Multi-sensory presentation of volumetric content

Abstract

Input indicating a selection of volumetric content for presentation is received. The volumetric content includes a volumetric representation of one or more elements of a real-world three-dimensional space. In response to the input, device state data associated with the volumetric content is accessed. The device state data describes a state of one or more network connected devices associated with a real-world three-dimensional space. And presenting the volume content. The presentation of the volumetric content includes presenting, by a display device, a volumetric representation of one or more elements superimposed on a real-world three-dimensional space, and configuring one or more network-connected devices using device state data.

Description

[0001] Priority claim

[0002] This patent application claims the benefit of priority to U.S. application serial number 17 / 899,970, filed on August 31, 2022, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates generally to mobile and wearable computing technologies. In particular, example embodiments of the present disclosure relate to systems, methods, and user interfaces for providing multisensory presentation of volumetric content. Background Art

[0004] Augmented reality (AR) experiences include applying virtual content to a real-world environment, whether by presenting the virtual content through a transparent display through which the real-world environment can be seen, or by enhancing image data to include virtual content superimposed on the real-world environment depicted therein. Virtual content may include one or more AR content items. AR content items may include audio content, visual content, or visual effects. Examples of audio content and visual content include pictures, text, logos, animations, and sound effects. Devices that support AR experiences in any of these ways are referred to herein as "AR devices."

[0005] For some example AR devices, audio and visual content or visual effects are applied to media data such as live image streams. Other example AR devices include head-mounted devices that can be implemented with transparent displays or translucent displays, through which users of the head-mounted devices can view the surrounding environment. Such devices enable users to see through the transparent or translucent display to view the surrounding environment, and can also see objects (e.g., virtual objects such as 3D renderings, images, videos, text, etc.) generated for display to appear as part of the surrounding environment and / or superimposed on the surrounding environment. Users of head-mounted devices can access and use computer software applications to perform various tasks or participate in entertainment activities. In order to use the computer software application, the user interacts with the 3D user interface provided by the head-mounted device.

[0006] The so-called "Internet of Things" or "IoT" is a network of physical objects (referred to as "smart devices" or "IoT devices") embedded with sensors, software, and other technologies that enable connection and exchange of data with other devices via the Internet. For example, IoT devices are used for home automation to control lighting, heating and air conditioning, media and security systems, and camera systems. Several IoT-enabled devices have been provided that serve as smart home hubs that connect different smart home products. IoT devices have also been used in several other applications. Application layer protocols and supporting frameworks for implementing such IoT applications have been provided. Artificial intelligence is also combined with IoT infrastructure to enable more efficient IoT operation, improve human-computer interaction, and enhance data management and analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] To easily identify the discussion of any particular element or action, the most significant digit(s) in a reference number refers to the figure number in which the element or action is first introduced.

[0008] Figure 1 is a diagrammatic representation of a networked environment in which a volumetric content rendering system may be deployed, according to some example implementations.

[0009] Figure 2A is a perspective view of a head mounted device according to some example embodiments.

[0010] Figure 2B According to some example embodiments, Figure 2A Additional views of the head-mounted device.

[0011] Figure 3 is a diagram showing a method according to some example embodiments including Figure 1 A block diagram of the networking system with details of the head mounted device.

[0012] Figure 4 is a diagrammatic representation of a volumetric content rendering system having both client-side and server-side functionality, according to some examples.

[0013] Figure 5 is a diagrammatic representation of a data structure as maintained in a database, according to some example implementations.

[0014] Figures 6 to 8 is a flow chart illustrating the operation of a volumetric content rendering system in performing a method for rendering volumetric video according to an example implementation.

[0015] Fig. 9 is a block diagram illustrating a representative software architecture that may be used in conjunction with the various hardware architectures described herein, according to an example implementation.

[0016] Fig.10 is a block diagram illustrating components of a machine capable of reading instructions from a machine-readable medium (eg, a machine-readable storage medium) and performing any one or more of the methodologies discussed herein, according to example embodiments. DETAILED DESCRIPTION

[0017] The following description includes systems, methods, techniques, instruction sequences and computer program products that implement the illustrative embodiments of the present disclosure. In the following description, for the purpose of illustration, many specific details are set forth to provide an understanding of the various embodiments of the subject of the present invention. However, it will be apparent to those skilled in the art that the embodiments of the subject of the present invention can be put into practice without these specific details. Usually, it is not necessary to show in detail known instruction examples, protocols, structures and techniques.

[0018] Volumetric content is an example of an augmented reality (AR) experience. Volumetric content may include volumetric video and images of a three-dimensional space captured in three dimensions (as well as audio signals recorded with the volumetric video and images). Recording of volumetric content includes: using a combination of a camera and a sensor to volumetrically capture elements of the three-dimensional space such as objects and humans. Volumetric content includes a volumetric representation of one or more three-dimensional elements (e.g., objects or people) of the three-dimensional space. The volumetric representation of an element (e.g., an AR content item) refers to a visual representation of the three-dimensional element in three dimensions. The presentation of volumetric content may include: displaying one or more AR content items superimposed on a real-world space, which may be the same or a different space from the three-dimensional space in which the volumetric video is captured. The presentation of volumetric content may include: displaying one or more content items in motion, displaying one or more content items performing movement or other actions, displaying one or more content items in a static position, or a combination thereof. The content items may be displayed for the duration of the presentation of the volumetric content or a portion of the volumetric content.

[0019] The presentation of volumetric content may include tracking the user's position and movement within their physical real-world environment, and using the tracked user position and movement to allow the user to move around and interact with the presentation of volumetric content. Thus, the presentation of volumetric content may include displaying content items from multiple perspectives based on changes in the user's movement and position. In this manner, the presentation of volumetric content provides an immersive AR experience to the user.

[0020] Conventional volumetric content systems lack mechanisms to support fully immersive AR experiences beyond simply displaying volumetric content. That is, conventional volumetric content systems typically provide only limited engagement with the user's sight and sound, while failing to provide interaction with the user's other senses, thereby reducing the perception of realism that the AR experience is intended to provide by presenting a volumetrically captured moment.

[0021] Aspects of the present disclosure include systems, methods, techniques, instruction sequences, and computer program products for providing multi-sensory presentation of volumetric content. To this end, a volumetric presentation system associates device state information with the volumetric content, and the system uses the device state information to configure one or more network-connected devices (e.g., IoT devices) as part of presenting the volumetric content. In this manner, devices associated with a volumetric capture of a user's experience can be configured to behave or operate during presentation of the volumetric content in the same manner as the volumetric content was during volumetric capture, thereby helping to recreate aspects of the real-world environment that was volumetrically captured at the time of volumetric capture to provide an AR experience that allows the user to re-experience prior moments and memories in a manner similar to how they originally experienced them, thereby almost creating a sense of deja vu-like.

[0022] In a first example, volumetric capture technology is used to generate volumetric content depicting a baby's first walk. During the volumetric capture, the family is in the living room, the lights are on, the smart speaker is playing background music, the parents are drinking coffee and watching TV, and the A / C is on - when the baby starts walking with toys lying around. The capture system (e.g., using a camera device, phone, or other setting) captures the baby's walk and toys as a volumetric scene, and collects state information that defines the state of all network-connected devices. In order to create a multi-sensory AR experience when presenting volumetric content, the volumetric content presentation system triggers all network-connected devices and projects a volumetric representation of the baby's walk in AR. More specifically, the presentation system causes: the AR device presents a volumetric presentation of the baby walking with toys; the audio device coupled to the AR device presents a conversation recorded from that moment; the lights turn on; the TV starts playing the same movie that was playing during the baby's walk; the A / C (controlled by the smart thermostat) turns on to bring the room to the same temperature; the smart coffee maker brews the same coffee; and the smart speaker plays the same music.

[0023] In a second example, volumetric capture technology can be used to generate volumetric content depicting a road trip taken by two friends. In this example, the two friends use wearable smart glasses to record videos and take photos to capture their shared experience on a road trip in the fall. As summer begins, the two friends decide to embark on the same road trip again. As the car moves along the same route that the friends took last time, the friends can select volumetric content for presentation. The volumetric content presentation system uses an AR device to project the colors of autumn onto the green trees of summer, bringing the friends back to that season. The presentation of volumetric content can also allow the two friends to watch their own volumetric presentation at exactly the same location, like watching their own AR movie in which they are the star. The volumetric content presentation system can also enable: the audio device to play the same song playlist played at a specific location during the trip; the navigation system recommends stopping at the same restaurants and coffee shops so that friends can relive the same experience; and the A / C and seat positioning in the car return to the same state as during the volumetric capture. Using a combination of AR displays and network-connected smart devices, the presentation system aims to recreate the same scene from the past in the way they felt it for the first time, and activate all five senses.

[0024] In accordance with some embodiments, a volumetric rendering system generates experience data including volumetric content and device state data associated with the volumetric content. The volumetric content includes a volumetric representation of one or more elements of a real-world three-dimensional space. The device state data includes a state of at least one network-connected device associated with the real-world three-dimensional space. In response to receiving a request to render the volumetric content, the volumetric content rendering system accesses the device state data associated with the volumetric content and uses the device state data to configure the one or more network-connected devices as part of the rendering of the volumetric content, which also includes causing a display device to render the volumetric representation of the one or more elements of the real-world three-dimensional space.

[0025] Figure 1 1 is a block diagram illustrating an example volumetric content rendering system 100 for rendering volumetric content. The volumetric content rendering system 100 includes a client device 102. The client device 102 hosts several applications including a rendering client 104. Each rendering client 104 is communicatively coupled to a rendering server system 108 via a network 106 (e.g., the Internet). In an example, the client device 102 is a wearable device (e.g., smart glasses) worn by a user 103, the wearable device including a camera and an optical element including a transparent display through which a real-world environment is visible to the user 103.

[0026] The presence client 104 is able to communicate and exchange data with another presence client 104 and a presence server system 108 via the network 106. The data exchanged between the presence clients 104 and between another presence client 104 and the presence server system 108 includes functions (e.g., commands for activating functions) and payload data (e.g., text, audio, video, or other multimedia data).

[0027] The presentation server system 108 provides server-side functionality to a particular presentation client 104 via the network 106. Although certain functionality of the volumetric content presentation system 100 is described herein as being performed by either the presentation client 104 or by the presentation server system 108, the location of certain functionality within the presentation client 104 or within the presentation server system 108 is a design choice. For example, it may be technically preferable to initially deploy certain technologies and functionality within the presentation server system 108, but later migrate the technologies and functionality to a presentation client 104 where the client device (102) has sufficient processing power.

[0028] The presence server system 108 supports various services and operations provided to the presence clients 104. Such operations include sending data to the presence clients 104, receiving data from the presence clients 104, and processing data generated by the presence clients 104. As examples, the data may include volumetric content (e.g., volumetric video), message content, device information, geolocation information, media annotations and overlays, message content persistence conditions, social network information, and live event information. The exchange of data within the volumetric content presentation system 100 is activated and controlled by functionality available via a user interface (UI) of the presence clients 104.

[0029] Turning now specifically to the presence server system 108, an application program interface (API) server 110 is coupled to and provides a programming interface to an application server 112. The application server 112 is communicatively coupled to a database server 118, which facilitates access to a database 120 in which data associated with messages processed by the application server 112 is stored.

[0030] An application program interface (API) server 110 receives and sends message data (e.g., commands and message payloads) between a client device 102 and an application server 112. Specifically, the API server 110 provides a set of interfaces (e.g., routines and protocols) that can be called or queried by a presence client 104 to activate functionality of the application server 112. The API server 110 exposes various functions supported by the application server 112, including: account registration, login functionality, sending messages from a particular presence client 104 to another presence client 104 via the application server 112, sending media files (e.g., volumetric video) to a presence client 104, setting a collection of media data (e.g., a story), retrieving a friend list of a user of the client device 102, retrieving such a collection, retrieving messages and content, adding and removing friends from a social graph, locating friends within a social graph, and opening application events (e.g., related to a presence client 104).

[0031] The application server 112 hosts several applications and subsystems, including a rendering server 114, an image processing server 116, and a social network server 122. The rendering server 114 is generally responsible for managing volumetric content and facilitating the rendering of volumetric content by the client device 102. The image processing server 116 is dedicated to performing various image processing operations, generally with respect to images or videos generated and displayed by the client device 102. The rendering server 114 and the image processing server 116 can work together to provide one or more AR experiences for the user 103. For example, the rendering server 114 and the image processing server 116 can work together to support the rendering of volumetric content by the client device 102. Further details regarding the rendering of volumetric content are discussed below.

[0032] The social network server 122 supports various social networking functions and services and makes these functions and services available to the presence server 114. To this end, the social network server 122 maintains and accesses an entity graph within the database 120. Examples of functions and services supported by the social network server 122 include identifying other users of the volumetric content presentation system 100 that have a relationship with a particular user or that the particular user is "following", and also includes identifying interests and other entities of a particular user.

[0033] The application server 112 is communicatively coupled to a database server 118 , which facilitates access to a database 120 in which data associated with content rendered by the rendering server 114 and the image processing server 116 is stored.

[0034] The presence server system 108 may also communicate and exchange data with one or more network-connected devices 130. For some devices, the presence server system 108 may communicate and exchange data with the network-connected devices 130 directly, while in other cases, the presence server system 108 may communicate and exchange data with the network-connected devices 130 via a network service 132 (e.g., a third-party application). For example, the network service 132 may expose one or more APIs for communicating with the network-connected devices 130. Examples of data transmitted between the presence server system 108 and one or more network-connected devices include device state data and sensor data, as well as or as part of various requests and commands. Figure 1 As shown, in some embodiments, the client device 102 (e.g., such as Figure 2A The display device of the glasses 200 in the figure is different from the network connection device 130.

[0035] As used herein, the term "network-connected device" includes devices that are referred to by those skilled in the art as "IoT devices." Thus, network-connected devices 130 may include other devices that a normal household and standard end user might encounter, such as smart lights and bulbs, thermostats, smart TVs, smart speakers, smart switches, smart appliances (e.g., washers, dryers, stoves, and microwaves), navigation systems, etc.

[0036] Figure 2A is a perspective view of a head mounted display device (eg, glasses 200) according to some examples. Glasses 200 are Figure 1 The glasses 200 are examples of client devices 102. The glasses 200 are capable of displaying content, and are therefore examples of display devices referenced below. In addition, the display capabilities of the glasses 200 support AR experiences, and are therefore examples of AR devices. As described above, AR experiences include applying virtual content to a real-world environment, whether by presenting the virtual content through a transparent display through which the real-world environment is visible, or by augmenting image data to include virtual content superimposed on the real-world environment depicted therein.

[0037] The glasses 200 may include a frame 202 made of any suitable material, such as plastic or metal, including any suitable shape memory alloy. In one or more examples, the frame 202 includes a first optical element holder or left optical element holder 204 (e.g., a display or lens holder) and a second optical element holder or right optical element holder 206 connected by a bridge 212. A first optical element or left optical element 208 and a second optical element or right optical element 210 may be disposed in the respective left optical element holder 204 and right optical element holder 206. The right optical element 210 and the left optical element 208 may be lenses, displays, display components, or a combination of the foregoing. Any suitable display component may be disposed in the glasses 200.

[0038] Frame 202 also includes a left arm or temple piece 222 and a right arm or temple piece 224. In some examples, frame 202 can be formed from a single piece of material to have a unitary or unitary construction.

[0039] The glasses 200 may include a computing device such as a computer 220, which may be of any suitable type so as to be carried by the frame 202, and in one or more examples, the computing device may be of a suitable size and shape to be partially disposed in one of the temple pieces 222 or temple pieces 224. The computer 220 may include one or more processors with memory, wireless communication circuitry, and a power supply. As discussed below, the computer 220 includes a low-power circuitry, a high-speed circuitry, and a display processor. Various other examples may include these elements in different configurations or integrated together in different ways. As shown in the data processor 302 discussed below, additional details of various aspects of the computer 220 may be implemented.

[0040] The computer 220 additionally includes a battery 218 or other suitable portable power supply. In some examples, the battery 218 is disposed in the left temple piece 222 and is electrically coupled to the computer 220 disposed in the right temple piece 224. The glasses 200 may include a connector or port (not shown) suitable for charging the battery 218, a wireless receiver, transmitter or transceiver (not shown), or a combination of such devices.

[0041] The glasses 200 include a first camera or left camera 214 and a second camera or right camera 216. Although two cameras are depicted, other examples contemplate the use of a single or additional (i.e., more than two) cameras. In one or more examples, the glasses 200 include any number of input sensors or other input / output devices in addition to the left camera 214 and the right camera 216. Such sensors or input / output devices may additionally include biometric sensors, positioning sensors, motion sensors, etc.

[0042] In some examples, left camera 214 and right camera 216 provide video frame data for use by glasses 200 to extract 3D information from a real-world scene.

[0043] The glasses 200 may also include a touchpad 226 mounted to one or both of the left temple piece 222 and the right temple piece 224, or integrated with one or both of the left temple piece 222 and the right temple piece 224. In some examples, the touchpad 226 is generally arranged vertically, approximately parallel to the temple of the user. As used herein, generally vertical alignment means that the touchpad is more vertical than horizontal, although potentially more vertical than this situation. Additional user input can be provided by one or more buttons 228, which, in the example shown, are disposed on the outer upper edges of the left optical element holder 204 and the right optical element holder 206. One or more touchpads 226 and buttons 228 provide a path through which the glasses 200 can receive input from the user of the glasses 200.

[0044] Figure 2B The glasses 200 are shown from the user's perspective. Figure 2A Several elements shown in FIG. Figure 2A As described, Figure 2B The illustrated eyeglasses 200 include a left optical element 208 and a right optical element 210 secured in a left optical element holder 204 and a right optical element holder 206, respectively.

[0045] The glasses 200 include a forward optical assembly 230 including a right projector 232 and a right near-eye display 234 , and a forward optical assembly 238 including a left projector 240 and a left near-eye display 244 .

[0046] In some examples, the near-eye display is a waveguide. The waveguide includes a reflective structure or a diffractive structure (e.g., a grating and / or an optical element such as a mirror, lens, or prism). Light 236 emitted by projector 232 encounters the diffractive structure of the waveguide of near-eye display 234, which directs the light toward the right eye of the user to provide an image superimposed on or in the right optical element 210 with a view of the real world seen by the user. Similarly, light 242 emitted by projector 240 encounters the diffractive structure of the waveguide of near-eye display 244, which directs the light toward the left eye of the user to provide an image superimposed on or in the left optical element 208 with a view of the real world seen by the user. The combination of the GPU, the forward optical assembly 230, the left optical element 208, and the right optical element 210 provides an optical engine of glasses 200. Glasses 200 use the optical engine to generate an overlay of the user's real-world view, including displaying a 3D user interface to the user of glasses 200.

[0047] However, it will be appreciated that other display technologies or configurations may be utilized within the optical engine to display images to the user in the user's field of view. For example, instead of the projector 232 and waveguide, an LCD, LED or other display panel or surface may be provided.

[0048] When in use, the user of the glasses 200 will be presented with information, content, and various 3D user interfaces on the near-eye display. As described in more detail herein, the user can then use the touch pad 226 and / or buttons 228, associated devices (e.g., Figure 3 The user may interact with the glasses 200 through voice input or touch input on a client device 328 shown in FIG. 1 , and / or hand movements, positions, and locations detected by the glasses 200 .

[0049] Figure 3 is a block diagram showing a networked system 300 including details of the glasses 200 according to some examples. The networked system 300 includes the glasses 200, a client device 328, and a server system 332. The client device 328 may be a smartphone, a tablet computer, a tablet phone, a laptop computer, an access point, or any other such device capable of connecting to the glasses 200 using a low power wireless connection 336 and / or a high speed wireless connection 334. The client device 328 is connected to the server system 332 via a network 330. The network 330 may include any combination of wired and wireless connections. The server system 332 may be one or more computing devices that are part of a service or network computing system. The client device 328 and any elements of the server system 332 and the network 330 may be connected using a wireless network, such as a wireless network or a wireless network. Fig. 9 and Fig.10 The details of the software architecture 906 or machine 1000 described in the description are implemented.

[0050] The glasses 200 include a data processor 302, a display 310, one or more cameras 308, and additional input / output elements 316. The input / output elements 316 may include a microphone, an audio speaker, a biometric sensor, an additional sensor, or an additional display element integrated with the data processor 302. Fig. 9 and Fig.10 Examples of input / output elements 316 are further discussed. For example, input / output elements 316 may include any I / O components 1018, including output components 1026, motion components 1034, etc. Figure 2B Examples of display 310 are discussed in . In the specific examples described herein, display 310 includes displays for the left and right eyes of a user.

[0051] Data processor 302 includes image processor 306 (eg, video processor), GPU and display driver 338, tracking module 340, interface 312, low power circuitry 304, and high speed circuitry 320. Components of data processor 302 are interconnected by bus 342.

[0052] The interface 312 refers to any source of user commands provided to the data processor 302. In one or more examples, the interface 312 is a physical button that sends a user input signal from the interface 312 to the low-power processor 314 when pressed. Pressing such a button and then releasing it immediately can be processed by the low-power processor 314 as a request to capture a single image, and vice versa. Pressing such a button for a first period of time can be processed by the low-power processor 314 as a request to capture video data when the button is pressed and end video capture when the button is released, wherein the video captured when the button is pressed is stored as a single video file. Alternatively, pressing the button for a long period of time can capture a still image. In some examples, the interface 312 can be any mechanical switch or physical interface capable of accepting user input associated with requesting data from the camera 308. In other examples, the interface 312 can have a software component, or can be associated with a command received wirelessly from another source such as from the client device 328.

[0053] Image processor 306 includes circuitry for receiving signals from camera 308 and processing those signals from camera 308 into a format suitable for storage in memory 324 or for transmission to client device 328. In one or more examples, image processor 306 (e.g., a video processor) includes a microprocessor integrated circuit (IC) customized for processing sensor data from camera 308, and volatile memory used by the microprocessor in operation.

[0054] The low power circuit system 304 includes a low power processor 314 and a low power wireless circuit system 318. These elements of the low power circuit system 304 can be implemented as separate elements or can be implemented on a single IC as part of a single system on a chip. The low power processor 314 includes logic for managing other elements of the glasses 200. As described above, for example, the low power processor 314 can accept user input signals from the interface 312. The low power processor 314 can also be configured to receive input signals or command communications from a client device 328 via a low power wireless connection 336. The low power wireless circuit system 318 includes circuit elements for implementing a low power wireless communication system. Bluetooth TM Smart, also known as Bluetooth TM Low power consumption is a standard implementation of a low power wireless communication system that may be used to implement the low power wireless circuitry 318. In other examples, other low power communication systems may be used.

[0055] High-speed circuit system 320 includes a high-speed processor 322, a memory 324, and a high-speed wireless circuit system 326. High-speed processor 322 can be any processor capable of managing high-speed communications and operations for any general-purpose computing system for data processor 302. High-speed processor 322 includes processing resources for managing high-speed data transmission over high-speed wireless connection 334 using high-speed wireless circuit system 326. In some examples, high-speed processor 322 executes an operating system such as a LINUX operating system or a program such as a UNIX operating system. Figure 5 The high-speed processor 322, which executes the software architecture of the data processor 302, manages data transmission with the high-speed wireless circuit system 326, in addition to any other duties. In some examples, the high-speed wireless circuit system 326 is configured to implement the Institute of Electrical and Electronics Engineers (IEEE) 802.11 communication standard, which is also referred to herein as Wi-Fi. In other examples, other high-speed communication standards can be implemented by the high-speed wireless circuit system 326.

[0056] Memory 324 includes any storage device capable of storing camera data generated by camera 308 and image processor 306. Although memory 324 is shown as being integrated with high-speed circuitry 320, in other examples, memory 324 may be a separate, stand-alone element of data processor 302. In some such examples, electrical wiring may provide a connection from image processor 306 or low-power processor 314 to memory 324 through a chip that includes high-speed processor 322. In other examples, high-speed processor 322 may manage addressing of memory 324 so that low-power processor 314 will initiate high-speed processor 322 any time a read or write operation involving memory 324 is needed.

[0057] The tracking module 340 estimates the pose of the glasses 200. For example, the tracking module 340 uses image data and corresponding inertial data from the camera 308 and the positioning component 1038, as well as GPS data, to track the position and determine the pose of the glasses 200 relative to a reference frame (e.g., a real-world environment). The tracking module 340 continuously collects and uses updated sensor data describing the movement of the glasses 200 to determine an updated three-dimensional pose of the glasses 200, which indicates changes in relative position and orientation relative to physical objects in the real-world environment. The tracking module 340 allows the glasses 200 to visually place virtual objects relative to physical objects within the user's field of view via the display 310.

[0058] The GPU and display driver 338 may use the pose of the glasses 200 to generate frames of virtual content or other content to be presented on the display 310 when the glasses 200 are operating in a conventional augmented reality mode. In this mode, the GPU and display driver 338 generate updated frames of virtual content based on the updated three-dimensional pose of the glasses 200, which reflects changes in the position and orientation of the user relative to physical objects in the user's real-world environment.

[0059] One or more functions or operations described herein may also be performed in an application resident on the glasses 200 or on the client device 328 or on a remote server. The glasses 200 may be a stand-alone client device capable of independent operation, or may be a companion device that works with a host device to offload intensive processing and / or exchange data with the presentation server system 108 over the network 106. The glasses 200 may also be communicatively coupled to a companion device such as a smart watch and may be configured to exchange data with the companion device. The glasses 200 may also include various components common to mobile electronic devices such as smart glasses or smart phones (e.g., including a display controller for controlling the display of visual media on a display mechanism incorporated in the device).

[0060] Figure 41 is a block diagram showing additional details about a volumetric content rendering system 100 according to some examples. Specifically, the volumetric content rendering system 100 is shown to include a rendering client 104 and an application server 112. The volumetric content rendering system 100 contains several subsystems that are supported on the client side by the rendering client 104 and on the server side by the application server 112. These subsystems include, for example, a collection management system 402, a rendering control system 404, an augmentation system 406, a device configuration system 408, and a multi-sensory experience generation system 410.

[0061] The collection management system 402 is responsible for managing groups or collections of content (e.g., collections of text, images, video, and audio data). Collections of content may be organized into "event galleries" or "event stories." Such collections may be made available for a specified time period (e.g., the duration of an event to which the content is related). For example, content related to a concert may be made available as a "story" for the duration of the concert. The collection management system 402 may also be responsible for publishing an icon to the user interface of the presentation client 104 that provides notification of the existence of a particular collection.

[0062] In addition, the collection management system 402 also includes a curation interface 412, which allows collection managers to manage and curate specific content collections. For example, the curation interface 412 enables event organizers to curate a collection of content related to a specific event (e.g., to remove inappropriate content or redundant messages). Additionally, the collection management system 402 uses machine vision (or image recognition technology) and content rules to automatically curate content collections.

[0063] The presentation control system 404 is responsible for facilitating and controlling the volumetric content presentation. Thus, the presentation control system 404 provides a mechanism that allows a user to specify control operations for controlling the volumetric content presentation. The control operations may include, for example: a stop operation for stopping the presentation; a pause operation for pausing the presentation; a fast forward operation for advancing the presentation at a higher speed; a rewind operation for rewinding the presentation; a zoom in operation for increasing the zoom level of the presentation; a zoom out operation for decreasing the zoom level of the presentation; and a playback speed modification operation for changing the speed of the presentation (e.g., for producing a slow motion presentation of volumetric video).

[0064] For some embodiments, a user may specify inputs indicative of control operations for controlling presentation of volumetric content by providing one or more inputs via one or more I / O components (examples of which are described below with reference to Fig.10For some embodiments, the presentation control system 404 may provide an interactive control interface including one or more interactive elements (e.g., virtual buttons) to trigger a control operation, and the presentation control system 404 monitors interactions with the interactive interface to detect input indicating a control operation. For some embodiments, a user may trigger a control operation using a gesture such as a hand gesture or a head gesture that may be associated with a particular control operation.

[0065] The enhancement system 406 provides various functions that enable a user to enhance (e.g., annotate or otherwise modify or edit) media content. For example, the enhancement system 406 provides functions related to the generation, publication, and application of enhancement data, such as media overlays (e.g., image filters) to volumetric content. Media overlays can include audio and visual content and visual effects. Examples of audio content and visual content include pictures, text, logos, animations, and sound effects. Examples of visual effects include color overlays. Audio content and visual content or visual effects can be applied to media content items (e.g., photos) at the client device 102. For example, a media overlay can include text or images that can be superimposed on a photo taken by the client device 102. The enhancement system 406 is operable to provide one or more media overlays to the presentation client 104 based on the geographic location of the client device 102 or based on other information (such as social network information of a user of the client device 102). The media overlays can be stored in the database 120 and accessed through the database server 118.

[0066] A filter is an example of a media overlay that is displayed as an overlay on an image or video during presentation to a user. Filters can be of various types, including filters selected by a user from a set of filters presented to a user by presentation client 104. Other types of filters include geolocation filters (also referred to as geofilters), which can be presented to a user based on a geographic location. For example, presentation client 104 can present a geolocation filter specific to a nearby or particular location within a user interface based on geographic location information determined by a global positioning system (GPS) unit of client device 102.

[0067] Another type of filter is a data filter, which can be selectively presented to the user by the presentation client 104 based on other input or information collected by the client device 102. Examples of data filters include the current temperature at a particular location, the current speed the sending user is traveling, the battery life of the client device 102, or the current time.

[0068] AR content items are another example of a media overlay. AR content items may be real-time special effects and sounds that can be added to images or videos, including volumetric images and videos.

[0069] In general, AR content items, overlays, image transformations, images, and the like refer to modifications that can be applied to image data (e.g., video or images) that include volumetric content. This includes real-time modifications that modify an image as it is captured using a device sensor (e.g., one or more cameras) of the client device 102, and then the image with the modifications is displayed by a display device (e.g., an embedded display of the client device) of the client device 102. This also includes modifications to stored content such as volumetric videos in a gallery or collection that can be modified. For example, in a client device 102 that has access to multiple AR content items, a user can use a single volumetric video with multiple AR content items to see how different AR content items will modify the stored content. For example, by selecting different AR content items for the content, multiple augmented reality content items that apply different pseudo-random movement models can be applied to the same content. Similarly, real-time video capture can be used with the modifications shown to show how the video image currently captured by the sensor of the client device 102 will modify the captured data. Such data may be displayed only on the screen and not stored in memory, or content captured by the device sensors may be recorded and stored in memory with or without modification (or both). In some systems, a preview feature may show how different augmented reality content items will look in different windows of the display simultaneously. For example, this may enable viewing multiple windows with different pseudo-random animations on the display simultaneously.

[0070] Thus, data and various systems using augmented reality content items or other such augmented systems using augmented data to modify content may involve: detection of objects (e.g., faces, hands, bodies, cats, dogs, surfaces, objects, etc.) in video frames, tracking such objects as they leave the field of view, enter the field of view, and move around in the field of view, and modifying or transforming such objects as they are tracked. In various examples, different methods for implementing such transformations may be used. Some examples may involve generating a three-dimensional mesh model of one or more objects, and using transformations and animated textures of the models within the video to implement the transformations. In other examples, tracking of points on an object may be used to place an image or texture (which may be two-dimensional or three-dimensional) at a tracked location. In yet another example, neural network analysis of video frames may be used to place images, models, or textures in content (e.g., frames of an image or video). Thus, an AR content item refers to both images, models, and textures used to create transformations in content, as well as additional modeling and analysis information required to implement such transformations using object detection, tracking, and placement.

[0071] Real-time video processing can be performed with any kind of video data (e.g., video streams, video files, volumetric video, etc.) stored in the memory of any kind of computerized system. For example, a user can load video files and store them in the memory of the device, or a sensor of the device can be used to generate a video stream. In addition, any object, such as a human face and parts of a human body, an animal, or a non-living thing (e.g., a chair, a car, or other objects) can be processed using computer animation models.

[0072] In some examples, when a specific modification is selected together with the content to be enhanced (e.g., edited), the element to be transformed is identified by a computing device, and then if the element to be transformed is present in a frame of a video, the element to be transformed is detected and tracked. The elements of the object are modified according to the request for modification, so the frame of the video stream is transformed. For different kinds of transformations, the transformation of the frame of the video stream can be performed by different methods. For example, for a frame transformation that mainly involves changing the form of the elements of the object, feature points for each element of the object are calculated (e.g., using an active shape model (ASM) or other known methods). Then, a grid based on feature points is generated for each element of at least one element of the object. The grid can be used in a subsequent stage of tracking the elements of the object in the video stream. During the tracking process, the grid mentioned for each element is aligned with the positioning of each element. Then, additional points are generated on the grid. A set of first points is generated for each element based on the request for modification, and a set of second points is generated for each element based on the set of first points and the request for modification. Then, the frame of the video stream can be transformed by modifying the elements of the object based on the set of first points, the set of second points and the grid. In such an approach, the background of the modified object may also be changed or distorted by tracking and modifying the background.

[0073] In some examples, a transformation that changes some areas of an object using elements of an object can be performed by calculating feature points for each element of the object and generating a grid based on the calculated feature points. Points are generated on the grid, and then various areas are generated based on these points. Then, the elements of the object are tracked by aligning the area of ​​each element with the position of each element of at least one element, and the properties of the area can be modified based on the modification request, thereby transforming the frame of the video stream. Depending on the specific modification request, the properties of the mentioned area can be transformed in different ways. Such modifications may involve changing the color of the area; removing at least some parts of the area from the frame of the video stream; including one or more new objects into the area based on the modification request; and modifying or distorting the elements of the area or object. In various examples, any combination of such modifications or other similar modifications may be used. For certain models to be animated, some feature points may be selected as control points for determining the entire state space of options for model animation.

[0074] In some examples of computer animation models that use face detection to transform image data, faces are detected on an image using a specific face detection algorithm (e.g., Viola-Jones). An active shape model (ASM) algorithm is then applied to the face region of the image to detect facial feature reference points.

[0075] Other methods and algorithms suitable for face detection can be used. For example, in some examples, landmarks are used to locate features, which represent distinguishable points that are present in most of the images considered. For example, for facial landmarks, the location of the left eye pupil can be used. If the initial landmarks are not identifiable (for example, if the person is wearing an eye mask), secondary landmarks can be used. Such a landmark recognition process can be used for any such object. In some examples, a set of landmarks forms a shape. The shape can be represented as a vector using the coordinates of the points in the shape. A similarity transformation (which allows translation, scaling, and rotation) that minimizes the average Euclidean distance between the shape points is used to align one shape with another. The mean shape is the average of the aligned training shapes.

[0076] In some examples, the landmark search begins with an average shape that aligns with the position and size of the face determined by a global face detector. Such a search then repeats the steps of proposing tentative shapes by adjusting the positions of shape points by template matching of the image texture around each point, and then conforming the tentative shapes to a global shape model until convergence occurs. In some systems, individual template matches are unreliable, and the shape model pools the results of weak template matches to form a stronger overall classifier. The entire search is repeated at each level in the image pyramid, from coarse to fine resolution.

[0077] The augmentation system 406 can capture an image or video stream on a client device (e.g., client device 102) and perform complex image manipulations locally on the client device 102 while maintaining a suitable user experience, computational time, and power consumption. Complex image manipulations can include size and shape changes, emotional transitions (e.g., changing a face from a frown to a smile), state transitions (e.g., aging a subject, reducing apparent age, changing gender), style transitions, application of graphical elements, and any other suitable image or video manipulations enabled by a convolutional neural network that has been configured to execute efficiently on the client device 102.

[0078] The augmentation system 406 can capture images or video streams on a client device (e.g., client device 102) and perform complex image manipulations locally on the client device 102 while maintaining a suitable user experience, computational time, and power consumption. Complex image manipulations can include size and shape changes, emotional transitions (e.g., changing a face from a frown to a smile), state transitions (e.g., aging a subject, reducing apparent age, changing gender), style transitions, application of graphical elements, and any other suitable image or video manipulations enabled by a machine learning model that has been configured to execute efficiently on the client device 102. In some examples, a computer animation model for transforming video and image content can be used by the augmentation system 406, where a neural network operates as part of a rendering client application 104 operating on the client device 102.

[0079] The machine learning model can be trained using labeled or unlabeled training data including ground-truth information. For example, one or more images depicting a portion of a person's body and / or the entire body can be included in the training data together with ground-truth segmentation information that defines the current positioning of the limbs and joints of the user's entire body (e.g., the positioning of arms, torso, legs, head, shoulders, etc.). The machine learning model can be applied to a subset of the training data, such as one or more images in the training data, and an estimate or prediction of the ground-truth segmentation information about the current positioning of the limbs and joints of the user's entire body (e.g., the positioning of arms, torso, legs, head, shoulders, etc.) can be generated. The estimate or prediction can be compared with the corresponding ground-truth information to calculate the deviation. The deviation can then be used to update one or more parameters of the machine learning model. After updating one or more parameters, the machine learning model is applied to another subset of the training data, and these operations are repeated until the stopping criteria are reached.

[0080] Machine learning is a field of study that gives computers the ability to learn without explicit programming. Machine learning explores the study and construction of algorithms (also referred to herein as tools) that can learn from existing data and make predictions about new data. Such machine learning tools operate by building models based on example training data to make data-driven predictions or decisions that are represented as outputs or evaluations. Although examples are given for several machine learning tools, the principles given herein can be applied to other machine learning tools.

[0081] In some examples, different machine learning tools can be used. For example, logistic regression (LR), naive Bayes, random forest (RF), neural network (NN), matrix factorization, and support vector machine (SVM) tools can be used to classify or score job positions.

[0082] Two common types of problems in machine learning are classification problems and regression problems. Classification problems (also called categorization problems) aim to classify an item into one of several class values ​​(e.g., is this object an apple or an orange?). Regression algorithms aim to quantify some item (e.g., by providing values ​​that are real numbers).

[0083] Machine learning algorithms use features to analyze data to generate estimates. Each of the features is a separate measurable property of the phenomenon being observed. The concept of a feature is related to the concept of explanatory variables used in statistical techniques such as linear regression. Selecting informative, discriminative, and independent features is very important for the effective operation of MLPs in pattern recognition, classification, and regression. Features can be of different types, such as numeric features, strings, and graphs.

[0084] In one example, by way of example only, features may be of different types and may include one or more of content, concepts, attributes, historical data, and / or user data.

[0085] Machine learning algorithms use training data to find correlations between identified features that influence an outcome or evaluation. In some examples, the training data includes labeled data, which is known data about one or more identifying features and one or more outcomes, such as detecting communication patterns, detecting the meaning of a message, generating a summary of a message, detecting action items in a message, detecting urgency in a message, detecting a relationship between a user and a sender, calculating a score attribute, calculating a message score, etc.

[0086] Using the training data and the identified features, a machine learning tool is trained at the machine learning program training location. The machine learning tool evaluates the value of the feature when the feature is associated with the training data. The result of the training is a trained machine learning program.

[0087] When performing an evaluation using a trained machine learning program, new data is provided as input to the trained machine learning program, and the trained machine learning program generates an evaluation as output.

[0088] The machine learning program supports two types of phases, namely, a training phase and a prediction phase. In the training phase, supervised learning, unsupervised learning, or reinforcement learning can be used. For example, the machine learning program (1) receives features (e.g., as structured data or labeled data in supervised learning) and / or (2) identifies features in the training data (e.g., unstructured data or unlabeled data for unsupervised learning). In the prediction phase, the machine learning program uses the features to analyze the query data to generate a result or prediction, as an example of evaluation.

[0089] In the training phase, feature engineering is used to identify features and can include identifying informative, discriminative, and independent features for effective operation of machine learning programs in pattern recognition, classification, and regression. In some examples, the training data includes labeled data, which is known data of pre-identified features and one or more results. Each of the features can be a variable or attribute, such as a measurable property of a process, item, system, or phenomenon represented by a data set (e.g., training data).

[0090] During the training phase, the machine learning program uses the training data to find correlations between features that influence the predicted outcome or evaluation.

[0091] The machine learning program is trained during a training phase at the machine learning program training location using the training data and the identified features. The machine learning program evaluates the value of the feature when the feature is associated with the training data. The result of the training is a trained machine learning program (e.g., a trained or learned model).

[0092] In addition, the training phase may involve machine learning, in which the training data is structured (e.g., labeled during a preprocessing operation), and the trained machine learning program implements a relatively simple neural network that can, for example, perform classification and clustering operations. In other examples, the training phase may involve deep learning, in which the training data is unstructured, and the trained machine learning program implements a deep neural network that can perform both feature extraction and classification / clustering operations.

[0093] The neural network generated during the training phase and implemented within the trained machine learning program can include a hierarchical (e.g., layered) organization of neurons. For example, neurons (or nodes) can be hierarchically arranged into several layers, including an input layer, an output layer, and multiple hidden layers. Each of the layers within the neural network can have one or many neurons, and each of these neurons operationally calculates a small function (e.g., an activation function). For example, if the activation function generates a result that exceeds a certain threshold, the output can be transmitted from the neuron (e.g., a sending neuron) to a connected neuron (e.g., a receiving neuron) in a consecutive layer. The connection between neurons also has an associated weight that defines the influence on the input from the sending neuron to the receiving neuron.

[0094] In some examples, the neural network may also be one of several different types of neural networks, including, by way of example only, a single-layer feedforward network, an artificial neural network (ANN), a recurrent neural network (RNN), a symmetrically connected neural network, and an unsupervised pre-trained network, a convolutional neural network (CNN), or a recurrent neural network (RNN).

[0095] During the prediction phase, the trained machine learning program is used to perform the evaluation. The query data is provided as input to the trained machine learning program, and in response to receiving the query data, the trained machine learning program generates an evaluation as output.

[0096] The device configuration system 408 is responsible for determining and configuring the device state. The device state data defines the state of the network-connected device. The state of the network-connected device can be specified by a user, or can be determined from any one or more of the following: the network-connected device, a network service that communicates with the network-connected device, or sensor data from one or more sensors indicating one or more aspects of the operation or output of the network-connected device. Therefore, the device configuration system 408 can determine the state of the network-connected device by sending one or more requests for device state data to the network-connected device or the network service of the network-connected device, and / or by collecting sensor data from one or more sensors.

[0097] For some devices, the state of the device corresponds to a specific configuration of the device. For example, the state of a network-connected device may include one or more device settings that define various aspects of the operation or output of the device. In some cases, the network-connected device is a network-connected media device, such as a smart TV or speaker, and in these cases, the state may identify secondary content presented by the media device, such as video, image, and / or audio content. In some cases, the network-connected device is a navigation device or other device that provides navigation capabilities, and the device state data includes navigation data, which may include, for example, a path or route between two locations.

[0098] For some embodiments, the state of the network-connected device may correspond to the state of the network-connected device during the volumetric capture experienced by the user. For these embodiments, the device configuration system 408 may determine the state in real time as the volumetric capture occurs, or at a subsequent time after the volumetric capture.

[0099] The multisensory experience generation system 410 is responsible for associating the volumetric content with the determined device state to memorize the user experience. To this end, the multisensory experience generation system 410 can generate experience data for the volumetrically captured experience, the experience data including the virtual content and the associated device state data. When a request is received for rendering virtual content, the volumetric content rendering system 100 accesses the device state data associated with the volumetric content from the experience data, and uses the device state data to configure one or more network-connected devices as part of the rendering of the volumetric content.

[0100] For some embodiments, the multi-sensory experience generation system 410 is also responsible for generating volumetric content based on volumetric data generated as part of the volumetric capture process. Consistent with these embodiments, known volumetric capture techniques can be employed, which involve capturing a three-dimensional space using one or more cameras and sensors and motion capture techniques. The camera data (e.g., image and video data) captures the three-dimensional space from multiple angles, and the multi-sensory experience generation system 410 can stitch the multiple angles together to generate a three-dimensional model of each element in the space, which can be further enhanced with sensor data, which, for example, provides more detailed spatial information for each element of the three-dimensional space. Therefore, the multi-sensory experience generation system 410 can aggregate, process, and enhance image, audio, video, and sensor data from the cameras and sensors to generate volumetric content that can be presented by an AR device (e.g., glasses 200) as part of an AR experience.

[0101] Figure 5is a diagrammatic representation of a data structure 500 as maintained in database 120, according to some examples. While the contents of database 120 are shown as including several tables, it will be appreciated that data may be stored in other types of data structures (eg, as an object-oriented database).

[0102] The entity table 504 stores entity data and is linked (e.g., by reference) to the entity graph 506 and profile data 508. The entities whose records are maintained within the entity table 504 may include individuals, corporate entities, organizations, objects, places, events, etc. Regardless of the entity type, any entity about which the presence server system 108 stores data may be an identified entity. Each entity is provided with a unique identifier as well as an entity type identifier (not shown). The entity table 504 may associate various enhancements from the enhancement table 510 with various images and videos stored in the image table 516 and the video table 514.

[0103] Entity graph 506 stores information about relationships and associations between entities. Such relationships may be social, professional (e.g., working in a common company or organization), interest-based, or activity-based, by way of example only.

[0104] The profile data 508 stores various types of profile data about a particular entity. Based on the privacy settings specified by the particular entity, the profile data 508 can be selectively used and presented to other users of the volumetric content presentation system 100. In the case where the entity is a person, the profile data 508 includes, for example, a user name, a phone number, an address, settings (e.g., notification and privacy settings), and an avatar representation (or a collection of such avatar representations) selected by the user.

[0105] The database 120 also stores augmentation data, such as overlays including AR content items and filters, in augmentation table 510. The augmentation data is associated with and applied to videos (whose data is stored in video table 514) and images (whose data is stored in image table 516), including volumetric videos and images.

[0106] The story table 512 stores data about a collection of content including associated image, video or audio data that is compiled into a collection (e.g., a story or gallery). The creation of a particular collection can be initiated by a particular user (e.g., each user whose record is saved in the entity table 504). A user can create a "personal story" in the form of a collection of content that has been created and sent / broadcasted by the user. To this end, the user interface of the presentation client 104 may include an icon that is user-selectable to enable the sending user to add specific content to his or her personal story.

[0107] As mentioned above, the video table 514 stores video data including volumetric videos. Similarly, the image table 516 stores image data including volumetric images.

[0108] In addition, the database 120 may also store device state data in a device state table 518. The device state data describes the state of a network-connected device. Depending on the device, the device state data may specify, for example, a configuration of the device as controlled by one or more device settings, secondary content, or navigation data. Entries in the device state table 518 may be associated with videos (whose data is stored in the video table 514) and images (whose data is stored in the image table 516), including volumetric videos and images. For example, as will be discussed in further detail below, the volumetric content presentation system 100 may associate the device state data with the volumetric content when generating experience data to remember the user's experience.

[0109] Figures 6 to 8 6 is a flowchart illustrating the operation of the volumetric content rendering system 100 in accordance with an example embodiment when performing a method 600 for rendering volumetric video. The method 600 may be embodied in computer-readable instructions for execution by one or more processors, such that the operations of the method 600 may be performed in part or in whole by functional components of the volumetric content rendering system 100; therefore, the method 600 is described below by way of example with reference thereto. However, it should be understood that at least some of the operations of the method 600 may be deployed on various other hardware configurations other than the volumetric content rendering system 100.

[0110] At operation 605, the volumetric content presentation system 100 generates experience data to memorize the user's experience recorded using the volumetric capture technology. The experience data includes volumetric content and device state data associated with the volumetric content. The volumetric content corresponds to a volumetric capture of the user's experience and includes a volumetric representation of one or more elements of the real-world three-dimensional space during the user's experience. That is, the volumetric representation includes at least one content item (e.g., an AR content item) corresponding to a person or object in the three-dimensional space. The device state data describes the state of one or more network-connected devices (e.g., one or more network-connected devices 130) associated with the real-world three-dimensional space.

[0111] For some embodiments, the generation of experience data includes: generating volumetric content. For example, the volumetric content rendering system 100 can generate volumetric content by stitching together various video, image, audio, and sensor data generated by known volumetric capture techniques. The video, image, audio, and sensor data are provided by a user to the volumetric content rendering system 100, for example, as part of a request to generate volumetric content. For some embodiments, the request to generate volumetric content can include device state data associated with the volumetric content. For some embodiments, the request to generate volumetric content includes login credentials for accessing the device state data (e.g., directly from a network-connected device or a third-party network service).

[0112] As described above, the one or more network-connected devices may include, for example, any one or more of the following: a smart light or bulb, a thermostat, a navigation device, a smart television, a smart speaker, a smart switch, or a smart appliance (e.g., a washer, dryer, stove, and microwave). The device state data may include the state of one or more devices in a real-world three-dimensional space or a portion of the same environment as the real-world three-dimensional space. For example, the real-world three-dimensional space may be a room within a house, and the network-connected device for which device state data exists in the experience data may be located within the room or outside the room, but within the house. In general, the device state data may include the state of any device for which operation or output may be observed within the real-world three-dimensional space. The device state data may include the state of the network-connected device during the volumetric capture of the user's experience, or include a user-specified device state for association with volumetric content.

[0113] At operation 610, the volumetric content presentation system 100 stores the experience data in a network accessible data store (eg, database 120). The network accessible data store may include a collection of experience data that may include the user's experience data and other users' experience data that is allowed to be accessed by the user.

[0114] At operation 615, the volumetric content presentation system 100 provides an interactive interface to the display device (e.g., glasses 200) that allows the user to select a volumetric content set of volumetric content for presentation. The set of volumetric content includes at least the volumetric content included in the experience data generated at operation 605, and may also include other volumetric content that may correspond to other experience data in the set of experience data accessible by the user. At operation 620, the volumetric content presentation system 100 receives input indicating a selection of volumetric content for presentation.

[0115] In response to the selection of the volumetric content for presentation, the volumetric content presentation system 100 accesses the device state data in the experience data (operation 625) and causes the volumetric content to be presented (operation 630). To cause the volumetric content to be presented, the volumetric content presentation system 100 causes the display device to present the volumetric content (at operation 635) and configures one or more network-connected devices using the device state data (operation 640).

[0116] For some embodiments, the display device is an augmented reality device (e.g., glasses 200), and the presentation of volumetric content may include displaying one or more AR content items superimposed on a real-world space, which may be the same as or a different space from the three-dimensional space in which the volumetric video is captured. The presentation of volumetric content may include displaying one or more content items in motion, displaying one or more content items performing movement or other actions, displaying one or more content items statically positioned, or a combination thereof. The content items may be displayed for the duration of the presentation of the volumetric content or a portion of the volumetric content.

[0117] The presentation of volumetric content may also include tracking the position and movement of the user within their physical real-world environment, and using the tracked position and movement of the user to allow the user to move around in and interact with the presentation of the volumetric content. Thus, the presentation of volumetric content may include displaying content items from multiple perspectives based on the user's movement and changes in position. The presentation of volumetric content may be based on any one or more of the motion and positioning components from the display device, a primary device to which the display device is a complementary device, or a complementary device (e.g., a smartwatch) that communicates with the display device (examples of which are described below with reference to Fig.10 further described in detail) to track the user's location and movements.

[0118] The volumetric content may also include audio data including one or more audio signals, and thus, rendering of the volumetric content may include rendering the one or more audio signals.

[0119] As described above, the device state data may include the state of the network-connected device during the volumetric capture of the user experience. Thus, in some cases, configuring one or more network-connected devices includes: configuring the network-connected device according to the state of the network-connected device during the volumetric capture of the user experience to place the device in the same state as when the user experience occurred. Examples of using the device state data to configure the network-connected device include: setting the temperature of a smart thermostat; causing a navigation device to display a navigation path; causing a smart TV to play a movie or other secondary video content; causing a smart speaker to play a song; causing a smart coffee maker to brew coffee; placing a smart lock in a locked state or an unlocked state; causing a smart dishwasher or washing machine to start a cycle; turning smart lights on or off; dimming smart lights; starting, stopping, or changing the speed of a smart fan; and causing a smart door to open or close.

[0120] Additional details of configuring one or more network connection devices are discussed below.

[0121] like Figure 7 As shown, in some embodiments, method 600 may include operation 705 and operation 710. Consistent with these embodiments, operation 705 may be performed as part of operation 605, at which operation 605, the volumetric content rendering system 100 generates experience data. At operation 705, the volumetric content rendering system 100 determines the state of the network-connected device during the volumetric capture of the user's experience. In other words, the volumetric content rendering system 100 determines the state of the network-connected device when the volumetric content is captured. For some devices, the state of the device corresponds to a specific state of the device. For example, the device state data may, for example, include one or more device settings of the network-connected device. For some devices, the device state data may include map or location data, for example, including data defining a path or route between two locations. The volumetric content rendering system 100 may determine the state in real time when performing the volumetric capture or determine the state after the volumetric capture.

[0122] As shown, upon determining the state of the network-connected device, the volumetric content rendering system 100 may perform any of operations 706 and 707. At operation 706, the volumetric content rendering system 100 sends a request for device state data to the network-connected device or a network service associated with the network-connected device over a network (e.g., via an API of the device or the network service). At operation 707, the volumetric content rendering system 100 collects sensor data from one or more sensors associated with the real-world three-dimensional space. For example, the one or more sensors may include an embedded sensor of the network-connected device, a sensor communicatively coupled to the network-connected device, or a sensor in the real-world three-dimensional space or an associated real-world environment that is capable of sensing one or more aspects of the operation of the network-connected device.

[0123] Consistent with these embodiments, operation 710 may be performed as part of operation 635, where the volumetric content rendering system 100 configures one or more network-connected devices. At operation 710, the volumetric content rendering system 100 sends a command to a network-connected device or a network service associated with the network-connected device over a network to configure the device according to the state of the device when the volumetric content was captured, so that the network-connected device is configured to the same state as when the user experience occurred. As described above, the state of the device may include one or more device settings, and thus, configuring the network-connected device may include applying the one or more device settings to the network-connected device.

[0124] like Figure 8 As shown, in some embodiments, method 600 may include operation 805 and operation 810. Consistent with these embodiments, operation 805 may be performed as part of operation 605, where the volumetric content rendering system 100 generates experience data. At operation 805, the volumetric content rendering system 100 identifies secondary content associated with the volumetric content. The secondary content may include any one or more of audio, image, or video content, the rendering of which is observable in the real-world three-dimensional space during the volumetric capture of the user's experience.

[0125] For some embodiments, the volumetric content rendering system 100 identifies the secondary content based on an analysis of the volumetric content. For some embodiments, the volumetric content rendering system 100 identifies the secondary content based on a user input including an identifier of the secondary content. For some embodiments, the volumetric content rendering system 100 identifies the secondary content by sending one or more requests via a network to a network-connected media device (e.g., a smart TV or other network-connected display device or a smart speaker or other network-connected audio device) or a network service associated with the network-connected media device (e.g., via an API of the device or the network service).

[0126] Consistent with these embodiments, operation 810 may be performed as part of operation 635, where the volumetric content rendering system 100 configures one or more network-connected devices as part of the rendering of the volumetric content. At operation 810, the volumetric content rendering system 100 causes a network-connected media device to render the secondary content. The network-connected media device may be the same media device that rendered the secondary content during volumetric capture, or a different media device capable of rendering the secondary content. For example, the volumetric content rendering system 100 may cause the network-connected media device to render the secondary content by sending one or more commands to the network-connected media device or a network service associated with the network-connected media device via a network. By causing the network-connected device to render the secondary content along with rendering the volumetric content, the volumetric content rendering system 100 can provide a re-creation of the user experience.

[0127] Software Architecture

[0128] Fig. 9 is a block diagram illustrating an example software architecture 906 that may be used in conjunction with the various hardware architectures described herein. Fig. 9 is a non-limiting example of a software architecture, and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. Software architecture 906 may be implemented in a system such as Fig.10 1000, which includes a processor 1004, a memory / storage device 1006, an I / O component 1018, etc. A representative hardware layer 952 is shown and the representative hardware layer 952 may represent, for example Fig.10 The machine 1000 of the embodiment of the present invention. The representative hardware layer 952 layer includes a processing unit 954 having associated executable instructions 904. The executable instructions 904 represent executable instructions of the software architecture 906, including implementations of the methods, components, etc. described herein. The hardware layer 952 also includes a memory and / or storage module 956 also having executable instructions 904. The hardware layer 952 may also include other hardware 958.

[0129] exist Fig. 9In the example architecture shown, software architecture 906 can be conceptualized as a layer stack, wherein each layer provides specific functionality. For example, software architecture 906 may include layers such as operating system 902, library 920, framework / middleware 918, application 916, and presentation layer 914. In operation, application 916 and / or other components within the layer may activate API call 908 through the software stack and receive a response to API call 908 as message 912. The layers shown are representative in nature, and not all software architectures have all layers. For example, some mobile or dedicated operating systems may not provide framework / middleware 918, while other operating systems may provide such layers. Other software architectures may include additional or different layers.

[0130] The operating system 902 can manage hardware resources and provide general services. The operating system 902 may include, for example, a kernel 922, a service 924, and a driver 926. The kernel 922 may serve as an abstraction layer between the hardware layer and other software layers. For example, the kernel 922 may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, etc. The service 924 may provide other public services for other software layers. The driver 926 is responsible for controlling or interfacing with the underlying hardware. For example, depending on the hardware configuration, the driver 926 includes a display driver, a camera driver, drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Drivers, audio drivers, power management drivers, etc.

[0131] The library 920 provides a common infrastructure used by the application 916 and / or other components and / or layers. The library 920 provides functions that allow other software components to perform tasks in an easier way than directly interfacing with the underlying operating system 902 functions (e.g., core 922, service 924, and / or driver 926). The library 920 may include a system library 944 (e.g., a C standard library), which may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, etc. In addition, the library 920 may include an API library 946, such as a media library (e.g., a library for supporting the presentation and manipulation of various media formats such as MPEG4, H.294, MP3, AAC, AMR, JPG, and PNG), a graphics library (e.g., an OpenGL framework that can be used to render 2D and 3D graphics content on a display), a database library (e.g., SQLite that can provide various relational database functions), a web library (e.g., WebKit that can provide web browsing functions), etc. The library 920 may also include various other libraries 948 to provide many other APIs to the application 916 and other software components / modules.

[0132] The framework / middleware 918 provides a higher level common infrastructure that can be used by the applications 916 and / or other software components / modules. For example, the framework / middleware 918 can provide various GUI functions, advanced resource management, advanced location services, etc. The framework / middleware 918 can provide a wide range of other APIs that can be utilized by the applications 916 and / or other software components / modules, some of which can be specific to a particular operating system 902 or platform.

[0133] Applications 916 include built-in applications 938 and / or third-party applications 940. Examples of representative built-in applications 938 may include, but are not limited to, contact applications, browser applications, book reader applications, location applications, media applications, messaging applications, and / or game applications. Third-party applications 940 may include applications that are developed by entities other than the vendor of a particular platform using ANDROID TM or IOS TM Software Development Kit (SDK) for developing applications and can be used on platforms such as IOS TM ANDROID TM , Mobile software running on the mobile operating system of the phone or other mobile operating systems. The third-party application 940 can call API calls 908 provided by the mobile operating system (such as the operating system 902) to facilitate the functions described herein.

[0134] Applications 916 may create user interfaces to interact with users of the system using built-in operating system functionality (e.g., kernels 922, services 924, and / or drivers 926), libraries 920, and framework / middleware 918. Alternatively or additionally, in some systems, interaction with the user may occur through a presentation layer such as presentation layer 914. In these systems, the application / component "logic" may be separated from aspects of the application / component that interact with the user.

[0135] Fig.10 1 is a block diagram illustrating components of a machine 1000 capable of reading instructions from a machine-readable medium (e.g., a machine-readable storage medium) and performing any one or more of the methods discussed herein, according to some example embodiments. Specifically, Fig.10A graphical representation of a machine 1000 in the example form of a computer system is shown, within which instructions 1010 (e.g., software, programs, applications, applet, app, or other executable code) for causing the machine 1000 to perform any one or more of the methods discussed herein may be executed. Thus, the instructions 1010 may be used to implement the modules or components described herein. The instructions 1010 transform a general unprogrammed machine 1000 into a specific machine 1000 that is programmed to perform the functions described and shown in the described manner. In alternative embodiments, the machine 1000 operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine 1000 may operate with the performance of a server machine or a client machine in a server-client network environment, or operate as a peer machine in a peer-to-peer (or distributed) network environment. The machine 1000 may include, but is not limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a PDA, an entertainment media system, a cellular phone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web device, a network router, a network switch, a network bridge, or any machine capable of executing instructions 1010, either sequentially or otherwise, that specify actions to be taken by the machine 1000. Furthermore, while only a single machine 1000 is shown, the term “machine” should also be taken to include a collection of machines that individually or jointly execute instructions 1010 to perform any one or more of the methodologies discussed herein.

[0136] The machine 1000 may include a processor 1004, a memory / storage device 1006, and an I / O component 1018, which may be configured to communicate with each other, for example, via a bus 1002. In an example embodiment, the processor 1004 (e.g., a CPU, a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a GPU, a digital signal processor (DSP), an ASIC, a radio frequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 1008 and a processor 1009 that may execute instructions 1010. Although Fig.10 Multiple processors 1004 are shown, but the machine 1000 may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiple cores, or any combination thereof.

[0137] The memory / storage 1006 may include a memory 1012, such as a main memory or other storage device, and a storage unit 1014, both of which are accessible to the processor 1004, for example, via the bus 1002. The storage unit 1014 and the memory 1012 store instructions 1010 that embody any one or more of the methods or functions described herein. During execution of the instructions 1010 by the machine 1000, the instructions 1010 may also reside, completely or partially, within the memory 1012, within the storage unit 1014, within at least one of the processors 1004 (e.g., within a cache memory of a processor), or within any suitable combination thereof. Thus, the memory 1012, the storage unit 1014, and the memory of the processor 1004 are examples of machine-readable media.

[0138] The I / O components 1018 may include various components for receiving input, providing output, generating output, transmitting information, exchanging information, capturing measurements, etc. The specific I / O components 1018 included in a particular machine 1000 will depend on the type of machine. For example, a portable machine such as a mobile phone will likely include a touch input device or other such input mechanism, while a headless server machine will likely not include such a touch input device. It should be understood that the I / O components 1018 may include Fig.10 1028. The I / O components 1018 are grouped according to function only to simplify the following discussion, and the grouping is by no means limiting. In various example embodiments, the I / O components 1018 may include output components 1026 and input components 1028. The output components 1026 may include visual components (e.g., displays such as plasma display panels (PDPs), light emitting diode (LED) displays, liquid crystal displays (LCDs), projectors, or cathode ray tubes (CRTs)), acoustic components (e.g., speakers), tactile components (e.g., vibration motors, resistance mechanisms), other signal generators, etc. The input components 1028 may include alphanumeric input components (e.g., keyboards, touch screens configured to receive alphanumeric input, optical keyboards, or other alphanumeric input components), point-based input components (e.g., mice, touch pads, trackballs, joysticks, motion sensors, or other pointing instruments), touch input components (e.g., physical buttons, touch screen displays or other touch input components that provide location and / or force of touch or touch gestures), audio input components (e.g., microphones), etc.

[0139] In other example embodiments, the I / O component 1018 may include a biometric component 1030, a motion component 1034, an environmental component 1036, or a positioning component 1038, as well as various other components. For example, the biometric component 1030 may include a component for detecting expressions (e.g., hand expressions, facial expressions, voice expressions, body postures, or eye tracking), measuring biosignals (e.g., blood pressure, heart rate, body temperature, sweating, or brain waves), identifying a person (e.g., voice recognition, retinal recognition, facial recognition, fingerprint recognition, or EEG-based recognition), etc. The motion component 1034 may include an acceleration sensor component (e.g., an accelerometer), a gravity sensor component, a rotation sensor component (e.g., a gyroscope), etc. The environment component 1036 may include, for example, an illumination sensor component (e.g., a photometer), a temperature sensor component (e.g., one or more thermometers that detect ambient temperature), a humidity sensor component, a pressure sensor component (e.g., a barometer), an auditory sensor component (e.g., one or more microphones that detect background noise), a proximity sensor component (e.g., an infrared sensor that detects nearby objects), a gas sensor (e.g., a gas sensor that detects concentrations of hazardous gases for safety reasons or measures pollutants in the atmosphere), or other components that can provide indications, measurements, or signals corresponding to the surrounding physical environment. The positioning component 1038 may include a position sensor component (e.g., a global positioning system (GPS) receiver component), an altitude sensor component (e.g., an altimeter or barometer that detects air pressure, from which the altitude can be obtained), an orientation sensor component (e.g., a magnetometer), etc.

[0140] Various technologies may be used to implement communications. I / O components 1018 may include communications components 1040 operable to couple machine 1000 to network 1032 or device 1020 via coupling 1024 and coupling 1022, respectively. For example, communications components 1040 may include a network interface component or other suitable device to interface with network 1032. In other examples, communications components 1040 may include wired communications components, wireless communications components, cellular communications components, near field communications (NFC) components, Parts (e.g. Low energy consumption), Device 1020 may be another machine or any of a variety of peripheral devices (eg, a peripheral device coupled via USB).

[0141] In addition, the communication component 1040 can detect the identifier or can include a component that is operable to detect the identifier. For example, the communication component 1040 can include a radio frequency identification (RFID) tag reader component, an NFC smart tag detection component, an optical reader component (e.g., an optical sensor for detecting one-dimensional bar codes such as universal product codes (UPC) bar codes, multi-dimensional bar codes such as quick response (QR) codes, Aztec codes, data matrix, data symbols (Dataglyph), MaxiCode, PDF4114, Ultra Code, UCC RSS-2D bar codes, and other optical codes) or an acoustic detection component (e.g., a microphone for identifying tagged audio signals). In addition, various information can be obtained via the communication component 1040, such as location via Internet Protocol (IP) geolocation, ... Signal triangulation to obtain location, location obtained via detection of NFC beacon signals that can indicate a specific location, etc.

[0142] Glossary

[0143] "Carrier signal" in this context refers to any intangible medium capable of storing, encoding or carrying instructions for execution by a machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such instructions. Instructions may be sent or received over a network using a transmission medium via a network interface device and using any of a number of well-known transmission protocols.

[0144] A "client device" in this context refers to any machine that interfaces with a communication network to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, a desktop computer, a laptop computer, a PDA, a smart phone, a tablet computer, an ultrabook, a netbook, a laptop computer, a multiprocessor system, a microprocessor-based or programmable consumer electronics system, a game console, a set-top box, or any other communication device that a user may use to access a network.

[0145] A "communication network" in this context refers to one or more parts of a network, which may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a part of the Internet, a part of the public switched telephone network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, A network, another type of network, or a combination of two or more such networks. For example, the network or a portion of the network may include a wireless or cellular network, and the coupling to the network may be a code division multiple access (CDMA) connection, a global system for mobile communications (GSM) connection, or another type of cellular or wireless coupling. In this example, the coupling may implement any of various types of data transmission technologies, such as single carrier radio transmission technology (1xRTT), evolution data optimized (EVDO) technology, general packet radio service (GPRS) technology, enhanced data rate for GSM evolution (EDGE) technology, including 3G third generation partnership project (3GPP), fourth generation wireless (4G) network, universal mobile telecommunications system (UMTS), high speed packet access (HSPA), world wide interoperability for microwave access (WiMAX), long term evolution (LTE) standard, other standards defined by various standard setting organizations, other remote protocols or other data transmission technologies.

[0146] "Machine-readable medium" in this context refers to a component, device, or other tangible medium capable of temporarily or permanently storing instructions and data, and may include, but is not limited to, random access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage devices (e.g., erasable programmable read-only memory (EPROM)), and / or any suitable combination thereof. The term "machine-readable medium" should be deemed to include a single medium or multiple media capable of storing instructions (e.g., centralized or distributed databases or associated caches and servers). The term "machine-readable medium" should also be deemed to include any medium or combination of multiple media capable of storing instructions (e.g., code) for machine execution, such that the instructions, when executed by one or more processors of the machine, cause the machine to perform any one or more of the methods described herein. Thus, "machine-readable medium" refers to a single storage device or device as well as a "cloud-based" storage system or storage network comprising multiple storage devices or devices. The term "machine-readable medium" does not include the signal itself.

[0147] A "component" in this context refers to a logical or device, physical entity having boundaries defined by function or subroutine calls, branch points, APIs, or other techniques that provide partitioning or modularization of a particular processing or control function. A component may be combined with other components via its interfaces to perform a machine process. A component may be a packaged functional hardware unit designed for use with other components and as part of a program that typically performs a specific function of related functions. A component may constitute a software component (e.g., code implemented on a machine-readable medium) or a hardware component.

[0148] A "hardware component" is a tangible unit that can perform certain operations and can be configured or arranged in a physical manner. In various example embodiments, one or more computer systems (e.g., an independent computer system, a client computer system, or a server computer system) or one or more hardware components (e.g., a processor or a processor group) of a computer system can be configured by software (e.g., an application or an application part) to be a hardware component that operates to perform certain operations as described herein. The hardware components can also be implemented mechanically, electronically, or in any suitable combination thereof. For example, a hardware component may include a dedicated circuit system or logic that is permanently configured to perform certain operations. The hardware component may be a dedicated processor, such as a field programmable gate array (FPGA) or an ASIC. The hardware component may also include a programmable logic or circuit system that is temporarily configured to perform certain operations by software. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor.

[0149] Once configured by such software, the hardware component becomes a specific machine (or specific component of a machine) that is uniquely customized to perform the configured functions and is no longer a general-purpose processor. It should be understood that it may be decided for cost and time considerations whether to mechanically implement the hardware component in a dedicated and permanently configured circuit system or in a temporarily configured (e.g., configured by software) circuit system. Therefore, the phrase "hardware component" (or "hardware-implemented component") should be understood to include a tangible entity, that is, an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily configured (e.g., programmed) to operate in a certain manner or perform certain operations described herein.

[0150] Considering implementations where hardware components are temporarily configured (e.g., programmed), it is not necessary to configure or instantiate each of the hardware components at any one time in a timely manner. For example, where the hardware components include a general-purpose processor that is configured by software to be a special-purpose processor, the general-purpose processor can be configured to be a different special-purpose processor (e.g., including different hardware components) at different times. For example, software configures one or more specific processors accordingly to constitute a specific hardware component at one time and to constitute different hardware components at different times.

[0151] Hardware components can provide information to other hardware components and can receive information from other hardware components. Therefore, the described hardware components can be considered to be communicatively coupled. In the case of multiple hardware components simultaneously, communication can be achieved by signal transmission between two or more hardware components in the hardware components (e.g., by appropriate circuits and buses). In an embodiment in which multiple hardware components are configured or instantiated at different times, communication between such hardware components can be achieved, for example, by storing information in a memory structure accessed by multiple hardware components and retrieving information in the memory structure. For example, a hardware component can perform an operation and store the output of the operation in a memory device to which it is communicatively coupled. Then, other hardware components can access the memory device at a subsequent time to retrieve the stored output and process it. Hardware components can also initiate communication with an input device or an output device, and can operate on resources (e.g., a collection of information).

[0152] The various operations of the example methods described herein may be performed at least in part by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the related operations. Whether temporarily configured or permanently configured, such a processor may constitute a processor-implemented component that operates to perform one or more operations or functions described herein. As used herein, "processor-implemented components" refer to hardware components implemented using one or more processors. Similarly, the methods described herein may be implemented at least in part by a processor, wherein a specific one or more processors are examples of hardware. For example, at least some of the operations of the method may be performed by one or more processors or processor-implemented components.

[0153] In addition, one or more processors may also operate to support the execution of related operations in a "cloud computing" environment or operate as "software as a service" (SaaS). For example, at least some operations may be performed by a group of computers (as an example of a machine including a processor), where these operations can be accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., application programming interface (API)). The execution of certain operations in the operation may be distributed between processors, not just resident in a single machine, but deployed across several machines. In some example embodiments, the processor or the component implemented by the processor may be located in a single geographic location (e.g., in a home environment, an office environment, or a server cluster). In other example embodiments, the processor or the component implemented by the processor may be distributed across several geographic locations.

[0154] A "processor" in this context refers to any circuit or virtual circuit (a physical circuit simulated by logic executed on an actual processor) that manipulates data values ​​according to control signals (e.g., "commands," "opcodes," "machine codes," etc.) and produces corresponding output signals that are applied to operate a machine. For example, a processor may be a CPU, a RISC processor, a CISC processor, a GPU, a DSP, an ASIC, an RFIC, or any combination thereof. A processor may also be a multi-core processor having two or more independent processors (sometimes referred to as "cores") that can execute instructions simultaneously.

[0155] A "timestamp" in this context refers to a sequence of characters or coded information that identifies when some event occurred, for example, thereby giving a date and time of day, sometimes accurate to a fraction of a second.

Claims

1. A method comprising: receiving input indicating a selection of volumetric content for presentation, the volumetric content comprising a volumetric representation of one or more elements of a real-world three-dimensional space; In response to the input, accessing device state data associated with the volumetric content, the device state data describing a state of one or more network-connected devices associated with the real-world three-dimensional space; as well as causing presentation of the volumetric content, causing presentation of the volumetric content to include: causing a volumetric representation of the one or more elements to be presented superimposed on the real-world three-dimensional space by a display device distinct from the one or more network-connected devices; as well as The one or more network-connected devices are configured using the device status data.

2. The method according to claim 1, further comprising: A data record is generated, the data record comprising the volume contents and the device status data.

3. The method according to claim 2, wherein: Generating the data record includes determining a state of the one or more network-connected devices when the volumetric content was captured.

4. The method according to claim 3, wherein: Determining the status of the one or more network-connected devices includes sending a request for the status data to a network-connected device or a network service associated with the network-connected device over a network.

5. The method according to claim 3, wherein: Determining a status of the one or more network-connected devices includes collecting sensor data from one or more sensors associated with the real-world three-dimensional space.

6. The method according to claim 1, wherein: At least one of the one or more network-connected devices is located within the real-world three-dimensional space.

7. The method according to claim 1, wherein: Configuring the one or more network-connected devices includes configuring the network-connected devices according to a state of the network-connected devices when the volumetric content was captured.

8. The method according to claim 1, wherein: Configuring the one or more network connection devices includes sending commands over a network to the network connection devices or a network service associated with the network connection devices.

9. The method according to claim 1, further comprising: Secondary content is identified that was presented within the real-world three-dimensional space when the volumetric content was captured, wherein configuring the one or more network-connected devices includes causing presentation of the secondary content by a media device.

10. The method of claim 1, wherein: The device status data includes one or more device settings of the network-connected device; as well as Configuring the one or more network connection devices includes applying the one or more device settings to the network connection devices.

11. A system comprising: one or more hardware processors; as well as At least one memory storing instructions that cause the one or more hardware processors to perform operations comprising: receiving input indicating a selection of volumetric content for presentation, the volumetric content comprising a volumetric representation of one or more elements of a real-world three-dimensional space; In response to the input, accessing device state data associated with the volumetric content, the device state data describing a state of one or more network-connected devices associated with the real-world three-dimensional space; and causing presentation of the volumetric content, causing presentation of the volumetric content to include: causing a volumetric representation of the one or more elements superimposed on the real-world three-dimensional space to be presented by a display device distinct from the one or more network-connected devices; and The one or more network-connected devices are configured using the device status data.

12. The system according to claim 11, wherein: The operations also include generating a data record including the volume contents and the device status data.

13. The system according to claim 12, wherein: Generating the data record includes determining a state of the one or more network-connected devices when the volumetric content was captured.

14. The system according to claim 13, wherein: Determining the status of the one or more network-connected devices includes sending a request for the status data to a network-connected device or a network service associated with the network-connected device over a network.

15. The system of claim 13, wherein: Determining a status of the one or more network-connected devices includes collecting sensor data from one or more sensors associated with the real-world three-dimensional space.

16. The system of claim 13, wherein: At least one of the one or more network-connected devices is located within the real-world three-dimensional space.

17. The system of claim 13, wherein: Configuring the one or more network-connected devices includes configuring the network-connected devices according to a state of the network-connected devices when the volumetric content was captured.

18. The system of claim 11, wherein: Configuring the one or more network connection devices includes sending commands over a network to the network connection devices or a network service associated with the network connection devices.

19. The system of claim 11, wherein: The operations further include identifying secondary content that was presented within the real-world three-dimensional space when the volumetric content was captured, wherein configuring the at least one network-connected device includes causing presentation of the secondary content by a media device.

20. A machine-readable medium storing instructions that, when executed by a computer system, cause the computer system to perform operations comprising: receiving input indicating a selection of volumetric content for presentation, the volumetric content comprising a volumetric representation of one or more elements of a real-world three-dimensional space; In response to the input, accessing device state data associated with the volumetric content, the device state data describing a state of one or more network-connected devices associated with the real-world three-dimensional space; as well as causing presentation of the volumetric content, causing presentation of the volumetric content to include: causing a volumetric representation of the one or more elements to be presented superimposed on the real-world three-dimensional space by a display device distinct from the one or more network-connected devices; as well as The one or more network-connected devices are configured using the device status data.

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