3657results about "Details involving graphical user interface" patented technology

A system and method for creating complex, immersive, and interactive digital content is disclosed. The system integrates advanced artificial intelligence, multi-modal input processing, cloud-based shared environments, and immersive hardware to generate, optimize, and deliver rich interactive experiences. The platform supports content mashups, custom scenario generation, and adaptive AI behaviors, enabling the creation of unique and engaging digital environments across various media formats.

An example operation may include at least one of receiving, via a user interface of a device, an activation input from a user to initiate a session, capturing, by a camera of the device, a scan of a body of the user, wherein the capturing comprises recording at least one image and / or at least one video of the user, processing the at least one image and / or video to generate a three- dimensional model of the user comprising measurements and contours of the body, retrieving, from a database, at least one clothing item associated with the user, the at least one clothing item comprising dimensional attributes and texture attributes, rendering, by a graphics processing unit, the at least one clothing item onto the three-dimensional model to generate a visual representation, wherein the rendering simulates draping behavior, movement, and light interaction of the at least one clothing item relative to the three-dimensional model, and displaying, on the user interface, an interactive visualization comprising the visual representation of the three-dimensional model with the at least one clothing item from multiple viewing angles.

In implementation of techniques for three-dimensional reconstructions based on Gaussian primitives, a computing device implements a reconstruction system to receive a first digital image depicting an object from a first angle and a second digital image depicting the object from a second angle. The reconstruction system segments the first digital image and the second digital image into patches. The reconstruction system then generates, using a machine learning model, three-dimensional Gaussian primitives that predict parameters of points of the object in a three-dimensional space that correspond on a per-pixel basis to pixels of the patches. The reconstruction system then forms a three-dimensional reconstruction of the object for display in a user interface by merging the three-dimensional Gaussian primitives.

There is provided a method and a system for generating a 3D parametric mesh of an anatomical structure of a patient for storing multi-domain data therein. A plurality of anatomical segments having been obtained from segmentation of a set of images of a patient are received. A 3D mesh comprising a plurality of concentric 3D mesh layers is received, where each concentric 3D mesh layer includes a same predetermined number of nodes. A set of nodes in the 3D mesh corresponding to a respective anatomical segment is determined to obtain a respective correspondence rule therebetween. The set of nodes is encoded with a set of features from the respective anatomical segment by using the correspondence rule to obtain a 3D parametric mesh, each node of the set of nodes in the 3D parametric mesh being associated with a respective plurality of feature channels comprises the set of features.

A system for computer assisted navigation during surgery includes a computer platform that operates to register a target surgical area of a patient. In certain cases, a process includes: obtaining a pre-op CT image of a pelvic region of a patient and intra-operatively obtaining a point cloud data about the pelvic region with a navigated instrument, generating a 3D bone model which excludes non-targeted area such as a femur, and then merging the 3D bone model to the point cloud to register the target surgical area.

A data processing system implements constructing a first prompt including a font mask of a reference character (RC) and a style prompt, sending the first prompt to a text2image model to iteratively generate salient content and concentrate the salient content within the font mask of RC as a first image of RC; concatenating two of the first images as a second image; generating a combined font mask of the font mask of RC and a font mask of a target character (TC); constructing a second prompt including the combined font mask and the second image, sending the second prompt to the model to iteratively generate salient content and in-paint the salient content within a half of the combined font mask as a third image of RC and TC; cropping a styled TC image from the third image using the font mask of TC; providing the styled TC image to a client device.

A system for computer assisted navigation during surgery includes a computer platform that operates to register a target surgical area of a patient. In certain cases, a process includes: obtaining a pre-op CT image of a pelvic region of a patient and intra-operatively obtaining a point cloud data about the pelvic region with a navigated instrument, generating a 3D bone model which excludes non-targeted area such as a femur, and then merging the 3D bone model to the point cloud to register the target surgical area.

Disclosed herein is an extended reality system, and associated techniques, whereby personalized usage data of a user in one or more extended reality environments over a period of time can be collected and provided to a predictive model to determine optimal shortcut assignments for presentation to and subsequent use by the user. Determining the optimal shortcut assignments can involve estimating a plurality of interaction times for the user in the one or more extended reality environments, generating an optimized graphical user interface within the one or more extended reality environments with the optimal shortcut assignments reflected in the optimized graphical user interface, and rendering the optimized graphical user interface in the one or more extended reality environments to the user. The system may collect additional personalized usage data and periodically update the optimal shortcut assignments based on ongoing use of the system by the user.

One or more computer systems switch a representation of a first content item at a docked position in an environment with a representation of a second content item in the environment in response to input, switch from displaying a first environment to displaying a second environment in response to input while displaying a representation of a first content item at a docked position, detect and respond to events corresponding to requests to move virtual content in an environment, detect and respond to events corresponding to requests to transition a mode of display of virtual content in the environment, display a first framing element concurrently with a representation of a content item having different degrees of transparency in response to detecting an input, and / or facilitate docking of a content item in an environment based on an input, and / or determine clusters of virtual objects and restore virtual objects after a reboot event.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for content generation are provided. One of the methods includes receiving one or more user input identifying information associated with one or more media elements and one or more characteristics of the video to be generated; and generating video content based on the received one or more user inputs, the generating comprising: identifying assets to include in the video, the assets including an avatar, generating a script for the video, and assembling a video layout.

The invention belongs to the technical field of three-dimensional reconstruction, and discloses a three-dimensional digital human generation method and system capable of voice interaction. According to the invention, brand new speaking audios in different languages are automatically generated according to different languages of the input target text and the sampled human voice audios; the sequential stability and detail reduction capability of three-dimensional human motion are guaranteed by using multi-model joint estimation and a sequential loss function, and facial expression details and hand postures in the image can be accurately estimated. After the high-precision three-dimensional human body model is obtained through estimation, human body action and expression generation is carried out based on voice driving, accurate synchronization of actions and expressions generated through voice is achieved, and facial expression movement and body posture movement, namely a whole-body three-dimensional human body model, conforming to brand-new speaking audio are accurately generated; and finally, rendering the whole-body three-dimensional human body model into a real digital human capable of voice interaction by using a three-dimensional neural rendering model. According to the invention, the realization of single person picture input, high-precision three-dimensional digital person generation and voice interaction is facilitated.

A soundbar for medical monitoring which may comprise a speaker, a sensor, and a hardware processor. The speaker can be configured to emit audio signals. The sensor can be configured to obtain sensor data relating to a physiology of a subject. The sensor can include a camera and the sensor data can include image data. The hardware processor can be configured to access the sensor data and determine a health status of the subject based on at least the sensor data.

A system for computer assisted navigation during surgery includes a computer platform that operates to register a target surgical area of a patient. In certain cases, a process includes: obtaining a pre-op CT image of a pelvic region of a patient and intra-operatively obtaining a point cloud data about the pelvic region with a navigated instrument, generating a 3D bone model which excludes non-targeted area such as a femur, and then merging the 3D bone model to the point cloud to register the target surgical area.

In some embodiments, an electronic device generates an automatically-generated visual media using one or more recognized concepts extracted from a prompt inputted by a user. The recognized concepts include personalized template subjects and / or prompt suggestions. While displaying the user interface including the recognized concepts, the electronic device receives one or more inputs to modify the recognized concepts. The electronic device generates multiple variants of the automatically-generated visual content using the one or more recognized concepts. The electronic device adds an automatically-generated visual content to a content entry field of an application, different than the automatically-generated visual media application, without opening the automatically-generated visual media application. The electronic device applies a visual effect to content that is generated using an artificial intelligence model. The electronic device displays visual information corresponding to an artificial intelligence model. The electronic device displays an animation including displaying a user interface with high dynamic range luminance.

A system for computer assisted navigation during surgery includes a computer platform that operates to register a target surgical area of a patient. In certain cases, a process includes: obtaining a pre-op CT image of a pelvic region of a patient and intra-operatively obtaining a point cloud data about the pelvic region with a navigated instrument, generating a 3D bone model which excludes non-targeted area such as a femur, and then merging the 3D bone model to the point cloud to register the target surgical area.

The present invention provides a system and method for generating proposals for infrastructure modalities, such as electrical substations, using advanced artificial intelligence. It includes an input interface for data collection, a lightweight generative or rendering pipeline for creating preliminary 2D designs, and a generative model selected from diffusion, transformer-based, GAN or other architectures for refining these into detailed 3D models and generating preliminary designs. The system evaluates designs against predefined criteria to ensure compliance and feasibility. Supported by a cloud-based infrastructure for robust data processing and integration with third-party services, this system enhances the efficiency, accuracy, and compliance of modality planning and proposal generation.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

Example implementations are directed to recapturing or realigning a room or scene in an artificial reality (XR) environment as a three dimensional (3D) space. To initially capture a room, a user manually annotates, using an XR system, one or more walls around the XR system. The XR system then aligns or localizes itself relative to the room. Once a room is captured and stored, and the user in the future enters the room again, the XR system may not be able to align itself in the room due to, for example, lighting conditions. Rather than require the user to manually recapture every wall captured during the initial room capture, the XR system can select one wall for recapture and, after receiving an annotation or marking of the one wall from the user, use the selection to realign the XR system relative to the room.

Provided herein are imaging systems for a patient including an imaging probe and an imaging assembly. The imaging probe includes an elongate shaft with a rotatable optical core positioned within a lumen of the elongate shaft. The imaging probe further includes an optical assembly to direct light to tissue to be imaged and to collect reflected light from the tissue to be imaged. The system further includes an imaging assembly optically coupled to the imaging probe. The system further includes a processing unit with a processor and a memory coupled to the processor, and the memory stores instructions for the processor to perform an algorithm. The system records image data based on the reflected light collected by the optical assembly, such that the image data comprises data collected from a segment of a blood vessel during a pullback procedure. The algorithm can analyze the image data.

A method or system for implementing a machine learning pipeline on a chipset comprising a plurality of hardware compute elements. The system accesses a hardware-agnostic functional description of the machine learning pipeline, wherein the description specifies a plurality of functional modules, including at least one machine learning model. Hardware specifications of the chipset are accessed to identify the available hardware compute elements. Based on the hardware specifications, the functional modules are synthesized into a plurality of interconnected executable components configured to execute on at least two different hardware compute elements. An implementation package is generated, comprising the executable components and metadata describing interconnections between them. The implementation package is then deployed to the chipset, where the executable components are executed by the identified hardware compute elements.

A symbolic neuroadaptive control system is disclosed for real-time arbitration, consent, and ethical modulation of artificial intelligence agents operating in wearable computing environments. The system integrates multimodal biometric telemetry—including high-resolution EEG signals—with a symbolic kernel that performs logic-driven arbitration over cognitive, emotional, and ethical states. Using Coq-verified invariants and zero-knowledge biometric consent tokens, the system constructs a deterministic symbolic execution graph, gating AI outputs based on internal user states such as trauma, stress, or intentionality. Unlike conventional black-box BCI models, the invention routes EEG-inferred affective-symbolic tokens through a formal ethics layer that enforces real-time interrupt control, utility bounding, and trust verification. The kernel enables AGI systems to defer or modify behavior based on user-state alignment, granting sovereign agency over all downstream actions. This neuro-symbolic architecture redefines the interface between human cognition and intelligent machines, enabling emotionally conscious, morally verifiable, and symbolically transparent AI governance in dynamic, high-stakes contexts.The present invention relates to artificial intelligence and neurotechnology, specifically to a real-time, neuro-symbolic operating system kernel that converts electroencephalography (EEG) signals into structured symbolic data for use in emotional cognition, ethical prioritization, autonomous agent dispatch, and real-time telecommunications routing. The invention bridges brain-computer interface (BCI) inputs with symbolic AI architectures to enable ethically aligned machine response during cognitively or emotionally intense events.

This disclosure relates to techniques for generating and utilizing custom stickers in a digital communication environment. A technique involves receiving a text-based message input during a chat session and using a generative language model (e.g., a Large Language Model, or LLM) to create a text prompt. This prompt is then used by a generative image model to produce a custom sticker. The generated sticker is sent to a client device where it is displayed in a sticker tray alongside other selectable stickers. Users can select and send these stickers directly within their chat interface, enriching communication with visually expressive and contextually relevant imagery.

An automation system controls an automated production process of an industrial plant. The industrial plant includes a plurality of equipment for performing the production process. The automation system includes an augmented reality system including augmented reality glasses, executable program logic and a database system including a task manager configured to store a list of processes associated with respective equipment, where each process includes one or more tasks to be performed with respect to the equipment. The executable program logic is configured to receive from the database system the list of processes for display to a user of the AR glasses, receive a selection of a displayed process assigned to the user, send the selected process to the database system, and receive from the database system additional data corresponding to the selected process.

In some embodiments, an electronic device concurrently presents a navigation user interface element with a respective physical location designated and a content element including content corresponding to the respective physical location. In some embodiments, an electronic device presents navigation from a first physical location to a second physical location with reduced visual prominence in a content element in response to an input corresponding to a request to present content corresponding to the second physical location.

There is provided a method of automatically detecting that a target image is deepfake, comprising: receiving authentic images depicting a vehicle with actual damage, receiving the target image depicting potential damage to the vehicle, feeding the target image into a machine learning (ML) model, obtaining a candidate set of human-readable text describing the potential damage to the vehicle, feeding the authentic images into the ML model, obtaining from the ML model, a ground truth set of human-readable text describing the actual damage to the vehicle depicted in the authentic images, computing a similarity metric indicating a difference between the potential damage described in the candidate set of human-readable text and the actual damage described in the ground truth set of human-readable text, and in response to the difference being above a threshold or meeting a requirement indicating a significant difference, detecting that the target image is likely deepfake.

The disclosed technology includes a computer-implemented technique for generating images of physically producible products in response to user input describing a conceptual product. The system receives user input—such as natural language text, speech, or images—via a user interface, configures a prompt for a generative artificial intelligence (AI) system, and generates an image representing a version of the conceptual product with distinct physical attributes. Each version is associated with a unique identifier, enabling selection, modification, and purchase of the conceptual product. The system supports multiple product categories, including jewelry, home décor, and fashion, and extracts physical attributes to determine manufacturability and pricing. User feedback is incorporated to improve AI performance. The invention enables presentation of selectable product versions and initiates manufacturing processes based on user selections, supporting unstructured user input and multiple data modalities.

The present disclosure generally relates to methods and user interfaces for managing watch face user interfaces. In some embodiments, methods and user interfaces for managing watch faces based on depth data of a previously captured media item are described. In some embodiments, methods and user interfaces for managing clock faces based on geographic data are described. In some embodiments, methods and user interfaces for managing clock faces based on state information of a computer system are described. In some embodiments, methods and user interfaces related to the management of time are described. In some embodiments, methods and user interfaces for editing user interfaces based on depth data of a previously captured media item are described.

A method, apparatus, non-transitory computer readable medium, and system for image processing include obtaining an input image and an input mask, wherein the input mask indicates a region of the input image to be modified and generating, using a first image generation model, an intermediate result based on the input image and the input mask, wherein the intermediate result modifies the region of the input image indicated by the input mask. A second image generation model generates a synthetic image based on the input image and the intermediate result, wherein the synthetic image depicts the input image with content from the modified region at a higher level of detail than the intermediate result.

One or more computer systems switch a representation of a first content item at a docked position in an environment with a representation of a second content item in the environment in response to input, switch from displaying a first environment to displaying a second environment in response to input while displaying a representation of a first content item at a docked position, detect and respond to events corresponding to requests to move virtual content in an environment, detect and respond to events corresponding to requests to transition a mode of display of virtual content in the environment, display a first framing element concurrently with a representation of a content item having different degrees of transparency in response to detecting an input, and / or facilitate docking of a content item in an environment based on an input, and / or determine clusters of virtual objects and restore virtual objects after a reboot event.

An XR system is provided. This system captures images including images of a first hand of a user and a second hand of the user using one or more cameras. The XR system generates cropped images using the images, each cropped image including a surface of the first hand. The XR system detects a hand touch of the surface of the hand by a digit of the second hand using the cropped images. The hand touch is used as an input into an XR user interface of the XR system. The surface of the hand can be palmar surface or a hand dorsal surface.