded during key narrative beats or prolonged gaze-fixation periods, ensuring that scenes with deeper engagement are proportionally emphasized in the resulting score. In some aspects, weighting coefficients may be adaptively tuned using feedback from historical performance data or realtime learning models.

[0232] At block 1503, scene or beat-level effectiveness scores may be computed by combining weighted biometric responses into a unified metric representing the intensity, coherence, and consistency of audience engagement. The operations of block 1503 may include, without limitation, performing weighted summation, statistical regression, or machine-leaming-based fusion to derive normalized scores for each scene or narrative segment. These scores may be expressed as numerical indices, categorical ratings, or probability distributions reflecting audience engagement intensity. In the representative MR theater environment, block 1503 may compute both instantaneous and cumulative engagement scores that quantify audience attention or emotional resonance over time. In some aspects, distinct scoring functions may be defined for arousal, focus, or valence, with composite indices generated through multidimensional weighting matrices.

[0233] At block 1504, computed scores may be compared against predefined thresholds, benchmarks, or historical averages to determine relative scene performance and trigger adaptive adjustments where applicable. The operations of block 1504 may include, without limitation, evaluating scores against baseline expectations, identifying statistically significant deviations, and classifying scenes as underperforming, optimal, or exceeding engagement- 79 -107298845 1PATENTAttorney Docket No. 130586-866348 targets. In the representative MR theater environment, block 1504 may trigger modifications to lighting, pacing, or narrative intensity when real-time engagement falls below predetermined levels. Thresholds may be adjusted automatically over time to account for evolving audience dynamics, environmental factors, or production objectives. In some aspects, comparison logic may incorporate reinforcement-learning feedback loops, allowing the system to refine benchmark thresholds based on prior audience sessions.

[0234] At block 1505, the resulting scene effectiveness scores and diagnostic metadata may be output to an adaptive logic layer, enabling real-time orchestration and continuous improvement of mixed reality content. The operations of block 1505 may include, without limitation, transmitting scene scores through low-latency communication channels, logging historical performance data, and updating adaptive control parameters. Outputs may include not only numerical scores but also metadata identifying contributing anchors, audience subgroups, or contextual variables, and may be stored in a database for long-term trend analysis, archival, or cross-performance comparison. In the representative MR theater environment, block 1505 may forward effectiveness scores to a director console or automated control subsystem, where adjustments to narrative flow, sound intensity, or projection timing are enacted based on audience response patterns. In some aspects, outputs may include trend analyses or confidence-weighted performance indicators to guide both automated and human- in-the-loop decision-making.

[0235] While the aspect of FIG. 15 is described in the context of a representative scene effectiveness scoring method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including aggregation block 1501, weighting block 1502, computation block 1503. comparison block 1504, and output block 1505 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by collecting telemetry, updating weighting models, and re-invoking blocks 1501-1505 in accordance with timing, policy, or adaptive-control constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 15, but also variations that achieve comparable engagement assessment and feedback performance across physical, digital, or hybrid mixed reality environments. Unless stated otherwise, the method of FIG. 15 may be implemented by one or more processors executing instructions stored on non- transitory computer-readable media.- 80 -107298845 1PATENTAttorney Docket No. 130586-866348

[0236] Turning now to FIG. 16, an example real-time adaptive feedback method 1600 is illustrated in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for ingesting interpreted states and scene scores — specifically, the interpreted biometric states described with reference to FIG. 14 and the scene effectiveness scores described with reference to FIG. 15 — evaluating adaptive policies and safetyconstraints, selecting an adjustment plan based on predefined rules or learned models, modifying mixed reality scene parameters, and monitoring audience responses to refine or roll back adjustments as needed. The arrangement of FIG. 16 is presented in generalized form to demonstrate how feedback mechanisms may operate as a closed-loop system for continuous adaptation of mixed reality content. In the representative MR theater environment, the method may analyze biometric-derived engagement signals in real time, apply policy-driven constraints for pacing and safety, and dynamically adjust lighting, projection, or narrative flow to sustain optimal audience immersion, determining whether and how to modify mixed reality content in real time. Although described in the context of a theater-based performance system, the adaptive feedback method of FIG. 16 may likewise be implemented in enterprise, educational, entertainment, or collaborative contexts without departing from the scope of the present disclosure. Unless stated otherwise, the blocks shown — including feedback ingestion, policy evaluation, plan selection, parameter modification, and response monitoring — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure.

[0237] At block 1601, interpreted audience states and scene effectiveness scores may be ingested by the adaptive control layer, thereby providing real-time context for decision-making. The operations of block 1601 may include, without limitation, retrieving engagement vectors, emotional-state probabilities, and scene-level metrics from analytics or scoring subsystems described with reference to FIGS. 14-15. In the representative MR theater environment, block 1601 may involve streaming aggregated biometric indicators and scene performance data into a central adaptive-logic processor. In some aspects, redundant or delayed data may be reconciled using temporal alignment or priority weighting to ensure coherent feedback operation. Block 1601 thus establishes a data interface between interpretation layers and adaptive decision modules.

[0238] At block 1602, adaptive policies and safety constraints may be evaluated by parsing the ingested metrics against predefined rules, boundaries, or ethical guidelines, thereby- 81 -107298845 1PATENTAttorney Docket No. 130586-866348 ensuring that adaptive operations remain within safe and intended behavioral limits. The operations of block 1602 may include, without limitation, checking threshold boundaries for physiological stress, validating content-compliance conditions, or applying rate-limiting functions to prevent abrupt or excessive environmental change. In the representative MR theater environment, block 1602 may ensure that adaptive modifications — such as light intensity or sound amplitude — do not exceed comfort or accessibility thresholds. In some aspects, adaptive policy sets may be dynamically updated based on context, user preferences, or regulatory profiles. Such policies may include creative rules established by directors, performance objectives defined by producers, or ethical safeguards for audience well-being, thereby ensuring that adaptations remain consistent with creative and operational intent.

[0239] At block 1603, an adjustment plan may be selected by evaluating available rules, models, or policy outcomes to determine the optimal modification path for mixed reality content. The operations of block 1603 may include, without limitation, invoking rule-based logic trees, predictive neural networks, or optimization heuristics to select one or more scenemodification strategies. In the representative MR theater environment, block 1603 may determine whether to increase narrative tempo, alter lighting coloration, or vary holographic density based on real-time engagement decay. In some aspects, multi-objective optimization techniques may balance engagement, comfort, and pacing metrics when selecting the adaptive response.

[0240] At block 1604, mixed reality scene parameters may be modified according to the selected adjustment plan, thereby implementing the adaptive response in the live environment. The operations of block 1604 may include, without limitation, altering rendering parameters, audio-mix levels, lighting cues, or spatial-projection timing. In the representative MR theater environment, block 1604 may adjust holographic overlay brightness, soundtrack intensity, or ambient effects in proportion to measured audience arousal, including adjustments to lighting, audio, pacing, narrative progression, or digital overlays. Modifications may be deployed immediately or phased in gradually to minimize disruption, and adjustments may be applied selectively across devices, cohorts, or the entire audience, depending on system configuration. In some aspects, distributed control protocols may coordinate multiple devices or projection nodes to achieve coherent venue-wide adaptation with minimal perceptible latency.

[0241] At block 1605, audience responses may be monitored following the adaptive change, thereby enabling refinement or rollback as needed to maintain stability and comfort. The- 82 -107298845 1PATENTAttorney Docket No. 130586-866348 operations of block 1605 may include, without limitation, monitoring post-adaptation biometric trends, detecting recovery patterns, and comparing updated engagement scores against pre-adaptation baselines. In the representative MR theater environment, block 1605 may track whether adaptive changes successfully re-elevate attention or reduce fatigue, and, if not, may trigger rollback or gradual normalization routines. If adverse or unintended effects are detected, rollback mechanisms may revert the scene parameters to prior states. In some aspects, block 1605 may further employ closed-loop learning algorithms to refine future adjustment plans based on historical effectiveness.

[0242] While the aspect of FIG. 16 is described in the context of a representative real-time adaptive feedback method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including ingestion block 1601, policy evaluation block 1602, plan selection block 1603, parameter modification block 1604, and monitoring block 1605 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the adaptive feedback pipeline may maintain coherence by collecting telemetry, updating models, and reinvoking blocks 1601-1605 in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 16, but also variations that achieve comparable adaptive control and user-responsive modulation in physical, digital, or hybrid mixed reality environments. Unless stated otherwise, the methods of FIG. 16 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0243] Turning now to FIG. 17, an example privacy, consent, and data security method 1700 is illustrated in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for presenting consent options and data-usage disclosures, recording user preferences and enforcing opt-outs, pseudonymizing or minimizing retained biometric data, enforcing encryption and access control, and applying retention, purge, and subjectrequest policies. The arrangement of FIG. 17 is presented in generalized form to demonstrate how privacy-management and data-protection mechanisms may be integrated into the biometric-adaptive mixed reality framework described in FIGS. 11-16. In the representative MR theater environment, the method may ensure that audience members are informed of data- collection practices, have control over participation, and are protected by encryption and access safeguards throughout the adaptive-content process. Although described in the context of a- 83 -107298845 1PATENTAttorney Docket No. 130586-866348 theater-based deployment, the method of FIG. 17 may likewise be implemented in enterprise, educational, entertainment, healthcare, or collaborative contexts without departing from the scope of the present disclosure. These measures ensure that mixed reality experiences can be deployed responsibly in compliance with applicable privacy requirements while maintaining the integrity of adaptive-content systems. Unless stated otherwise, the blocks shown — including consent presentation, preference recording, data minimization, access enforcement, and policy application — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure.

[0244] At block 1701, consent options and data-usage disclosures may be presented to participants before any biometric collection occurs. The operations of block 1701 may include, without limitation, displaying clear, human-readable notices describing the categories of data to be collected, the purposes of processing, storage duration, sharing conditions, and participant rights. Disclosures may describe the nature of data being collected, the purposes for which it will be used, retention timeframes, and available opt-out provisions. Consent may be gathered via digital prompts, written agreements, or pre-performance interfaces. In the representative MR theater environment, block 1701 may be implemented through onboarding panels, mobile consent screens, or immersive pre-show interfaces allowing explicit acceptance or rejection of biometric tracking. In some aspects, multiple tiers of consent may be provided, enabling granular control over optional analytics or adaptive-feedback participation.

[0245] At block 1702, user preferences and opt-outs may be recorded and enforced by the data-management subsystem. The operations of block 1702 may include, without limitation, registering each participant's consent state within a secure ledger, applying policy flags to govern data flow, and automatically disabling non-essential sensors for opted-out users. A user may consent to some forms of data use (e.g., anonymized research) but not others (e.g., targeted personalization). The system enforces these preferences by filtering, blocking, or adjusting downstream data flows accordingly. In the representative MR theater environment, block 1702 may ensure that any device assigned to a non-consenting participant operates solely in anonymized or non-recording mode. In some aspects, preference management may support real-time updates, allowing users to revoke or modify consent dynamically during or after a session.

[0246] At block 1703, biometric data retained by the system may be pseudonymized, aggregated, or minimized to the least amount necessary' for adaptive processing. The operations- 84 -107298845 1PATENTAttorney Docket No. 130586-866348 of block 1703 may include, without limitation, replacing personal identifiers with pseudonymous tokens, aggregating group-level statistics, and deleting raw sensor outputs once derived metrics are computed. In the representative MR theater environment, block 1703 may involve computing engagement indices from biometric samples, storing only derived numerical vectors, and discarding the original facial or physiological data. In some aspects, the pseudonymization process may include cryptographic hashing or keyed randomization techniques to prevent re-identification.

[0247] At block 1704, access control, encryption, and audit logging may be enforced to safeguard retained data. Access may be limited to authorized subsystems of the MR engine or designated operators. The operations of block 1704 may include, without limitation, encrypting biometric records at rest and in transit, enforcing role-based or attribute-based access controls, and generating immutable audit trails of access events. In the representative MR theater environment, block 1704 may ensure that only authorized system operators or privacy officers can retrieve stored engagement metrics, with all accesses time-stamped and verified. In some aspects, hardware-backed security' modules or distributed-ledger systems may be employed to record and verify audit integrity.

[0248] At block 1705, retention, purge, and subject-request policies may be applied in accordance with legal, regulatory, or organizational requirements. The operations of block 1705 may include, without limitation, enforcing automated retention periods, executing data- purge commands after session completion, and processing user-initiated access or deletion requests. Subject requests, such as requests for deletion or export of personal data, may be processed in accordance with applicable laws and policies. In the representative MR theater environment, block 1705 may ensure that biometric or engagement data are retained only for a predefined analysis window before being securely deleted or archived in anonymized form. In some aspects, policy enforcement may rely on programmable logic or smart-contract mechanisms to ensure transparent and verifiable compliance.

[0249] While the aspect of FIG. 17 is described in the context of a representative privacy, consent, and data-security method, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including consent presentation block 1701, preference recording block 1702, data minimization block 1703, access control block 1704, and policy enforcement block 1705 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued- 85 -107298845 1PATENTAttorney Docket No. 130586-866348 operation, the method of FIG. 17 may operate in coordination with the adaptive-feedback pipeline of FIG. 16 to ensure that all biometric data used for real-time content modulation are handled in accordance with explicit consent and robust privacy guarantees. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 17, but also variations that achieve comparable privacy-preserving control and regulatory compliance across physical, digital, or hybrid MR environments. The following figure therefore turns to system architecture considerations, which illustrate how the components and methods described with reference to FIGS. 11-17 may be integrated into an overall adaptive mixed reality engine.

[0250] Turning now to FIG. 18, an example system-architecture flow for a biometric- adaptive content engine 1800 is illustrated in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for initializing the MR engine and registering subsystems, establishing data pipelines for collection, analytics, and feedback, deploying models and configuration bundles, starting runtime services with telemetry monitoring, and managing workload scaling and failover orchestration. The arrangement of FIG. 18 is presented in generalized form to demonstrate how the modular methods described in FIGS. 11-17, including data collection, mapping, interpretation, scoring, adaptive feedback, and privacy enforcement, may be instantiated within a unified, runtime-operable architecture capable of supporting adaptive content control. In the representative MR theater environment, the architecture may coordinate multiple concurrent processes — such as biometric acquisition, content rendering, adaptive feedback, and privacy governance — through a distributed orchestration layer that ensures deterministic timing and fault-tolerant execution. Although described in the context of a theater deployment, the system of FIG. 18 may likewise be implemented in enterprise, educational, entertainment, healthcare, or collaborative contexts without departing from the scope of the present disclosure. Unless stated otherwise, the blocks shown — including initialization, pipeline establishment, model deployment, runtime startup, and workload management — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure.

[0251] At block 1801, the MR engine may be initialized by loading configuration profiles, allocating resources, and registering dependent subsystems, including audience interface and interaction subsystems, physical-environment instrumentation modules, mixed reality- 86 -107298845 1PATENTAttorney Docket No. 130586-866348 processing and rendering nodes, and content-management controllers (e.g., 302-305). The operations of block 1801 may include, without limitation, loading core modules for rendering, input handling, and adaptive feedback; initializing biometric interfaces; and linking the privacy and security modules described in FIG. 17. In the representative MR theater environment, block 1801 may register venue-specific devices such as audience sensors, projection servers, and audio arrays to establish baseline connectivity before runtime execution. In some aspects, engine initialization may include health checks, dependency resolution, or environment verification to ensure readiness for adaptive operation.

[0252] At block 1802, data pipelines may be established to enable continuous collection, analytics, and feedback communication among the registered subsystems. The operations of block 1802 may include, without limitation, defining ingestion channels for biometric telemetry using message queues, shared-memory segments, or distributed data buses; configuring analytic streams for state interpretation and scene scoring; and registering outbound feedback channels for adaptive-content control. In the representative MR theater environment, block 1802 may involve establishing low-latency messaging buses or publish- subscribe topics between audience sensor arrays, the MR engine core, and content orchestration nodes. In some aspects, redundant pipeline paths may be provisioned to ensure reliable transmission under high throughput or partial network failure conditions.

[0253] At block 1803, models, rules, and configuration bundles may be deployed to operational nodes, thereby enabling context-specific adaptive behavior. The operations of block 1803 may include, without limitation, deploying pre-trained biometric-interpretation models, loading scene effectiveness scoring functions, and activating adaptive-policy definitions that govern real-time modifications. In the representative MR theater environment, block 1803 may distribute lightweight inference models to edge devices co-located with sensors, while maintaining centralized policy management on a venue controller for orchestration consistency. In some aspects, configuration bundles may include performance thresholds, narrative-branching criteria, or reinforcement-learning reward structures derived from historical audience data.

[0254] At block 1804, runtime services may be started with continuous health and telemetry monitoring to maintain operational stability. The operations of block 1804 may include, without limitation, launching distributed worker nodes for biometric processing, activating rendering clusters, and initializing feedback controllers that respond to interpreted audience- 87 -107298845 1PATENTAttorney Docket No. 130586-866348 states. In the representative MR theater environment, block 1804 may start services responsible for visual projection, spatial audio modulation, and real-time adaptation scheduling. Telemetry collection may include system-health metrics, performance counters, latency traces, or audience-response coverage indicators such as frame rate and throughput statistics, ensuring that adaptive responses remain within target timing constraints.

[0255] At block 1805, workloads may be scaled dynamically and failover orchestration may be managed to sustain responsiveness and fault tolerance during operation. The operations of block 1805 may include, without limitation, provisioning additional compute instances under increased load, redistributing data streams across redundant nodes, and invoking failover routines upon detection of hardware or network anomalies. Scaling may involve allocating additional compute or memory resources in response to audience size or content complexity. In the representative MR theater environment, block 1805 may allow audience-sensor processing clusters to scale elastically as attendance fluctuates or as engagement-analysis demand increases. In some aspects, automatic recovery logic may isolate malfunctioning modules and re-instantiate replacement services without interrupting ongoing adaptive performance.

[0256] While the aspect of FIG. 18 is described in the context of a representative systemarchitecture flow, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including initialization block 1801, pipeline establishment block 1802, model deployment block 1803, runtime startup block 1804, and workload management block 1805 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the system of FIG. 18 may maintain coherence by collecting telemetry across all subsystems, updating configuration bundles as conditions evolve, and re-invoking adaptive-control routines in accordance with timing, policy, or fault-tolerance constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 18, but also variations that achieve comparable system orchestration and adaptive performance across physical, digital, or hybrid MR environments. Unless stated otherwise, the methods of FIG. 18 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media, in which the methods of biometric collection, mapping, interpretation, scoring, adaptive feedback, and privacy enforcement are coordinated under the control of the MR engine.- 88 -107298845 1PATENTAttorney Docket No. 130586-866348

[0257] In view of the foregoing, the operations described with reference to FIGS. 11-18 illustrate representative techniques by which the mixed reality system may collect, interpret, and adapt biometric and contextual inputs to drive content responsiveness within the adaptive- feedback framework. Building upon this adaptive infrastructure, the disclosure now turns to the personalized content-processing pipeline illustrated in FIGS. 19-26. These figures describe representative methods by which user-specific data, authenticated device integrations, and consented content sources may be securely accessed, curated, and incorporated into mixed reality experiences under the orchestration of the core engine (301-305). In certain implementations, portions of these operations may execute locally on audience HMDs, within venue-based edge nodes, or across distributed cloud resources, thereby allowing flexible partitioning of personalization workloads in accordance with latency, privacy, and bandwidth constraints. These operations are non-limiting and may execute sequentially or concurrently, in whole or in part, provided they conform to the orchestration interfaces of the adaptive- content framework previously described. The following figures illustrate example method flows for these personalization processes, each presented in a non-limiting manner to demonstrate how localized data handling, rendering, and narrative adaptation may be applied to deliver user-tailored mixed reality experiences across theatrical, enterprise, educational, and entertainment contexts.

[0258] Turning now to FIG. 19, an example of a personalized mixed reality content pipeline 1900 is illustrated in accordance with aspects of the present disclosure. As shown, the pipeline may include discrete blocks for establishing a secure smartphone-HMD connection, obtaining user consent and authentication, harvesting personal media and social content, preprocessing and filtering data for relevance, transmitting curated content to the mixed reality engine, integrating such content into the mixed reality rendering pipeline, and applying privacy and compliance safeguards. The arrangement of FIG. 19 is presented in generalized form to demonstrate how user-specific information may be securely accessed, curated, and introduced into a mixed reality environment. Although described in the context of a representative MR- theater deployment, the method of FIG. 19 may likewise be implemented in enterprise, educational, collaborative, or entertainment contexts without departing from the scope of the present disclosure.

[0259] At block 1901, a secure smartphone-HMD connection may be established by initiating authenticated communication channels between a user’s personal device and a mixed- 89 -107298845 1PATENTAttorney Docket No. 130586-866348 reality headset, thereby enabling controlled exchange of personalization data. The operations of block 1901 may include, without limitation, pairing via encrypted Bluetooth, Wi-Fi Direct, ultra- wideband, or equivalent low-latency protocols; performing device handshake and certificate validation; and synchronizing session keys for subsequent data exchange. In some implementations, the connection may alternatively be brokered through a local edge node or production server, enabling session management across multiple users. In the representative MR-theater environment, block 1901 may include pairing an audience member’s smartphone application w ith the theater’s MR system to allow consented personal media retrieval. In some aspects, block 1901 may further include mutual-authentication protocols, token-based authorization, or zero-knowledge handshakes operable to ensure end-to-end confidentiality and integrity of the link.

[0260] At block 1902, user consent and authentication may be obtained by presenting authorization prompts and verifying identity credentials, thereby ensuring that subsequent data access occurs under explicit, auditable permission. The operations of block 1902 may include, without limitation, displaying opt-in requests, verifying biometric or passcode authentication, generating signed consent tokens, and recording consent metadata within a compliance ledger, and generating a secure session token representing the authorized access scope, ensuring subsequent operations remain bound to user consent. In the representative MR-theater environment, block 1902 may include prompting a user through the companion application to grant temporary' access to selected photos, playlists, or avatars for inclusion in adaptive scenes. In some aspects, block 1902 may further include federated-identity validation, OAuth-based consent flows, or secure enclave storage of consent receipts operable to align with privacy regulations and organizational policies.

[0261] At block 1903, personal media and social content may be harvested by collecting user-authorized assets and metadata from device storage or networked services, thereby supplying candidate material for personalization. The operations of block 1903 may include, without limitation, enumerating local media libraries, retrieving user-shared content via API interfaces, including, without limitation, platform-provided photo-library and social-media APIs configured for user-approved retrieval, extracting caption or tag metadata, and classifying content ty pes for suitability. In the representative MR-theater environment, block 1903 may include retrieving audience-submitted images or status updates that can be dynamically composited into live scenes. In some aspects, block 1903 may further include differential-- 90 -107298845 1PATENTAttorney Docket No. 130586-866348 privacy sampling, semantic labeling, or content-trust scoring algorithms operable to maintain both personalization fidelity and confidentiality.

[0262] At block 1904, harvested data may be preprocessed and filtered for relevance by applying semantic, contextual, and technical screening operations, thereby ensuring that only suitable content proceeds to rendering. The operations of block 1904 may include, without limitation, deduplication, content-type detection, profanity and toxicity filtering, resolution normalization, and feature extraction using computer-vision or natural-language models. In the representative MR-theater environment, block 1904 may include selecting only those audience photos matching current scene themes or emotional tones. In some aspects, block 1904 may further include Al-based contextual ranking, on-device redaction of sensitive imagery, or encryption of retained metadata operable to preserve privacy while supporting adaptive selection.

[0263] At block 1905, curated content may be transmitted to the mixed reality engine by packaging approved assets and metadata into authenticated payloads, thereby enabling integration with core rendering pipelines. The operations of block 1905 may include, without limitation, compressing and encrypting content packages, signing payload headers, and performing integrity validation (e g., cryptographic hash comparison) to confirm end-to-end data fidelity, and routing transmissions through secure transport protocols such as HTTPS / TLS or QUIC. In the representative MR-theater environment, block 1905 may include uploading filtered audience imagery to a local edge server where the mixed reality engine executes adaptive placement within the performance. In some aspects, block 1905 may further include latency-aware queueing, acknowledgment tracking, or chunked streaming protocols operable to maintain sub-frame synchronization w ith live performance timing.

[0264] At block 1906, personalized content may be integrated into the mixed reality rendering pipeline by mapping received assets to designated anchor points, shaders, or texture layers within the core engine, thereby incorporating user-specific elements into the shared visual experience. Curated assets may be cached locally on the HMD or at an edge node prior to compositing to reduce latency and network dependency. The operations of block 1906 may include, without limitation, instantiating dynamic materials, updating texture atlases, aligning personal imagery with spatial anchors, and compositing assets under lighting and occlusion models consistent with the mixed reality scene. In the representative MR-theater environment, block 1906 may include replacing a generic digital billboard with a personalized banner- 91 -107298845 1PATENTAttorney Docket No. 130586-866348 containing a user’s name or image rendered in real time during a performance. In some aspects, block 1906 may further include scene-graph substitution, adaptive level-of-detail management, or neural style-transfer pipelines operable to harmonize personal content with global aesthetics.

[0265] At block 1907, privacy and compliance safeguards may be applied by enforcing policy-based controls and secure-deletion procedures across all personalized data paths, thereby ensuring regulatory and ethical alignment. The operations of block 1907 may include, without limitation, verifying consent scope, encry pting stored residuals, executing retentionwindow expiration, and generating compliance telemetry for audit, enforcing policy-based controls, granular user controls for data-fype selection, real-time revocation mechanisms, and secure-deletion procedures. In the representative MR-theater environment, block 1907 may include automatically deleting audience-derived media after performance completion and issuing verifiable deletion receipts. In some aspects, block 1907 may further include continuous policy-evaluation engines, blockchain-anchored consent proofs, or machine-readable privacy manifests operable to satisfy regional data-protection frameworks and industry^ standards.

[0266] While the aspect of FIG. 19 is described in the context of a representative personalized-content processing pipeline, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 1901-1907 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by collecting telemetry, updating personalization states as conditions evolve, and re-invoking blocks in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 19. but also variations that achieve comparable secure-personalization functionality in different physical, digital, or hybrid mixed reality environments. Subsequent figures (i.e., FIGS. 20-26) provide more detailed depictions of these sub-processes, including secure device integration and consent management, API-level data harvesting, preprocessing and filtering, transmission protocols, rendering modalities, dynamic narrative adaptation, and privacy enforcement. Unless stated otherwise, the methods of FIG. 19 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0267] Having described the generalized personalized content pipeline with reference to FIG. 19, attention is now directed to FIG. 20, which illustrates an example process 2000 for secure device integration and user consent acquisition in accordance with aspects of the present- 92 -107298845 1PATENTAttorney Docket No. 130586-866348 disclosure. As shown, the method may include discrete blocks for detecting a user smartphone, initiating a peer-to-peer connection, prompting for user consent via a device interface, authenticating identity, and generating a secure session token. The arrangement of FIG. 20 is presented in generalized form to demonstrate how consented device pairing and authenticated data exchange may be achieved prior to the harvesting and personalization operations described in subsequent figures. Although described in the context of a representative MR- theater deployment, the method of FIG. 20 may likewise be implemented in enterpnse, educational, or collaborative environments without departing from the scope of the present disclosure. This sub-process establishes the foundation for responsible personalization by ensuring that user data is accessed only after explicit approval, device authentication, and issuance of a secure session token. Comparable mechanisms may be applied to tablets, wearables, or cloud-linked profiles.

[0268] At block 2001, a smartphone may be detected by the mixed reality system through scanning or advertisement discovery, thereby identifying eligible user devices available for pairing. The operations of block 2001 may include, without limitation, broadcasting a discovery beacon from the mixed reality headset, listening for Bluetooth Low Energy (BLE) advertisements, Wi-Fi Direct service announcements, or equivalent signals, and filtering detected devices based on authentication certificates, proximity parameters, or sessiondiscovery protocols. In the representative MR-theater environment, block 2001 may include detecting audience smartphones registered with a performance-specific companion application as they enter the venue or approach a designated pairing zone. In some aspects, block 2001 may further include context-aware filtering, device whitelisting, or broadcast-power calibration algorithms operable to ensure accurate and secure discovery without unauthorized interception.

[0269] At block 2002, a peer-to-peer connection may be initiated between the mixed reality system and the detected smartphone by establishing a secure networking channel, thereby enabling subsequent consent and authentication operations. In some aspects, the system may automatically evaluate available transports and select the protocol offering the most stable throughput and lowest latency under prevailing network conditions. The operations of block 2002 may include, without limitation, initiating a handshake over BLE, Wi-Fi Direct, ultra- wideband, or equivalent short-range transport; negotiating encryption parameters; exchanging digital certificates; and confirming mutual authenticity. In the representative MR-theater environment, block 2002 may include initiating a peer-to-peer session between an audience- 93 -107298845 1PATENTAttorney Docket No. 130586-866348 member's smartphone and the HMD to create an individualized communication path for consent and data transfer. In some aspects, block 2002 may further include edge-node brokering, session-token preallocation, or low-latency handshake optimizations operable to minimize setup time while maintaining cryptographic integrity.

[0270] At block 2003, the user may be prompted for consent via a smartphone user interface, thereby enabling explicit authorization of data access for personalization. The operations of block 2003 may include, without limitation, displaying a permission dialog identifying requested data categories (e.g., photos, playlists, or profde data), presenting contextual information describing the purpose of data use, and recording user responses as digitally signed consent receipts. In the representative MR-theater environment, block 2003 may include presenting a branded consent dialog through the companion application before performance start, allowing users to opt into optional personalization features. In some aspects, block 2003 may further include standardized consent formats such as OAuth authorization screens, dynamic privacy notices, or granular category toggles operable to provide transparency and user control over the scope of data sharing.

[0271] At block 2004, the system may authenticate user identity by verifying credentials, biometric signatures, or other secure tokens, thereby ensuring that the consenting individual is the legitimate owner of the connected device. The operations of block 2004 may include, without limitation, verifying passwords or device passcodes, performing biometric checks such as facial or fingerprint recognition, or validating identify through federated single-sign-on services. In the representative MR-theater environment, block 2004 may include confirming that each smartphone user corresponds to a valid ticket holder or registered participant within the performance network. In some aspects, block 2004 may further include mutualauthentication protocols, two-factor validation, or zero-knowledge proofs operable to provide verifiable identify confirmation without exposing personal credentials.

[0272] At block 2005, a secure session token may be generated and stored by the mixed reality system, thereby establishing a bounded authorization context for subsequent data interactions. The operations of block 2005 may include, without limitation, creating a cryptographically signed token containing user identifiers, consent scope, validity period, and encryption keys, and storing the token in a secure enclave on the device or within a protected memory region of the mixed reality engine. In the representative MR-theater environment, block 2005 may include generating an ephemeral session token linked to the specific- 94 -107298845 1PATENTAttorney Docket No. 130586-866348 performance instance and automatically expiring upon completion of the show. In some aspects, block 2005 may further include token-rotation mechanisms, blockchain-anchored audit records, or distributed key -management services operable to maintain verifiable trust and non-repudiation across the data-sharing lifecycle.

[0273] While the aspect of FIG. 20 is described in the context of a representative secure device integration and consent process, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 2001-2005 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by monitoring device connections, updating authorization states as conditions evolve, and reinvoking blocks in accordance with timing and policy constraints. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 20. but also variations that achieve comparable secure device detection, consent acquisition, and sessiontoken generation in different mixed reality, enterprise, or networked environments. Once a secure and authorized session has been established, the system may proceed to harvest designated categories of personal media and metadata through platform APIs and social integrations, as illustrated in FIG. 21. Unless stated otherwise, the methods of FIG. 20 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0274] Building upon the secure device integration and consent process illustrated in FIG. 20, attention is now directed to FIG. 21, which depicts an example process 2100 for API-level data harvesting and metadata capture in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for requesting access to local media, connecting to linked social accounts, retrieving authorized data, extracting metadata, and assembling a preliminary personalized dataset. The arrangement of FIG. 21 is presented in generalized form to demonstrate how user-approved content may be securely collected and structured for subsequent processing in the mixed reality personalization pipeline. Although described in the context of a representative MR-theater deployment, the method of FIG. 21 may likewise be implemented in enterprise, educational, or social-collaboration contexts without departing from the scope of the present disclosure. In this aspect, the mixed reality system may retrieve personal media and contextual information by leveraging platform-specific application programming interfaces (APIs) and authenticated integrations. Comparable mechanisms may- 95 -107298845 1PATENTAttorney Docket No. 130586-866348 also be employed with other personal data sources, including cloud storage services, wearable devices, or enterprise collaboration platforms.

[0275] At block 2101, access to local media may be requested by invoking platform-level interfaces on the user’s smartphone or connected personal device, thereby allowing the mixed reality system to enumerate and retrieve authorized media assets. The operations of block 2101 may include, without limitation, invoking photo-library or media-service APIs, displaying operating-system permission dialogs, verifying access tokens, and registering callback handlers for approved content retrieval. In some aspects, photo-library APIs provided by the operating system may support album-level or time-based scoping, allowing fine-grained control over the specific content categories made available for personalization. In the representative MR- theater environment, block 2101 may include requesting temporary access to local photos or videos that the audience member has preselected for inclusion in adaptive scenes. In some aspects, block 2101 may further include context-aware permission scopes, read-only sandbox enforcement, or tokenized request identifiers operable to isolate each authorization event and prevent persistent device access.

[0276] At block 2102, connections may be established to linked social accounts by authenticating with user-approved network services, thereby enabling retrieval of public or private content explicitly authorized for inclusion in mixed reality experiences. The operations of block 2102 may include, without limitation, performing OAuth or equivalent authentication flows, exchanging secure access tokens, and establishing session contexts for application programming interface (API) communication with designated social platforms. Such integrations may utilize OAuth protocols that issue time-limited access tokens and support retrieval of user-approved posts, captions, or social stories consistent with the user’s consent parameters. In the representative MR-theater environment, block 2102 may include connecting to a user’s linked social -media account (e.g., an image-sharing or messaging service) to retrieve recent posts or media associated with the performance theme. In some aspects, block 2102 may further include scoped access policies, federated identity confirmation, or encrypted API proxies operable to enforce privacy constraints and comply with data-protection regulations.

[0277] At block 2103, authorized data may be retrieved through authenticated API calls or local-access channels, thereby generating a controlled feed of user-approved assets for personalization. The operations of block 2103 may include, without limitation, quer ing device indexes or remote endpoints for permitted media objects, downloading authorized resources,- 96 -107298845 1PATENTAttorney Docket No. 130586-866348 performing integrity checks, and caching content identifiers for traceability. In some aspects, retrieval operations may be filtered according to token-scoped permissions to ensure that only explicitly authorized categories of content are harvested. In the representative MR-theater environment, block 2103 may include downloading approved images, text captions, or usergenerated clips from both local and cloud sources for later inclusion in adaptive rendering sequences. In some aspects, block 2103 may further include adaptive bandwidth management, data deduplication, or checksum validation operable to ensure completeness and authenticity of the retrieved dataset.

[0278] At block 2104, metadata may be extracted from each retrieved asset, thereby generating contextual information for organizing and interpreting user content. The operations of block 2104 may include, without limitation, parsing file headers and embedded metadata fields (e.g., EXIF, IPTC, or XMP formats), extracting timestamps, geolocation coordinates, device identifiers, and user-supplied captions, and normalizing metadata values into standardized schema representations. Metadata may further include device-generated attributes such as focal length, exposure settings, or color profiles, which can assist in matching personal media to lighting and rendering conditions within the MR scene. In the representative MR- theater environment, block 2104 may include extracting keywords or timestamps from audience photos to align them with thematic scenes or narrative segments. In some aspects, block 2104 may further include machine-learning classifiers for sentiment analysis, object detection, or contextual tagging operable to derive higher-order features from raw' metadata, enabling more nuanced personalization of subsequent rendering operations.

[0279] At block 2105, a preliminary personalized dataset may be assembled by aggregating the retrieved media and extracted metadata into a unified, structured representation suitable for downstream processing in the mixed reality engine. The operations of block 2105 may include, without limitation, creating data bundles that pair media objects with contextual descriptors, compressing and encrypting the resulting dataset, and transmitting the packaged payload to the personalization subsystem of the mixed reality engine. In the representative MR-theater environment, block 2105 may include assembling a per-user dataset including photos, captions, and thematic indicators that will later be filtered and rendered as adaptive overlays or textures during live performance. In some aspects, block 2105 may further include incremental dataset versioning, change tracking, or schema validation pipelines operable to ensure that the personalized data remains consistent, verifiable, and compliant with consented parameters.- 97 -107298845 1PATENTAttorney Docket No. 130586-866348This dataset may subsequently undergo downstream relevance scoring, thematic detection, and emotional-cue analysis to support adaptive narrative alignment in later processing stages.

[0280] While the aspect of FIG. 21 is described in the context of a representative API-level data-harvesting and metadata-capture process, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 2101-2105 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by synchronizing API access tokens, monitoring data integrity, and re-invoking data-harvesting blocks as necessary to refresh user content. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 21, but also variations that achieve comparable secure data collection and metadata extraction in different mixed reality , mobile, or networked environments. The subsequent figure, FIG. 22. details how this dataset may undergo preprocessing and intelligent filtering to ensure that only curated, meaningful content is incorporated into the mixed reality7environment. Unless stated otherwise, the methods of FIG. 21 may be implemented by one or more processors executing instructions stored on non- transitory computer-readable media.

[0281] Building upon the dataset assembly operations described in FIG. 21, attention is now directed to FIG. 22, which illustrates an example process 2200 for preprocessing and intelligent filtering of user-specific data in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for applying recency and content-type filters, running machine-learning classifiers, scoring the relevance of candidate assets, selecting assets with the highest relevance scores, and outputting a personalized content set. The arrangement of FIG. 22 is presented in generalized form to demonstrate how candidate media and metadata gathered from consented sources may be refined into a curated set suitable for adaptive rendering. Although described in the context of a representative MR-theater deployment, the method of FIG. 22 may likewise be implemented in enterprise, educational, or collaborative settings without departing from the scope of the present disclosure. This refinement stage may reduce computational overhead, safeguard privacy by limiting propagation of non-essential personal data, and improve overall system performance. Although primarily described with local smartphone or MR-system preprocessing, comparable blocks may be distributed across edge servers or cloud infrastructures depending on deployment architecture.- 98 -107298845 1PATENTAttorney Docket No. 130586-866348

[0282] At block 2201. recency and content-type filters may be applied to the preliminary personalized dataset, thereby eliminating outdated or irrelevant entries prior to advanced processing. The operations of block 2201 may include, without limitation, filtering assets according to timestamps, geolocation ranges, file types, or media-format attributes and, in some aspects, restricting processing to user-approved categories such as family photos or travelalbum images, and discarding entries that fall outside consented temporal or categorical boundaries. In the representative MR-theater environment, block 2201 may include filtering audience photos or posts to include only recent materials relevant to the current production theme. In some aspects, block 2201 may further include rule-based heuristics, user-defined constraints, or adaptive threshold functions operable to dynamically adjust filtering criteria based on dataset density or narrative context.

[0283] At block 2202, machine-learning classifiers may be executed to analyze the filtered dataset, thereby identifying emotional, thematic, or contextual cues associated with each asset. The operations of block 2202 may include, without limitation, applying convolutional or transformer-based neural networks for image recognition, natural-language-processing models for caption interpretation, and multimodal-fusion algorithms that combine visual and textual features. Examples include detecting faces, landmarks, or other salient objects in images and performing sentiment analysis on captions or comments to assess emotional tone, thereby supporting thematic alignment with narrative contexts. In the representative MR-theater environment, block 2202 may include running pre-trained classifiers to detect mood indicators (e.g., joyful, reflective, energetic) or narrative motifs aligning with current scenes. In some aspects, block 2202 may further include on-device inference optimization, federated-learning updates, or domain-adaptation layers operable to tailor classifier behavior to performancespecific aesthetics.

[0284] At block 2203, a relevance score may be computed for each candidate asset based on classifier outputs and contextual weighting factors, thereby quantifying its suitability for inclusion in the personalized content stream. The operations of block 2203 may include, without limitation, computing weighted averages across detected features, combining recency, emotional tone, and thematic alignment metrics, and normalizing scores across all candidates. In the representative MR-theater environment, block 2203 may include assigning higher weights to assets exhibiting visual motifs or textual descriptors directly related to the ongoing narrative segment. In some aspects, block 2203 may further include reinforcement-learning- 99 -107298845 1PATENTAttorney Docket No. 130586-866348 feedback loops, Bayesian relevance estimators, or ensemble-scoring architectures operable to refine ranking accuracy across multiple performances. Relevance factors may include frequency of appearance, semantic similarity to production themes, and inferred emotional resonance. In certain aspects, scoring parameters may be user-configurable and may adapt over time using audience engagement signals captured during prior performances.

[0285] At block 2204, assets possessing the highest relevance scores may be selected to form a refined subset of user-specific content, thereby optimizing personalization quality while minimizing processing overhead. The operations of block 2204 may include, without limitation, sorting candidate entries by relevance score, pruning low-ranked items, balancing content diversity across categories, and applying quota constraints to maintain consistent data volume per user. In the representative MR-theater environment, block 2204 may include selecting a limited number of images, clips, or textual elements that best represent the user's emotional or narrative alignment with the performance. In some aspects, block 2204 may further include diversity-aware selection heuristics, cross-user normalization, or fairnessweighting mechanisms operable to ensure equitable representation across the audience base. In practice, the curated collection may represent a fraction of the original dataset, thereby lowering transmission load and storage requirements while preserving narrative coherence.

[0286] At block 2205, a personalized content set may be output to the downstream transmission subsystem for delivery to the mixed reality engine, thereby concluding the preprocessing stage. The operations of block 2205 may include, without limitation, packaging the curated content set into encrypted payloads, annotating assets with relevance-score metadata, and storing or transmitting the resulting bundle for integration into the rendering pipeline. In the representative MR-theater environment, block 2205 may include forwarding the user-specific content package to an edge server responsible for scene-level personalization. In some aspects, block 2205 may further include content-validation checks, consent-scope reverification, or metadata-signing operations operable to maintain continuity and traceability across processing stages.

[0287] While the aspect of FIG. 22 is described in the context of a representative preprocessing and intelligent-filtering process, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 2201-2205 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence- 100 -107298845 1PATENTAttorney Docket No. 130586-866348 by periodically re-evaluating relevance metrics, updating classifier models, and re-invoking filtering procedures as user datasets evolve. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 22, but also variations that achieve comparable intelligent-filtering and personalization-refinement functionality in different mixed reality, enterprise, or data-processing environments. As shown in FIG. 23, the resulting curated content set may then be transmitted securely to the mixed reality rendering infrastructure for integration into the live experience. Unless stated otherwise, the methods of FIG. 22 may be implemented by one or more processors executing instructions stored on non- transitory computer-readable media.

[0288] Building upon the preprocessing and intelligent filtering operations described in FIG. 22, attention is now directed to FIG. 23, which illustrates an example process 2300 for data transmission and system integration in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for encrypting the curated dataset, transmitting the dataset via a selected channel, verifying the integrity of the received dataset, caching the data locally, and routing it to the content-integration module. The arrangement of FIG. 23 is presented in generalized form to demonstrate how filtered and personalized content may be securely delivered from preprocessing subsystems to rendering pipelines within a mixed reality environment. Although described in the context of a representative MR-theater deployment, the method of FIG. 23 may likewise be implemented in enterprise, industrial, or collaborative network infrastructures without departing from the scope of the present disclosure. In certain implementations, the process may encompass smartphone-to-HMD or smartphone-to-edge data transfer, as well as cloud-based delivery or multi-venue synchronization scenarios. These transmission pathways are designed to presen e data integrity while minimizing latency throughout the mixed reality infrastructure.

[0289] At block 2301, the curated dataset may be encrypted by the transmitting subsystem prior to network transfer, thereby ensuring confidentiality and tamper resistance during transport. The operations of block 2301 may include, without limitation, applying symmetric or asymmetric encryption algorithms such as AES-256 or RSA-4096, generating ephemeral encryption keys, and packaging associated metadata with cryptographic signatures for validation. Encryption protocols may include Transport Layer Security (TLS 1.3), Datagram TLS, or equivalent end-to-end cryptographic standards integrated with the payload-level encryption mechanisms described herein. In the representative MR-theater environment, block- 101 -107298845 1PATENTAttorney Docket No. 130586-8663482301 may include encrypting audience-specific content bundles before transmission to venue- local edge servers responsible for rendering orchestration. In some aspects, block 2301 may further include hybrid encryption combining public-key exchange with symmetric-key payload encry ption, key-rotation mechanisms, or integration with secure hardware modules operable to maintain FIPS-compliant data-protection standards.

[0290] At block 2302, the encry pted dataset may be transmitted via a selected communication channel based on network conditions and deployment topology, which may include direct transfer to an audience member’s HMD. routing through a local edge node within the theater, or relaying via a centralized mixed reality7server for multi-audience coordination, thereby ensuring reliable and efficient delivery'. The operations of block 2302 may include, without limitation, selecting between wired (e.g., Ethernet) and wireless (e.g., Wi-Fi 6, 5G, or optical wireless) transports, establishing session protocols such as HTTPS, QUIC, or gRPC, and monitoring throughput or latency metrics for dynamic channel selection. In some aspects, adaptive path-selection algorithms may evaluate multiple available routes and choose the channel that minimizes round- trip latency while maintaining reliability7. In the representative MR-theater environment, block 2302 may include routing encrypted audience-specific data streams to local edge nodes that feed multiple HMDs in real time. In some aspects, block 2302 may further include adaptive bit-rate control, packet-loss mitigation, or multipath transport mechanisms operable to sustain low-latency synchronization with ongoing performances.

[0291] At block 2303, the integrity of the received dataset may be verified by the receiving subsystem to confirm that transmitted content has not been corrupted or altered in transit. The operations of block 2303 may include, without limitation, computing and comparing cryptographic hash values (e.g.. SHA-256 or SHA-3), validating digital signatures, verifying certificate chains, and confirming payload length and checksum consistency. In the representative MR-theater environment, block 2303 may include validating integrity' of audience-personalization packages received by edge-rendering servers before injecting them into the real-time performance stream. In some aspects, block 2303 may7further include redundant verification at multiple layers of the data pipeline, audit logging of validation results, or failure-handling routines operable to trigger retransmission or error isolation upon mismatch detection. Failed integrity' checks may trigger automatic retransmission, fallback to redundant nodes, or error-recovery routines to sustain continuous operation.- 102 -107298845 1PATENTAttorney Docket No. 130586-866348

[0292] At block 2304, verified data may be cached locally within the receiving system to facilitate low-latency access during subsequent rendering operations, thereby improving runtime performance and resilience to transient connectivity issues. The operations of block 2304 may include, without limitation, writing the verified dataset to secure edge storage, indexing cached items with metadata keys, and applying eviction policies based on usage frequency or expiration times. In certain aspects, caching may also occur directly within an HMD’s onboard storage to ensure localized availability of personalized assets during playback. In the representative MR-theater environment, block 2304 may include caching encrypted personalization data at the theater’ s local server cluster to ensure uninterrupted playback should the upstream connection fluctuate. Cache-management policies may include least-recently- used (LRU) eviction, time-based expiration, or adaptive memory-allocation strategies optimized for real-time rendering throughput. In some aspects, block 2304 may further include distributed cache replication, memory-mapped I / O for rapid retrieval, or blockchain-anchored cache-verification entries operable to guarantee integrity across redundant nodes.

[0293] At block 2305, the cached and verified data may be routed to the content-integration module, thereby initiating the final stage of system integration before mixed reality rendering. The operations of block 2305 may include, without limitation, passing data references to rendering schedulers, triggering content-mapping routines that align personalized assets with spatial anchors, and notifying synchronization controllers responsible for scene timing. In the representative MR-theater environment, block 2305 may include routing audience- personalized datasets into the core rendering engine, where each user's individualized content is composited with live-performance imagery. This integration may encompass multiple content modalities, including two-dimensional overlays, volumetric holographic projections, and interactive virtual props synchronized with live stage cues and digital lighting effects. In some aspects, block 2305 may further include load-balancing algorithms, dynamic queue management, or microsenrice-based routing architectures operable to maintain deterministic latency and frame alignment during real-time performance execution.

[0294] While the aspect of FIG. 23 is described in the context of a representative data- transmission and system-integration process, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 2301-2305 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence- 103 -107298845 1PATENTAttorney Docket No. 130586-866348 by monitoring transmission status, re-verifying integrity during caching cycles, and reinvoking routing operations as new personalization data becomes available. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 23, but also variations that achieve comparable secure-transmission and integration functionality in different mixed reality7, networked, or cloud-based environments. The subsequent figure, FIG. 24. details how the curated and transmitted content may be rendered across multiple modalities within the mixed reality environment, including overlays, holograms, interactive elements, and dynamic scene backgrounds. Unless stated otherwise, the methods of FIG. 23 may be implemented by one or more processors executing instructions stored on non-transitoiy computer-readable media.

[0295] Building upon the secure data-transmission and integration operations described in FIG. 23, attention is now directed to FIG. 24, which illustrates an example process 2400 for rendering personalized content across multiple modalities within a mixed reality environment in accordance with aspects of the present disclosure. As shown, the method may include discrete blocks for overlaying personal media into background layers, projecting personalized content as holographic objects, inserting personalized interactive elements, transforming scene backgrounds with personalized motifs, and synchronizing rendering across all HMDs. The arrangement of FIG. 24 is presented in generalized form to demonstrate how user-specific content may be spatially, visually, and interactively integrated into a shared MR environment while maintaining synchronization across distributed rendering systems. Although described in the context of an MR-theater deployment, the method of FIG. 24 may likewise be implemented in enterprise, educational, collaborative, or entertainment contexts without departing from the scope of the present disclosure. In this aspect, the mixed reality system transforms curated user data into visual and interactive elements that may appear as overlays, holograms, interactive props, or dynamic backgrounds, each synchronized with the shared narrative experience.

[0296] At block 2401, personal media may be overlaid into background layers of the mixed reality scene, which may appear as framed media, floating panels, or environmental textures projected behind live stage elements, thereby establishing context-specific visual backdrops that incorporate user-approved content. The operations of block 2401 may include, without limitation, compositing two-dimensional images or textures within environment-mapped backgrounds, adjusting brightness and color balance to maintain global scene coherence, and- 104 -107298845 1PATENTAttorney Docket No. 130586-866348 scaling assets according to spatial constraints or artistic direction. In the representative MR- theater environment, block 2401 may include blending an audience member’s personal photographs or videos into the virtual stage panorama to provide individualized scenic context. In some aspects, block 2401 may further include color-grading pipelines, shader-based blending, or parallax-aware projection techniques operable to ensure seamless integration of personal imagery into multi-depth backgrounds.

[0297] At block 2402, personalized content may be projected as holographic objects within the mixed reality scene, thereby enabling volumetric visualization of user-specific assets. The operations of block 2402 may include, without limitation, generating three-dimensional meshes or billboards from personal images, applying depth mapping and occlusion-aware rendering, and aligning holographic objects with real-world spatial anchors. Holographic projections may take the form of volumetric renderings or three-dimensional floating images that are spatially anchored to stage markers or actor positions to ensure alignment and immersion. In the representative MR-theater environment, block 2402 may include projecting audience- submitted visual elements — such as symbols, photos, or avatars — onto volumetric holographic displays surrounding the stage. In some aspects, block 2402 may further include light-field rendering, adaptive holographic scaling, or physics-based motion integration operable to ensure that projected personalized objects respond realistically to lighting and spatial dynamics of the performance environment.

[0298] At block 2403, personalized interactive elements may be inserted into the scene, thereby allowing real-time audience engagement and participation through mixed reality interfaces. The operations of block 2403 may include, without limitation, spawning interactive nodes or props linked to the user’s consented data, configuring touch or gesture-based input handlers, and establishing event-driven connections between audience interactions and performance responses. In the representative MR-theater environment, block 2403 may include inserting interactive holographic props — such as banners, emblems, or character tokens — that audience members can manipulate using gestures or handheld devices. In some aspects, block 2403 may further include predictive input modeling, low-latency feedback loops, or networked interaction protocols operable to synchronize multi-user interactions across multiple HMDs. These interactive elements may serve as narrative devices that draw each user into participatory engagement with the unfolding performance.- 105 -107298845 1PATENTAttorney Docket No. 130586-866348

[0299] At block 2404, scene backgrounds may be transformed with personalized motifs, thereby adapting environmental features of the mixed reality experience to reflect individual audience themes or preferences. The operations of block 2404 may include, without limitation, parameterizing shaders, textures, or environmental lighting based on personalization metadata, updating scene graph parameters dynamically, and mapping motif patterns derived from user- supplied imagery. In the representative MR-theater environment, block 2404 may include dynamically transforming digital set pieces — such as sky domes, stage surfaces, or virtual banners — to reflect thematic motifs extracted from audience photos or social feeds. In some aspects, block 2404 may further include procedural generation algorithms, motif-clustering logic, or adaptive lighting controllers operable to harmonize per-user transformations with overall scene continuity. For example, a virtual skybox may shift to resemble a user’s vacation photo, or digital stage scenery may adapt to display familiar landmarks or motifs derived from the curated dataset.

[0300] At block 2405, rendering may be synchronized across all HMDs, thereby ensuring temporal and visual consistency among users sharing the mixed reality experience. The operations of block 2405 may include, without limitation, distributing frame-timing signals through a synchronization bus, broadcasting scene-update deltas, and compensating for network latency using predictive frame extrapolation. In the representative MR-theater environment, block 2405 may include synchronizing frame outputs between performer and audience HMDs such that personalized overlays, holographic projections, and interactive responses appear simultaneously for all participants. In some aspects, block 2405 may further include distributed-rendering architectures, precision timestamp alignment, or clocksynchronization protocols operable to achieve sub-frame timing uniformity across heterogeneous hardware. While each user may perceive distinct overlays, holograms, or background variations, synchronization mechanisms preserve consistent timing, spatial alignment, and narrative pacing across the collective audience.

[0301] While the aspect of FIG. 24 is described in the context of a representative renderingmodality process, it will be understood that the illustrated arrangement is not limiting. The blocks shown — including 2401-2405 — may be rearranged, subdivided, omitted, combined, or supplemented with additional blocks without departing from the scope of the present disclosure. In continued operation, the method may maintain coherence by dynamically adapting rendered elements to changing scene conditions, recalibrating synchronization clocks.- 106 -107298845 1PATENTAttorney Docket No. 130586-866348 and reprojecting user content in accordance with performance choreography. Accordingly, the disclosure encompasses not only the particular sequencing of functions depicted in FIG. 24, but also variations that achieve comparable personalized rendering and synchronization functionality in different mixed reality, distributed, or immersive environments. The subsequent figure, FIG. 25, describes how these personalized renderings may drive dynamic narrative adaptation, enabling story pathways and visual motifs to adjust responsively to userspecific datasets. Unless stated otherwise, the methods of FIG. 24 may be implemented by one or more processors executing instructions stored on non-transitory computer-readable media.

[0302] Building upon the rendering modalities described in FIG. 24, attention is now directed to FIG. 25, which illustrates an example process 2500 for dynamic narrative adaptation in accordance with aspects of the present disclosure. As show n, the method may include discrete blocks for inputting the curated personal dataset into the story engine, analyzing thematic and emotional relevance to narrative nodes, selecting adaptive branches or motifs based on user data, rendering modified scenes to the user’s HMD, and maintaining global narrative coherence across all audience members. The arrangement of FIG. 25 is presented in generalized form to demonstrate how the mixed reality story engine may responsively tailor narrative progression and emotional tone to user-specific data while preserving overall performance cohesion. Although described in the context of a representative MR-theater system, the method of FIG. 25 may likewise be implemented in interactive entertainment, training simulations, or collaborative narrative environments without departing from the scope of the present disclosure. In this aspect, curated personal content may influence story progression itself, with overlays, holograms, and props informing adaptive narrative choices while overall coherence is preserved.

[0303] At block 2501, the curated personal dataset may be input into the story engine, thereby providing the narrative subsystem with user-specific contextual information...

Claims

PATENTAttorney Docket No. 130586-866348CLAIMSWHAT IS CLAIMED IS:

1. A computer implemented method for calculating an effectiveness score based on biometric sensor data, the method comprising: obtaining first sensor measurements from one or more biometric sensors during a first time period; generating a first set of features from the first sensor measurements; deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant; providing, to the participant, a content sequence comprising a plurality of content segments, each content segment associated with a label identifying a level of emotional intensity represented in the content segment; obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors; generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments; providing the baseline biometric profile and the second set of features to a machinelearning model configured to output a physiological response score; and calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence.

2. The computer implemented method of claim 1, wherein the one or more biometric sensors comprise at least one of a heart-rate monitor, galvanic skin response sensor, eye tracking camera, or facial expression recognition system.

3. The computer implemented method of claim 1, wherein each content segment corresponds to a scene of a mixed reality, augmented reality, or virtual reality presentation.- 175 -107298845.1PATENTAttorney Docket No. 130586-8663484. The computer implemented method of claim 1, wherein the labels are generated from prior testing sessions or annotated training data defining target engagement levels.

5. The computer implemented method of claim 1, wherein the machine-learning model comprises a neural network model trained to predict the physiological response score from the baseline biometric profile and the second set of features.

6. The computer implemented method of claim 1, further comprising adjusting at least one presentation parameter of a subsequent content segment based on the calculated effectiveness score.

7. The computer implemented method of claim 1, wherein the effectiveness score is transmitted to an analytics server for aggregation across multiple participants or sessions.

8. The computer implemented method of claim 1, wherein the effectiveness score is displayed on a control interface to provide real-time feedback to an operator or automated orchestration system.

9. A virtual reality system comprising one or more memories and one or more processors coupled to the one or more memories and configured to perform operations comprising: obtaining first sensor measurements from one or more biometric sensors during a first time period; generating a first set of features from the first sensor measurements; deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant; providing, to the participant, a content sequence comprising a plurality of content segments, each content segment associated with a label identifying a level of emotional intensity represented in the content segment; obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors;- 176 -107298845.1PATENTAttorney Docket No. 130586-866348 generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments; providing the baseline biometric profile and the second set of features to a machinelearning model configured to output a physiological response score; and calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence.

10. The virtual reality system of claim 9, wherein the one or more biometric sensors comprise at least one of a heart-rate monitor, galvanic skin response sensor, eye tracking camera, or facial expression recognition system.

11. The virtual reality system of claim 9, wherein each content segment corresponds to a scene of a mixed reality, augmented reality, or virtual reality presentation.

12. The virtual reality system of claim 9, wherein the labels are generated from prior testing sessions or annotated training data defining target engagement levels.

13. The virtual reality system of claim 9, wherein the machine-learning model comprises a neural network model trained to predict the physiological response score from the baseline biometric profile and the second set of features.

14. The virtual reality system of claim 9, further comprising adjusting at least one presentation parameter of a subsequent content segment based on the calculated effectiveness score.

15. The virtual reality system of claim 9, wherein the effectiveness score is transmitted to an analytics server for aggregation across multiple participants or sessions.

16. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a system to perform a method for generating an experienceeffectiveness score, the method comprising:- 177 -107298845.1PATENTAttorney Docket No. 130586-866348 obtaining first sensor measurements from one or more biometric sensors during a first time period; generating a first set of features from the first sensor measurements; deriving, from the first set of features, a baseline biometric profile representative of an initial physiological state of a participant; providing, to the participant, a content sequence comprising a plurality of content segments, each content segment associated with a label identifying a level of emotional intensity represented in the content segment; obtaining, for a time period corresponding to presentation of at least one of the content segments, second sensor measurements from the one or more biometric sensors; generating, from the second sensor measurements, a second set of features corresponding to a physiological response to the at least one of the content segments; providing the baseline biometric profile and the second set of features to a machinelearning model configured to output a physiological response score; and calculating, based on the physiological response score, an effectiveness score indicative of participant engagement with the content sequence.

17. The non-transitoiy computer-readable medium of claim 16, wherein the one or more biometric sensors comprise at least one of a heart-rate monitor, galvanic skin response sensor, eye tracking camera, or facial expression recognition system.

18. The non-transitory computer-readable medium of claim 16, wherein each content segment corresponds to a scene of a mixed reality, augmented reality, or virtual reality presentation.

19. The non-transitory computer-readable medium of claim 16, wherein the labels are generated from prior testing sessions or annotated training data defining target engagement levels.

20. The non-transitory computer-readable medium of claim 16, wherein the machine-learning model comprises a neural network model trained to predict the physiological response score from the baseline biometric profile and the second set of features.- 178 -107298845.1

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