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WO2025153195A1 - Représentation multimédia d'avatar pour une transmission - Google Patents

Représentation multimédia d'avatar pour une transmission

Info

Publication number
WO2025153195A1
WO2025153195A1 PCT/EP2024/078231 EP2024078231W WO2025153195A1 WO 2025153195 A1 WO2025153195 A1 WO 2025153195A1 EP 2024078231 W EP2024078231 W EP 2024078231W WO 2025153195 A1 WO2025153195 A1 WO 2025153195A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
avatar
type
decoded
processor
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/EP2024/078231
Other languages
English (en)
Inventor
João Pedro COVA REGATEIRO
Philippe Henri GOSSELIN
Quentin AVRIL
Francois Le Clerc
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
InterDigital CE Patent Holdings SAS
Original Assignee
InterDigital CE Patent Holdings SAS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by InterDigital CE Patent Holdings SAS filed Critical InterDigital CE Patent Holdings SAS
Publication of WO2025153195A1 publication Critical patent/WO2025153195A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/46—Embedding additional information in the video signal during the compression process
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/30—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
    • A63F13/31—Communication aspects specific to video games, e.g. between several handheld game devices at close range
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T13/00—Animation
    • G06T13/20—3D [Three Dimensional] animation
    • G06T13/40—3D [Three Dimensional] animation of characters, e.g. humans, animals or virtual beings
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/001—Model-based coding, e.g. wire frame
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/002—Image coding using neural networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/20—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/20—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
    • H04N19/23—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding with coding of regions that are present throughout a whole video segment, e.g. sprites, background or mosaic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/597—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
    • A63F2300/55—Details of game data or player data management
    • A63F2300/5546—Details of game data or player data management using player registration data, e.g. identification, account, preferences, game history
    • A63F2300/5553—Details of game data or player data management using player registration data, e.g. identification, account, preferences, game history user representation in the game field, e.g. avatar
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/80—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game specially adapted for executing a specific type of game
    • A63F2300/8082—Virtual reality

Definitions

  • the data type is one of a data set including: video data, image data, mesh data, and game data.
  • An eighth example apparatus in accordance with some embodiments may include a computer- readable medium storing instructions for causing one or more processors to perform any one of the methods listed above.
  • a ninth example apparatus in accordance with some embodiments may include: at least one processor and at least one non-transitory computer-readable medium storing instructions for causing the at least one processor to perform any one of the methods listed above.
  • FIG. 11 is a process diagram illustrating an example artificial intelligence avatar media stream process according to some embodiments.
  • FIG. 12 is a process diagram illustrating an example encoder architecture according to some embodiments.
  • FIG. 13 is a process diagram illustrating an example decoder architecture according to some embodiments.
  • FIG. 14 is a flowchart illustrating an example process for encoding avatar data according to some embodiments.
  • FIG. 15 is a flowchart illustrating an example process for decoding avatar data according to some embodiments.
  • FIG. 1A is a diagram illustrating an example communications system 100 in which one or more disclosed embodiments may be implemented.
  • the communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users.
  • the communications system 100 may enable multiple wireless users to access such content through the sharing of system resources, including wireless bandwidth.
  • the communications systems 100 may employ one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), zero-tail unique-word DFT-Spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block-filtered OFDM, filter bank multicarrier (FBMC), and the like.
  • CDMA code division multiple access
  • TDMA time division multiple access
  • FDMA frequency division multiple access
  • OFDMA orthogonal FDMA
  • SC-FDMA single-carrier FDMA
  • ZT UW DTS-s OFDM zero-tail unique-word DFT-Spread OFDM
  • UW-OFDM unique word OFDM
  • FBMC filter bank multicarrier
  • the communications system 100 may include wireless transmit/receive units (WTRUs) 102a, 102b, 102c, 102d, a RAN 104/113, a ON 106, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112, though it will be appreciated that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and/or network elements.
  • WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and/or communicate in a wireless environment.
  • the WTRUs 102a, 102b, 102c, 102d may be configured to transmit and/or receive wireless signals and may include a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a subscription-based unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a netbook, a personal computer, a wireless sensor, a hotspot or Mi-Fi device, an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (e.g., remote surgery), an industrial device and applications (e.g., a robot and/or other wireless devices operating in an industrial and/or an automated processing chain contexts), a consumer electronics device, a device operating on commercial and/or industrial wireless networks, and the like.
  • UE user equipment
  • PDA personal digital assistant
  • HMD head-mounted display
  • a vehicle a drone
  • the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN).
  • the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR etc.) to establish a picocell or femtocell.
  • the base station 114b may have a direct connection to the Internet 110.
  • the base station 114b may not be required to access the Internet 110 via the CN 106.
  • the RAN 104/113 may be in communication with the CN 106, which may be any type of network configured to provide voice, data, applications, and/or voice over internet protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d.
  • the data may have varying quality of service (QoS) requirements, such as differing throughput requirements, latency requirements, error tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, and the like.
  • QoS quality of service
  • the CN 106 may provide call control, billing services, mobile location-based services, pre-paid calling, Internet connectivity, video distribution, etc., and/or perform high-level security functions, such as user authentication.
  • the processor 118 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker/microphone 124, the keypad 126, and/or the display/touchpad 128 (e.g., a liquid crystal display (LCD) display unit or organic light-emitting diode (OLED) display unit).
  • the processor 118 may also output user data to the speaker/microphone 124, the keypad 126, and/or the display/touchpad 128.
  • the processor 118 may access information from, and store data in, any type of suitable memory, such as the non-removable memory 130 and/or the removable memory 132.
  • the processor 118 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102.
  • location information e.g., longitude and latitude
  • the WTRU 102 may receive location information over the air interface 116 from a base station (e.g., base stations 114a, 114b) and/or determine its location based on the timing of the signals being received from two or more nearby base stations. It will be appreciated that the WTRU 102 may acquire location information by way of any suitable locationdetermination method while remaining consistent with an embodiment.
  • the processor 118 may further be coupled to other peripherals 138, which may include one or more software and/or hardware modules that provide additional features, functionality and/or wired or wireless connectivity.
  • the peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (for photographs and/or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands free headset, a Bluetooth® module, a frequency modulated (FM) radio unit, a digital music player, a media player, a video game player module, an Internet browser, a Virtual Reality and/or Augmented Reality (VR/AR) device, an activity tracker, and the like.
  • FM frequency modulated
  • the WTRU 102 may include a half-duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for either the UL (e.g., for transmission) or the downlink (e.g., for reception)).
  • a half-duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for either the UL (e.g., for transmission) or the downlink (e.g., for reception)).
  • the one or more emulation devices may perform the one or more, including all, functions while not being implemented/deployed as part of a wired and/or wireless communication network.
  • the emulation devices may be utilized in a testing scenario in a testing laboratory and/or a non-deployed (e.g., testing) wired and/or wireless communication network in order to implement testing of one or more components.
  • the one or more emulation devices may be test equipment. Direct RF coupling and/or wireless communications via RF circuitry (e.g., which may include one or more antennas) may be used by the emulation devices to transmit and/or receive data.
  • RF circuitry e.g., which may include one or more antennas
  • FIG. 1 C is a system diagram illustrating an example set of interfaces for a system according to some embodiments.
  • An extended reality display device together with its control electronics, may be implemented for some embodiments.
  • System 150 can be embodied as a device including the various components described below and is configured to perform one or more of the aspects described in this document. Examples of such devices, include, but are not limited to, various electronic devices such as personal computers, laptop computers, smartphones, tablet computers, digital multimedia set top boxes, digital television receivers, personal video recording systems, connected home appliances, and servers. Elements of system 150, singly or in combination, can be embodied in a single integrated circuit (IC), multiple ICs, and/or discrete components.
  • IC integrated circuit
  • the processing and encoder/decoder elements of system 150 are distributed across multiple ICs and/or discrete components.
  • the system 150 is communicatively coupled to one or more other systems, or other electronic devices, via, for example, a communications bus or through dedicated input and/or output ports.
  • the system 150 is configured to implement one or more of the aspects described in this document.
  • the system 150 includes at least one processor 152 configured to execute instructions loaded therein for implementing, for example, the various aspects described in this document.
  • Processor 152 may include embedded memory, input output interface, and various other circuitries as known in the art.
  • the system 150 includes at least one memory 154 (e.g., a volatile memory device, and/or a non-volatile memory device).
  • System 150 may include a storage device 158, which can include non-volatile memory and/or volatile memory, including, but not limited to, Electrically Erasable Programmable Read-Only Memory (EEPROM), Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Random Access Memory (RAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), flash, magnetic disk drive, and/or optical disk drive.
  • the storage device 158 can include an internal storage device, an attached storage device (including detachable and non-detachable storage devices), and/or a network accessible storage device, as non-limiting examples.
  • System 150 includes an encoder/decoder module 156 configured, for example, to process data to provide an encoded video or decoded video, and the encoder/decoder module 156 can include its own processor and memory.
  • the encoder/decoder module 156 represents module(s) that can be included in a device to perform the encoding and/or decoding functions. As is known, a device can include one or both of the encoding and decoding modules. Additionally, encoder/decoder module 156 can be implemented as a separate element of system 150 or can be incorporated within processor 152 as a combination of hardware and software as known to those skilled in the art.
  • Program code to be loaded onto processor 152 or encoder/decoder 156 to perform the various aspects described in this document can be stored in storage device 158 and subsequently loaded onto memory 154 for execution by processor 152.
  • one or more of processor 152, memory 154, storage device 158, and encoder/decoder module 156 can store one or more of various items during the performance of the processes described in this document. Such stored items can include, but are not limited to, the input video, the decoded video or portions of the decoded video, the bitstream, matrices, variables, and intermediate or final results from the processing of equations, formulas, operations, and operational logic.
  • memory inside of the processor 152 and/or the encoder/decoder module 156 is used to store instructions and to provide working memory for processing that is needed during encoding or decoding.
  • a memory external to the processing device (for example, the processing device can be either the processor 152 or the encoder/decoder module 152) is used for one or more of these functions.
  • the external memory can be the memory 154 and/or the storage device 158, for example, a dynamic volatile memory and/or a non-volatile flash memory.
  • an external non-volatile flash memory is used to store the operating system of, for example, a television.
  • a fast external dynamic volatile memory such as a RAM is used as working memory for video coding and decoding operations, such as for MPEG-2 (MPEG refers to the Moving Picture Experts Group, MPEG-2 is also referred to as ISO/IEC 13818, and 13818-1 is also known as H.222, and 13818-2 is also known as H.262), HEVC (HEVC refers to High Efficiency Video Coding, also known as H.265 and MPEG-H Part 2), or VVC (Versatile Video Coding, a new standard being developed by JVET, the Joint Video Experts Team).
  • MPEG-2 MPEG refers to the Moving Picture Experts Group
  • MPEG-2 is also referred to as ISO/IEC 13818
  • 13818-1 is also known as H.222
  • 13818-2 is also known as H.262
  • HEVC High Efficiency Video Coding
  • VVC Very Video Coding
  • the input to the elements of system 150 can be provided through various input devices as indicated in block 172.
  • Such input devices include, but are not limited to, (i) a radio frequency (RF) portion that receives an RF signal transmitted, for example, over the air by a broadcaster, (ii) a Component (COMP) input terminal (or a set of COMP input terminals), (iii) a Universal Serial Bus (USB) input terminal, and/or (iv) a High Definition Multimedia Interface (HDMI) input terminal.
  • RF radio frequency
  • COMP Component
  • USB Universal Serial Bus
  • HDMI High Definition Multimedia Interface
  • the RF portion of various embodiments includes one or more elements to perform these functions, for example, frequency selectors, signal selectors, band-limiters, channel selectors, filters, downconverters, demodulators, error correctors, and demultiplexers.
  • the RF portion can include a tuner that performs various of these functions, including, for example, downconverting the received signal to a lower frequency (for example, an intermediate frequency or a near-baseband frequency) or to baseband.
  • the RF portion and its associated input processing element receives an RF signal transmitted over a wired (for example, cable) medium, and performs frequency selection by filtering, downconverting, and filtering again to a desired frequency band.
  • Adding elements can include inserting elements in between existing elements, such as, for example, inserting amplifiers and an analog-to-digital converter.
  • the RF portion includes an antenna.
  • the USB and/or HDMI terminals can include respective interface processors for connecting system 150 to other electronic devices across USB and/or HDMI connections.
  • various aspects of input processing for example, Reed-Solomon error correction, can be implemented, for example, within a separate input processing IC or within processor 152 as necessary.
  • aspects of USB or HDMI interface processing can be implemented within separate interface ICs or within processor 152 as necessary.
  • the demodulated, error corrected, and demultiplexed stream is provided to various processing elements, including, for example, processor 152, and encoder/decoder 156 operating in combination with the memory and storage elements to process the datastream as necessary for presentation on an output device.
  • connection arrangement 174 for example, an internal bus as known in the art, including the Inter- IC (I2C) bus, wiring, and printed circuit boards.
  • I2C Inter- IC
  • the system 150 includes communication interface 160 that enables communication with other devices via communication channel 162.
  • the communication interface 160 can include, but is not limited to, a transceiver configured to transmit and to receive data over communication channel 162.
  • the communication interface 160 can include, but is not limited to, a modem or network card and the communication channel 162 can be implemented, for example, within a wired and/or a wireless medium.
  • Data is streamed, or otherwise provided, to the system 150, in various embodiments, using a wireless network such as a Wi-Fi network, for example IEEE 802.11 (IEEE refers to the Institute of Electrical and Electronics Engineers).
  • the Wi-Fi signal of these embodiments is received over the communications channel 162 and the communications interface 160 which are adapted for Wi-Fi communications.
  • the communications channel 162 of these embodiments is typically connected to an access point or router that provides access to external networks including the Internet for allowing streaming applications and other over-the-top communications.
  • Other embodiments provide streamed data to the system 150 using a set-top box that delivers the data over the HDMI connection of the input block 172.
  • Still other embodiments provide streamed data to the system 150 using the RF connection of the input block 172.
  • various embodiments provide data in a non-streaming manner.
  • various embodiments use wireless networks other than Wi-Fi, for example a cellular network or a Bluetooth network.
  • the system 150 can provide an output signal to various output devices, including a display 176, speakers 178, and other peripheral devices 180.
  • the display 176 of various embodiments includes one or more of, for example, a touchscreen display, an organic light-emitting diode (OLED) display, a curved display, and/or a foldable display.
  • the display 176 can be for a television, a tablet, a laptop, a cell phone (mobile phone), or other device.
  • the display 176 can also be integrated with other components (for example, as in a smart phone), or separate (for example, an external monitor for a laptop).
  • the other peripheral devices 180 include, in various examples of embodiments, one or more of a stand-alone digital video disc (or digital versatile disc) (DVR, for both terms), a disk player, a stereo system, and/or a lighting system.
  • Various embodiments use one or more peripheral devices 180 that provide a function based on the output of the system 150. For example, a disk player performs the function of playing the output of the system 150.
  • control signals are communicated between the system 150 and the display 176, speakers 178, or other peripheral devices 180 using signaling such as AV.Link, Consumer Electronics Control (CEC), or other communications protocols that enable device-to-device control with or without user intervention.
  • the output devices can be communicatively coupled to system 150 via dedicated connections through respective interfaces 164, 166, and 168. Alternatively, the output devices can be connected to system 150 using the communications channel 162 via the communications interface 160.
  • the display 176 and speakers 178 can be integrated in a single unit with the other components of system 150 in an electronic device such as, for example, a television.
  • the display interface 164 includes a display driver, such as, for example, a timing controller (T Con) chip.
  • the display 176 and speaker 178 can alternatively be separate from one or more of the other components, for example, if the RF portion of input 172 is part of a separate set-top box.
  • the output signal can be provided via dedicated output connections, including, for example, HDMI ports, USB ports, or COMP outputs.
  • the system 150 may include one or more sensor devices 168.
  • sensor devices that may be used include one or more GPS sensors, gyroscopic sensors, accelerometers, light sensors, cameras, depth cameras, microphones, and/or magnetometers. Such sensors may be used to determine information such as user’s position and orientation.
  • the system 150 is used as the control module for an extended reality display (such as control modules 124, 132)
  • the user’s position and orientation may be used in determining how to render image data such that the user perceives the correct portion of a virtual object or virtual scene from the correct point of view.
  • the position and orientation of the device itself may be used to determine the position and orientation of the user for the purpose of rendering virtual content.
  • other inputs may be used to determine the position and orientation of the user for the purpose of rendering content.
  • a user may select and/or adjust a desired viewpoint and/or viewing direction with the use of a touch screen, keypad or keyboard, trackball, joystick, or other input.
  • the display device has sensors such as accelerometers and/or gyroscopes, the viewpoint and orientation used for the purpose of rendering content may be selected and/or adjusted based on motion of the display device.
  • the embodiments can be carried out by computer software implemented by the processor 152 or by hardware, or by a combination of hardware and software. As a non-limiting example, the embodiments can be implemented by one or more integrated circuits.
  • the memory 154 can be of any type appropriate to the technical environment and can be implemented using any appropriate data storage technology, such as optical memory devices, magnetic memory devices, semiconductor-based memory devices, fixed memory, and removable memory, as non-limiting examples.
  • the processor 152 can be of any type appropriate to the technical environment, and can encompass one or more of microprocessors, general purpose computers, special purpose computers, and processors based on a multi-core architecture, as non-limiting examples. Block-Based Video Coding
  • FIG. 2A gives the block diagram of a block-based hybrid video encoding system 200. Variations of this encoder 200 are contemplated, but the encoder 200 is described below for purposes of clarity without describing all expected variations.
  • a video sequence Before being encoded, a video sequence may go through pre-encoding processing 204, for example, applying a color transform to an input color picture (e.g., conversion from RGB 4:4:4 to YCbCr 4:2:0), or performing a remapping of the input picture components in order to get a signal distribution more resilient to compression (for instance using a histogram equalization of one of the color components).
  • Metadata can be associated with the pre-processing and attached to the bitstream.
  • the input video signal 202 including a picture to be encoded is partitioned 206 and processed block by block in units of, for example, CUs. Different CUs may have different sizes. In VTM-1.0, a CU can be up to 128x128 pixels. However, different from the HEVC which partitions blocks only based on quad-trees, in the VTM-1.0, a coding tree unit (CTU) is split into CUs to adapt to varying local characteristics based on quad/binary/ternary-tree.
  • CTU coding tree unit
  • each CU is always used as the basic unit for both prediction and transform without further partitions.
  • a CTU is firstly partitioned by a quad-tree structure.
  • each quad-tree leaf node can be further partitioned by a binary and ternary tree structure.
  • Different splitting types may be used, such as quaternary partitioning, vertical binary partitioning, horizontal binary partitioning, vertical ternary partitioning, and horizontal ternary partitioning.
  • spatial prediction 208 and/or temporal prediction 210 may be performed.
  • Spatial prediction (or “intra prediction”) uses pixels from the samples of already coded neighboring blocks (which are called reference samples) in the same video picture/slice to predict the current video block. Spatial prediction reduces spatial redundancy inherent in the video signal.
  • Temporal prediction (also referred to as “inter prediction” or “motion compensated prediction”) uses reconstructed pixels from the already coded video pictures to predict the current video block. Temporal prediction reduces temporal redundancy inherent in the video signal.
  • a temporal prediction signal for a given CU may be signaled by one or more motion vectors (MVs) which indicate the amount and the direction of motion between the current CU and its temporal reference.
  • MVs motion vectors
  • a reference picture index may additionally be sent, which is used to identify from which reference picture in the reference picture store 212 the temporal prediction signal comes.
  • the mode decision block 214 in the encoder chooses the best prediction mode, for example based on a rate-distortion optimization method. This selection may be made after spatial and/or temporal prediction is performed.
  • the intra/inter decision may be indicated by, for example, a prediction mode flag.
  • the prediction block is subtracted from the current video block 216 to generate a prediction residual.
  • the prediction residual is de-correlated using transform 218 and quantized 220.
  • the encoder may bypass both transform and quantization, in which case the residual may be coded directly without the application of the transform or quantization processes.
  • the quantized residual coefficients are inverse quantized 222 and inverse transformed 224 to form the reconstructed residual, which is then added back to the prediction block 226 to form the reconstructed signal of the CU.
  • Further in-loop filtering such as deblocking/SAO (Sample Adaptive Offset) filtering, may be applied 228 on the reconstructed CU to reduce encoding artifacts before it is put in the reference picture store 212 and used to code future video blocks.
  • coding mode inter or intra
  • prediction mode information prediction mode information
  • motion information motion information
  • quantized residual coefficients are all sent to the entropy coding unit (108) to be further compressed and packed to form the bit-stream.
  • FIG. 2B gives a block diagram of a block-based video decoder 250.
  • a bitstream is decoded by the decoder elements as described below.
  • Video decoder 250 generally performs a decoding pass reciprocal to the encoding pass as described in FIG. 2A.
  • the encoder 200 also generally performs video decoding as part of encoding video data.
  • the input of the decoder includes a video bitstream 252, which can be generated by video encoder 200.
  • the video bit-stream 252 is first unpacked and entropy decoded at entropy decoding unit 254 to obtain transform coefficients, motion vectors, and other coded information.
  • Picture partition information indicates how the picture is partitioned.
  • the decoder may therefore divide 256 the picture according to the decoded picture partitioning information.
  • the coding mode and prediction information are sent to either the spatial prediction unit 258 (if intra coded) or the temporal prediction unit 260 (if inter coded) to form the prediction block.
  • the residual transform coefficients are sent to inverse quantization unit 262 and inverse transform unit 264 to reconstruct the residual block.
  • the prediction block and the residual block are then added together at 266 to generate the reconstructed block.
  • the reconstructed block may further go through in-loop filtering 268 before it is stored in reference picture store 270 for use in predicting future video blocks.
  • the decoded picture 272 may further go through post-decoding processing 274, for example, an inverse color transform (e.g. conversion from YCbCr 4:2:0 to RGB 4:4:4) or an inverse remapping performing the inverse of the remapping process performed in the pre-encoding processing 204.
  • the post-decoding processing can use metadata derived in the pre-encoding processing and signaled in the bitstream.
  • the decoded, processed video may be sent to a display device 276.
  • the display device 276 may be a separate device from the decoder 250, or the decoder 250 and the display device 276 may be components of the same device.
  • FIG. 3A is a schematic side view illustrating an example waveguide display that may be used with extended reality (XR) applications according to some embodiments.
  • An image is projected by an image generator 302.
  • the image generator 302 may use one or more of various techniques for projecting an image.
  • the image generator 302 may be a laser beam scanning (LBS) projector, a liquid crystal display (LCD), a light-emitting diode (LED) display (including an organic LED (OLED) or micro LED ( LED) display), a digital light processor (DLP), a liquid crystal on silicon (LCoS) display, or other type of image generator or light engine.
  • LBS laser beam scanning
  • LCD liquid crystal display
  • LED light-emitting diode
  • LED organic LED
  • DLP digital light processor
  • LCDoS liquid crystal on silicon
  • Light representing an image 312 generated by the image generator 302 is coupled into a waveguide 304 by a diffractive in-coupler 306.
  • the in-coupler 306 diffracts the light representing the image 312 into one or more diffractive orders.
  • light ray 308 which is one of the light rays representing a portion of the bottom of the image, is diffracted by the in-coupler 306, and one of the diffracted orders 310 (e.g. the second order) is at an angle that is capable of being propagated through the waveguide 304 by total internal reflection.
  • the image generator 302 displays images as directed by a control module 324, which operates to render image data, video data, point cloud data, or other displayable data.
  • At least a portion of the light 310 that has been coupled into the waveguide 304 by the diffractive in-coupler 306 is coupled out of the waveguide by a diffractive out-coupler 314.
  • At least some of the light coupled out of the waveguide 304 replicates the incident angle of light coupled into the waveguide.
  • out-coupled light rays 316a, 316b, and 316c replicate the angle of the in-coupled light ray 308. Because light exiting the out-coupler replicates the directions of light that entered the in-coupler, the waveguide substantially replicates the original image 312. A user’s eye 318 can focus on the replicated image.
  • the out-coupler 314 out-couples only a portion of the light with each reflection allowing a single input beam (such as beam 308) to generate multiple parallel output beams (such as beams 316a, 316b, and 316c). In this way, at least some of the light originating from each portion of the image is likely to reach the user’s eye even if the eye is not perfectly aligned with the center of the out- coupler. For example, if the eye 318 were to move downward, beam 316c may enter the eye even if beams 316a and 316b do not, so the user can still perceive the bottom of the image 312 despite the shift in position.
  • the out-coupler 314 thus operates in part as an exit pupil expander in the vertical direction.
  • the waveguide may also include one or more additional exit pupil expanders (not shown in FIG. 3A) to expand the exit pupil in the horizontal direction.
  • the waveguide 304 is at least partly transparent with respect to light originating outside the waveguide display.
  • the light 320 from real-world objects such as object 322 traverses the waveguide 304, allowing the user to see the real-world objects while using the waveguide display.
  • the diffraction grating 3114 As light 320 from real-world objects also goes through the diffraction grating 314, there will be multiple diffraction orders and hence multiple images.
  • the diffraction order zero no deviation by 314 to have a great diffraction efficiency for light 320 and order zero, while higher diffraction orders are lower in energy.
  • the out-coupler 314 is preferably configured to let through the zero order of the real image. In such embodiments, images displayed by the waveguide display may appear to be superimposed on the real world.
  • FIG. 3B is a schematic side view illustrating an example alternative display type that may be used with extended reality applications according to some embodiments.
  • a control module 332 controls a display 334, which may be an LCD, to display an image.
  • the headmounted display includes a partly-reflective surface 336 that reflects (and in some embodiments, both reflects and focuses) the image displayed on the LCD to make the image visible to the user.
  • the partly-reflective surface 336 also allows the passage of at least some exterior light, permitting the user to see their surroundings.
  • FIG. 3C is a schematic side view illustrating an example alternative display type that may be used with extended reality applications according to some embodiments.
  • a control module 342 controls a display 344, which may be an LCD, to display an image. The image is focused by one or more lenses of display optics 346 to make the image visible to the user.
  • exterior light does not reach the user’s eyes directly.
  • an exterior camera 348 may be used to capture images of the exterior environment and display such images on the display 344 together with any virtual content that may also be displayed.
  • the embodiments described herein are not limited to any particular type or structure of XR display device.
  • Digital humans may take the form of several representations (mesh, volumetric, voxel, point cloud, image, video, and sound), which is critical for the creation and formalization of digital media content.
  • a formalized template may be created to capture different representations of a human and allow interoperable representations.
  • This template may be, e.g., a generic human body model with a skeletal structure attached, a subject-specific model, a statistical shape model, or metadata representing the individual social properties. Either of these approaches may accurately provide a human figure as an initialization stage capable of statistically representing different human representations.
  • Synthetic 3D models may be used for digital human representation.
  • a synthetic representation is usually easier to manipulate and tailor to represent a specific human anatomy, visuals, and social parameters and facilitate animation generation in immersive realities given that all parameters are known a priori.
  • Synthetic models also facilitate appearance generalization and stylization, which professionals may use for animation and streaming.
  • 3D synthetic models appear to be a good representation, but they lack a standard definition and structure that may be used and matched by other digital human representations, for example, for userspecific details, such as virtual identity, social status, input device controls, the semantical structure of geometrical properties, semantical structure of shape and skeletal anatomy, but not exclusive of semantics on animation parameters.
  • Digital human content standardization is understood to not take into consideration human social behaviors and interaction with environmental information, and/or social and human privacy issues that are common attributes in the real world and may be adopted within social technologies.
  • the encoding of digital human content and the definition of the data structure needs to be defined.
  • these data formats are known. For open systems, the format of such data needs to be specified and standardized to enable interoperability between different systems. Described herein is a new media content format for an avatar/user representation.
  • avatar representations examples are presented herein.
  • the proposed representation of an avatar is intended to be compatible with any technology such as virtual reality (VR), augmented reality (AR), extended reality (XR), streaming, gaming, interactive, collaborative, or communication systems, that considers the transmission of digital human content, e.g., 2D/3D videos, or images containing body, faces or speech, 3D technology for rendering, animating or manipulating assets of human nature, or any other system that includes social and contextual information about a real user or avatar, such as, the social and communication media industry.
  • VR virtual reality
  • AR augmented reality
  • XR extended reality
  • FIG. 4 provides a high-level overview of the different components present in the avatar media codec representation.
  • the set 400 of core components are “Metadata” 402, “Geometry” 404, “Style” 406, “Animation” 408, “Context” 410, “Physics” 412, “Speech” 414, and “Properties” 416.
  • Each component represents a higher level of the avatar media codec. The following section will detail and introduce all the components shown in FIG. 4.
  • FIG. 5 is a process diagram illustrating an example top-level avatar media framework according to some embodiments.
  • the high-level components may be part of a description of a scene or an encoding format.
  • FIG. 5 presents mid-level components derived from the high-level components presented in FIG. 4.
  • FIG. 5 shows the structure of the different components and classifies them given the nature of the work.
  • a component of the example structure 500 may be classified as belonging to media 502, systems 504, or a joint collaboration 506 between the two.
  • the following section provides detail for all the components present in FIGs. 4 and 5 and discusses the different parts of the work, which are divided into a media block, systems block, and a joint block.
  • a media may include a coding (codec) of n-dimensional data whether computer-generated or captured from the physical world, and this data may include 3D graphics objects and environments.
  • codec codec
  • media representation is separate from delivery or presentation mechanisms, such as systems or internet protocols.
  • FIG. 7 illustrates the difference between these two concepts and demonstrates the need for the two on the same topic. Although these two concepts have different mandates, there is still a frontier between the two that is sometimes not clear and may overlap, as illustrated in FIG. 5.
  • FIG. 6 is a process diagram illustrating an example avatar encoding and decoding process according to some embodiments.
  • raw avatar and scene description data resides on a server 602.
  • the raw scene description data may be retrieved, formatted, and processed by a server, which may be different from the server storing the raw data.
  • raw avatar data may be retrieved, formatted, and processed by a server (which may be different from the server storing the raw data) to obtain avatar model data 604, avatar animation data 606, and avatar metadata 608.
  • These three sets of avatar data may be encoded using an avatar encoder 610.
  • these three sets of avatar data may be sent to a scene description processing block 612 for further processing.
  • the output of the avatar encoder may undergo formatting and binary coding 614 to generate an encoded avatar binary file.
  • This encoded avatar binary file may be sent to a client device.
  • the client device 616 may decode 618 the file to obtain the avatar data.
  • the client device may also obtain scene description data.
  • the client device 616 may use both of these data items to render 620 an augmented reality scene environment combined with an avatar.
  • FIG. 7 is a process diagram illustrating an example avatar media cataloging process according to some embodiments.
  • the left side of the system 700 of FIG. 7 shows a codec block 702 that is agnostic to the meaning of the data.
  • This codec block 702 is not capable of interpreting the applicability or the dissimilarities between the different data channels.
  • the codec interprets the different input formats 704 equally and stores them in similar data structures.
  • the structure of a channel 708 contains properties that allow a system model 706, such as the one on the right side of FIG. 7, to correctly interpret the meaning of the channel 708 or packet data.
  • FIG. 7 The example in FIG.
  • FIG. 7 shows a mapping of a “geometry” (left side) packet 710 flagged with “FlagJD: 0” with a system object “Geometry” (right-side) 712.
  • the system object understands the streamed content as geometrical information and handles the content accordingly.
  • FIG. 7 shows the differences and overlap of media and systems.
  • the objective is to compress and efficiently transmit data.
  • the objective is to process and handle the media according to the nature of its properties.
  • FIG. 8 is a system diagram illustrating example top-level avatar media codec streaming component interfaces according to some embodiments.
  • FIG. 8 illustrates what types of data may be streamed over a period of time or on a single instance.
  • the blocks shown in FIG. 8 represent the core blocks of the avatar media codec format.
  • FIG. 8 shows a structure 800 with a focus on encoding and transmitting static and timebased animation, geometric, appearance, and/or artificial intelligence data.
  • the encoding may be “time-based” or “key-frame based”.
  • the encoding encapsulates at least one of the profiles of Computer Graphics (CG) 802, Parametric Model 804, or Artificial Intelligence (Al) Model 806.
  • Time-based data transmission assumes a continuous stream of timed media without the necessity of intra-frame interpolation. Each frame transmitted is assumed to be continuous in time and consequently temporally aligned.
  • Key-frame data transmission assumes a discontinuous stream of timed media with the possibility for intra-frame or inter-frame interpolation between, either key-frames or reference frames.
  • a key-frame is assumed to be data received with respect to a single time instance, which may be in the future, present, or past.
  • a reference frame is assumed to be data transmitted one or several times as a key-frame flagged as a reference frame and to be kept in memory or used for inter-frame interpolation.
  • the encoding is agnostic to the type of data being compressed. As a consequence, whether the data is time or key-frame based does not affect the encoded data for transmission.
  • the encoding may follow three major profiles, but not exclusive. The major profiles are CG, Parametric Model, and Al Model.
  • Animation data transmission handles dynamic information that is to be updated or continuously streamed.
  • Animation data may include (but not exclusively): joint animation 808, blendshape weights 810, controllers weights 812, vertex displacements 820, vertices 822, landmarks 832, motion dictionary 814, texture/materials 816, UV displacements 818, shape weights, and other related information.
  • Geometry data transmission handles static information that only requires transmission for handshakes and model updates.
  • Geometry data may include (but not exclusively): vertices 822, faces 830, skeleton 824, landmarks 832, UV maps 826, skinning 834, texture/materials 816, blendshapes 828, vertex displacements 820, and other related static data.
  • the parametric model profile is based on a non-AI-based mechanism, but instead is based on probabilistic models that are data-driven and parametrized with known characteristics.
  • one model may have animation weights 836 that directly modify and drive the model's animation system, such as making an avatar walk, or making the avatar model reach for objects in the scene.
  • Shape weights 838 may make the avatar skeletal, body, or garment change into different visual forms while preserving the essence of the model (topology).
  • Texture weights 840 may make the visual appearance change or animate without interfering with the geometry.
  • Pose weights 842 may change the pose of the avatar through predefined rigg parameters on the shape and skeletal structure.
  • FIG. 9 is a process diagram illustrating an example computer-generated avatar media stream process according to some embodiments.
  • FIG. 9 shows an architecture 900 for avatar media streaming that has a context more focused on computer-generated (CG) content.
  • CG computer-generated
  • FIG. 9 contains the components used for encoding and transmitting avatar information, which is interoperable across systems and platforms.
  • the input block 902 in FIG. 9 shows examples of different inputs that may be used simultaneously or as individual content inputs.
  • the processing block 904 uses algorithms and/or methods to extract information from the input source(s) for a particular codec format (e.g., VPCC, GPCC, V-DMC, gITF, and USD).
  • the priors block 906 includes models that are used to infer template-based information about the content of the input source.
  • the data format block 908 defines the elements and data of the avatar media codec.
  • the encode block 910 and decode block 912 each use compression / decompression, and compacting / de-compacting processes to allow efficient and lightweight bitstream transmission of the avatar media codec.
  • the output block 914 uses algorithms and/or methods to transform the data into a format used by an application.
  • the application block 916 uses the avatar data, such as by 2D/3D rendering or other means to display and/or interact with digital content.
  • Vertices 918 may be expressed in the form of 2D/3D spatial descriptors that represent the 2D or 3D geometrical composition of an avatar.
  • Shape weights 1020 may be expressed as 1 D, 2D, or nD (for any integer greater than 0) descriptors that represent parameters to deform the geometry representation of the avatar. Such descriptors are modelbased and not transferable across different models. These descriptors may have several forms, such as, a form with an associated semantical meaning or a form that is more numerical.
  • FIG. 11 contains the components used for encoding and transmitting avatar information, which is interoperable across systems and platforms.
  • the input block 1102 in FIG. 11 shows examples of different inputs that may be used simultaneously or as individual content inputs.
  • the processing block 1104 uses algorithms and/or methods to extract information from the input source(s) for a particular codec format (e.g., VPCC, GPCC, V-DMC, gITF, and USD).
  • the priors block 1106 includes models that are used to infer template-based information about the content of the input source.
  • the data format block 1108 defines the elements and data of the avatar media codec.
  • a deep network may be expressed as a pre-trained neural network that uses input features (video, image, or shape, among others) to represent a given task for avatar streaming, representation, and/or manipulation.
  • a deep network may include mechanisms for encoding and decoding through a combination of linear or convolutional layers.
  • a deep network may use a latent feature representation of encoded data on the receiver side along with a decoder. For a given latent feature, the decoder may generate an output that is given to the network while in training mode.
  • An architecture 1118 may be expressed in a binary or human-readable (JSON) format that includes the format and representation of all the layers in the network.
  • An architecture may include encoders, decoders, and/or generators. The architecture includes details for all attributes related to such layers, such as, input and output parameters, linear and convolutional layers, activation mechanism types (if any), normalization mechanism types, skip connection details, arithmetics between layers (the multiplying, adding, subtracting, and/or dividing of: layers, weights, parameters, and/or outputs), and initialization parameters.
  • the network weights 1120 may be expressed in a binary or human-readable (JSON) format that includes all weights and bias parameters of the network architecture. These weights initialize the network architecture to a state capable of being instantiated (e.g., the state of the network when training was satisfied/completed).
  • JSON binary or human-readable
  • the animation, geometry, and texture parameters may take the form presented above in the context of a CG profile and may be available at the receiver or application side of the framework.
  • the transmitted information may relate to one or more properties of the data presented above in the context of a CG profile.
  • a label may accompany a latent feature to indicate which type of data the decoder or application is expected to handle (e.g., an “Animation”, ” JointAnimation”, or other latent feature).
  • Such a label may announce to the application or decoder that the latent feature is a joint animation.
  • Such a joint animation may be a joint rotation, translation, and/or scale.
  • Latent features 1122 may be expressed as 1 D, 2D, or nD (for any integer greater than 0) descriptors that represent parameters to deform one or several components of an animation, a geometry and/or a texture/appearance representation of an avatar. Such descriptors are Al-based and not transferable across different networks without re-training. These descriptors may have several forms, such as, a form with an associated semantical meaning or a form that is more numerical.
  • the interchange format may be a JSON format or another text-form implementation of the data model. This format is human-readable and may be manipulated by a user.
  • the format is Avatar JSON Interchange Format (AJIF). AJIF information about digital humans (avatars) may be encoded and represented in a stream between systems. Table 1 illustrates higher level information available for streaming and representing of avatar media.
  • API application programming interface
  • the geometry of an avatar media represents properties that define the avatar asset and semantical meaning. This may be in the form of connected or disconnected vertices, skeletal structures, 3D markers, images, or contextual information.
  • the function “processGeometryO” handles the fetching of (relevant) information.
  • semantics may include labeling of vertices, faces, regions (e.g., geometry), landmarks and skeletal labeling, texture labeling, for applications such as classification; avatar-object interaction, avatar-avatar interaction, avatar retargeting (e.g., animation, style, geometry, and the other elements shown in FIG. 4 and Tables 2-10).
  • This signal is to inform the decoder that geometric information is available for reading.
  • This signal may take many forms, such as traditional encoding standards for geometric information, including MPEG-I SD, MPEG-AI MPEG V-DMC, L-PCC, MPEG 4, H-anim, JVET, and others.
  • an animation avatar media element may be related to the animation parameters, for example, styles may be correlated with motion and have specific motion vectors available to certain styles of animation.
  • animation may be related to skeletal animation, geometry displacement either rigid or non-rigid.
  • animation may be correlated with the garments motion of the avatar if existing.
  • This signal is to inform the decoder that animation information is available for reading.
  • This signal may take many forms, such as traditional encoding standards for geometric and complementary information, such as MPEG-I SD, MPEG-AI MPEG V-DMC, L-PCC, MPEG 4, H-anim, JVET, and others.
  • the context of an avatar media represents the properties that define the scene in which the avatar is included, such as a description of the world environment within a VR or AR system as a video stream or in a scene description format.
  • the function “processContextO” handles the fetching of (relevant) information.
  • scene of the avatar includes the surroundings that the avatar is currently at.
  • the scene may be, for example, the background in the context of a 2D video stream, that is to be preserved while streaming with the avatar data, or to be removed according to the signal present.
  • This signal is to inform the decoder that context information is available for reading.
  • This signal may take many forms, such as traditional encoding standards for geometric and complementary information, such as MPEG-I SD, MPEG-AI MPEG V-DMC, L-PCC, MPEG 4, H-anim, JVET, and others.
  • the physics of an avatar media represents the properties that define the avatar motion and scene interaction based on physical models of the avatar and its environment. These properties may describe the gravity force, wind forces, or other natural forces, as well as lighting or material properties.
  • the function “processPhysicsQ” handles the fetching of (relevant) information.
  • the haptics of an avatar media represents the properties that define the haptic feedback features available for an avatar. These features may take the form of object material properties, haptic sensors on the avatar, potential feedback responses from other objects and systems in an environment, haptic signals attached to specific body parts or a sensitivity map for instance.
  • the function “processHapticsQ” handles the fetching of (relevant) information.
  • This signal is to inform the decoder that haptic information is available for reading.
  • This signal may take many forms, such as traditional encoding standards for geometric and complementary haptic information, such as MPEG-I SD, MPEG-AI MPEG V-DMC, L-PCC, MPEG 4, H-anim, JVET, HMPG, H JI F and others.
  • able 7 Haptics Semantics Audio
  • the properties of an avatar media represent additional information that may further define the avatar being transmitted, for example, social or personal information, or additional information relevant to the application that receives the data content that may possibly not be included in the specifications (for example, proprietary physics properties, proprietary semantics of the avatar geometry, and others).
  • the function “processPropertiesO” handles the fetching of (relevant) information.
  • This signal is to inform the decoder that properties information is available for reading.
  • This signal may take many forms, such as traditional encoding standards for geometric and complementary information, such as MPEG-I SD, MPEG-AI MPEG V-DMC, L-PCC, MPEG 4, H-anim, JVET, and others.
  • Geometry The geometry of an avatar media represents properties that define the avatar asset and semantical meaning. This may be in the form of connected or disconnected vertices, skeletal structures, 3D markers, images, or contextual information.
  • decodeGeometryO handles the fetching of (relevant) information transmitted by the encoder.
  • the animation of an avatar media represents the properties that define the avatar motion, such as in the form of 2D video, immersive video, multi-view video, skeletal or geometry.
  • the function “decodeAnimationO” handles the fetching of (relevant) information transmitted by the encoder.
  • semantics may include decoding of labels for vertices, faces, regions (e.g., geometry), landmarks and skeletal labeling, texture labeling, for applications such as classification; avatarobject interaction, avatar-avatar interaction, avatar retargeting (e.g., animation, style, geometry, and the other elements shown in FIG. 4 and Tables 2-10).
  • the context of an avatar media represents the properties that define the scene in which the avatar is included, such as a description of the world environment within a VR or AR system as a video stream or in a scene description format.
  • the function “decodeContextO” handles the fetching of (relevant) information transmitted by the encoder.
  • the audio of an avatar media represents the properties that define the avatar audio, such as speech and noise by contact or spatial audio properties.
  • the function “decodeAudioQ” handles the fetching of (relevant) information transmitted by the encoder.
  • semantics may include decoding of audio properties that may include audio related to spatial audio or speech.
  • Metadata of an avatar media represents the properties that allow signal and data decoding from other entities, such as other standards (MPEG-I SD, MPEG-AI MPEG V-DMC, L-PCC, MPEG 4, H- anim, JVET).
  • the function “decodeMetadataQ” handles the fetching of (relevant) information transmitted by the encoder.
  • FIG. 12 is a process diagram illustrating an example encoder architecture according to some embodiments.
  • FIG. 12 illustrates in more detail the encoder architecture 1200 for the avatar media codec and properties described above.
  • the encoder is able to process multiple types of input files 1202, descriptive avatar media files (such as Graphics Library Transmission Format (.gltf) 1204, Extensible Three-Dimensional format (.x3d) 1206, JavaScript Object Notation (.json) 1208, Extensible Markup Language format (.xml) 1210, and text format (.txt) to name a few formats) which contain the information presented above.
  • the output data from the encoder may have multiple forms. For some embodiments, as illustrated in FIG.
  • two encoder output formats are used: a human readable format (based on JSON in this example implementation) and a binary format.
  • the JSON-based format (which may be stored in JSON-based file 1212 for some embodiments) provides metadata information for each of the elements of the avatar data structure (such as geometry, style, animation, and the other elements shown in FIG. 4 and Tables 2-10) and references the appropriate file.
  • the binary format compresses (all) the data in a single binary file 1214. In this format, the data may be “packetized” to allow independent access to each of the elements of the avatar data structure.
  • formatting 1218 the avatar data structure may include formatting the avatar data structure into blocks, where each block contains, e.g., the avatar description elements represented in FIG. 4, and, e.g., includes a header allowing the decoder to unambiguously identify the contents of the block.
  • the input files may be a single format or a collection of files in different formats for some embodiments.
  • the format analysis 1216 and formatting 1218 of blocks have the objective of fetching (relevant) information and arranging the information in such a way that the original file format may be recovered in either binary or human-readable format.
  • a header section may be included in an avatar data structure element “packet”, as defined above, to inform the decoder how to decompress and recover the original formats.
  • the arranging of the information obtained from the input file(s) may be stored in (or populated into) an avatar data structure.
  • the JSON output file may include one or more avatar data properties.
  • FIG. 12 shows an example set of avatar data properties.
  • Some JSON output files may include other avatar properties not shown in this example.
  • some JSON output files may use different formats for properties than the formats used in this example.
  • the Geometry property may be encoded in “,x3d” format.
  • the Style property may be encoded in “.xml” format.
  • the Animation property may be encoded in “. gltf” format.
  • the Haptics property may be encoded in “.json” format.
  • the header section or packet may make the same reference to facilitate decoding in a lossless manner back to the original format.
  • Format analysis 1216 and formatting 1218 of blocks depicted in FIG. 12 may use parsing mechanisms to extract the (relevant) information in different file formats so that the information may be packed and compressed into a binary compression format or human-readable format.
  • the formatting block 1218 allows the generation of a human-readable format instead of a binary format.
  • the human-readable format may be in the form of a JSON file format.
  • the human-readable format may be a format other than JSON.
  • the binary compression block 1220 applies lossless compression using the normative SPIHT algorithm and Arithmetic Coding (AC) and transforms the data into a bitstream.
  • AC Arithmetic Coding
  • the binary compression 1220 for “.json” files follow the RFC 8949 Concise Binary Object Representation standard.
  • the binary compression 1220 for “,x3d” files follow the ISO/IEC 19776- 3.2:2011 Extensible 3D encodings standard.
  • the binary compression 1220 for “.gltf” files follow the open gITF 2.0 specification from the Khronos group to generate binary “.gib” files.
  • the binary compression 1220 for “.xml” files follow the ISO/IEC 23001 - 1 : 2006 Binary MPEG format for XML
  • packetization 1222 may include organizing binary compression data into packets for each of the elements of a data structure (such as geometry, style, or any of the other elements shown in FIG. 4 and Tables 2-10). For some embodiments, packetization 1222 may be used during transport to request access to part of the data only.
  • both human-readable files such as JSON files
  • binary files may be outputted from an encoder.
  • FIG. 12 presents an example configuration in accordance with some embodiments.
  • only human-readable files may be outputted from an encoder.
  • only binary files may be outputted from an encoder.
  • FIG. 13 is a process diagram illustrating an example decoder architecture according to some embodiments.
  • FIG. 13 illustrates the decoder architecture 1300 for the avatar media codec and properties described above in more detail.
  • the decoder takes a binary file 1302 and/or a set of text files as an input and outputs the original file formats which are interoperable.
  • the input text files may be represented in JSON format file 1204 as shown in FIG. 13, or in any other text file format.
  • the decoded avatar data includes avatar animation data.
  • the decoded avatar data includes avatar geometry data.
  • the decoded avatar data includes avatar appearance data.
  • a second example apparatus in accordance with some embodiments may include: a processor; and a non-transitory computer-readable medium storing instructions operative, when executed by the processor, to cause the apparatus to perform any of the methods listed above.
  • a third example method in accordance with some embodiments may include: obtaining an input file, wherein the input file includes avatar content data; determining a data type corresponding to the avatar content data; processing the avatar data to extract information from the input file based on the data type and codec type; inferring template-based information regarding the avatar content data; formatting the avatar content data based on a profile type and the template-based information, wherein the profile type is a parametric profile type; and encoding the formatted avatar data.
  • the data type is one of a data set including: video data, image data, mesh data, and game data.
  • the formatted avatar data includes weights for a parameter.
  • the parameter is one of a property set including: animation, shape, texture, and pose properties.
  • the formatted avatar data includes a parameter-based model of an avatar.
  • a third example apparatus in accordance with some embodiments may include: a processor; and a non-transitory computer-readable medium storing instructions operative, when executed by the processor, to cause the apparatus to perform any of the methods listed above.
  • a fourth example method in accordance with some embodiments may include: obtaining encoded avatar data; decoding the encoded avatar data to generate decoded avatar data; determining a data type corresponding to the decoded avatar data; processing the decoded avatar data based on the data type and codec type, wherein the profile type is a parametric profile type; and rendering the processed and decoded avatar data.
  • the data type is one of a data set including: video data, image data, mesh data, and game data.
  • the decoded avatar data includes weights for a parameter.
  • the parameter is one of a property set including: animation, shape, texture, and pose properties.
  • the decoded avatar data includes a parameter-based model of an avatar.
  • a fourth example apparatus in accordance with some embodiments may include: a processor; and a non-transitory computer-readable medium storing instructions operative, when executed by the processor, to cause the apparatus to perform any of the methods listed above.
  • a fifth example method in accordance with some embodiments may include: obtaining an input file, wherein the input file includes avatar content data; determining a data type corresponding to the avatar content data; processing the avatar data to extract information from the input file based on the data type and codec type; inferring template-based information regarding the avatar content data; formatting the avatar content data based on a profile type and the template-based information, wherein the profile type is an artificial intelligence (Al) profile type; and encoding the formatted avatar data.
  • Al artificial intelligence
  • the data type is one of a data set including: video data, image data, mesh data, and game data.
  • the formatted avatar data includes information corresponding to a neural network.
  • encoding the formatted avatar data includes using a neural network.
  • a fifth example apparatus in accordance with some embodiments may include: a processor; and a non-transitory computer-readable medium storing instructions operative, when executed by the processor, to cause the apparatus to perform any of the methods listed above.
  • the data type is one of a data set including: video data, image data, mesh data, and game data.
  • the decoded avatar data includes information corresponding to a neural network.
  • a sixth example apparatus in accordance with some embodiments may include: a processor; and a non-transitory computer-readable medium storing instructions operative, when executed by the processor, to cause the apparatus to perform any of the methods listed above.
  • a seventh example apparatus in accordance with some embodiments may include at least one processor configured to perform any one of the methods listed above.
  • An eighth example apparatus in accordance with some embodiments may include a computer- readable medium storing instructions for causing one or more processors to perform any one of the methods listed above.
  • a ninth example apparatus in accordance with some embodiments may include at least one processor and at least one non-transitory computer-readable medium storing instructions for causing the at least one processor to perform any one of the methods listed above.
  • This disclosure describes a variety of aspects, including tools, features, embodiments, models, approaches, etc. Many of these aspects are described with specificity and, at least to show the individual characteristics, are often described in a manner that may sound limiting. However, this is for purposes of clarity in description, and does not limit the disclosure or scope of those aspects. Indeed, all of the different aspects can be combined and interchanged to provide further aspects. Moreover, the aspects can be combined and interchanged with aspects described in earlier filings as well.
  • the terms “reconstructed” and “decoded” may be used interchangeably, the terms “pixel” and “sample” may be used interchangeably, the terms “image,” “picture” and “frame” may be used interchangeably.
  • the term “reconstructed” is used at the encoder side while “decoded” is used at the decoder side.
  • Embodiments described herein may be carried out by computer software implemented by a processor or other hardware, or by a combination of hardware and software. As a non-limiting example, the embodiments can be implemented by one or more integrated circuits.
  • the processor can be of any type appropriate to the technical environment and can encompass one or more of microprocessors, general purpose computers, special purpose computers, and processors based on a multi-core architecture, as nonlimiting examples.
  • Accessing the information can include one or more of, for example, receiving the information, retrieving the information (for example, from memory), storing the information, moving the information, copying the information, calculating the information, determining the information, predicting the information, or estimating the information.
  • such phrasing is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of the third listed option (C) only, or the selection of the first and the second listed options (A and B) only, or the selection of the first and third listed options (A and C) only, or the selection of the second and third listed options (B and C) only, or the selection of all three options (A and B and C).
  • This may be extended for as many items as are listed.
  • Implementations can produce a variety of signals formatted to carry information that can be, for example, stored or transmitted.
  • the information can include, for example, instructions for performing a method, or data produced by one of the described implementations.
  • a signal can be formatted to carry the bitstream of a described embodiment.
  • Such a signal can be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal.
  • the formatting can include, for example, encoding a data stream and modulating a carrier with the encoded data stream.
  • the information that the signal carries can be, for example, analog or digital information.
  • the signal can be transmitted over a variety of different wired or wireless links, as is known.
  • the signal can be stored on a processor-readable medium.
  • a TV, set-top box, cell phone, tablet, or other electronic device that performs adaptation of filter parameters according to any of the embodiments described.
  • a TV, set-top box, cell phone, tablet, or other electronic device that performs adaptation of filter parameters according to any of the embodiments described, and that displays (e.g. using a monitor, screen, or other type of display) a resulting image.
  • a TV, set-top box, cell phone, tablet, or other electronic device that selects (e.g. using a tuner) a channel to receive a signal including an encoded image, and performs adaptation of filter parameters according to any of the embodiments described.
  • a TV, set-top box, cell phone, tablet, or other electronic device that receives (e.g. using an antenna) a signal over the air that includes an encoded image, and performs adaptation of filter parameters according to any of the embodiments described.
  • modules that carry out (i.e., perform, execute, and the like) various functions that are described herein in connection with the respective modules.
  • a module includes hardware (e.g., one or more processors, one or more microprocessors, one or more microcontrollers, one or more microchips, one or more application-specific integrated circuits (ASICs), one or more field programmable gate arrays (FPGAs), one or more memory devices) deemed suitable by those of skill in the relevant art for a given implementation.
  • ASICs application-specific integrated circuits
  • FPGAs field programmable gate arrays
  • Each described module may also include instructions executable for carrying out the one or more functions described as being carried out by the respective module, and it is noted that those instructions could take the form of or include hardware (i.e., hardwired) instructions, firmware instructions, software instructions, and/or the like, and may be stored in any suitable non-transitory computer-readable medium or media, such as commonly referred to as RAM, ROM, etc.
  • ROM read only memory
  • RAM random access memory
  • register cache memory
  • semiconductor memory devices magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks, and digital versatile disks (DVDs).
  • a processor in association with software may be used to implement a radio frequency transceiver for use in a WTRU, UE, terminal, base station, RNC, or any host computer.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Signal Processing (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • Computer Graphics (AREA)
  • Human Computer Interaction (AREA)
  • Artificial Intelligence (AREA)
  • Processing Or Creating Images (AREA)

Abstract

Certains modes de réalisation d'un procédé peuvent consister à : obtenir un fichier d'entrée, le fichier d'entrée comprenant des données de contenu d'avatar ; déterminer un type de données correspondant aux données de contenu d'avatar ; traiter les données d'avatar pour extraire des informations du fichier d'entrée sur la base du type de données et d'un type de codec ; déduire des informations basées sur un modèle, relatives aux données de contenu d'avatar ; formater les données de contenu d'avatar sur la base d'un type de profil et des informations basées sur un modèle ; et encoder les données d'avatar formatées.
PCT/EP2024/078231 2024-01-15 2024-10-08 Représentation multimédia d'avatar pour une transmission Pending WO2025153195A1 (fr)

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EP24305093.7 2024-01-15

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Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
GILLES TENIOU (TENCENT): "Use cases and MPEG technologies for Metaverse-related experiences", no. m65744, 20 October 2023 (2023-10-20), XP030313502, Retrieved from the Internet <URL:https://dms.mpeg.expert/doc_end_user/documents/144_Hannover/wg11/m65744-v1-m65744.zip m65744 Use cases and MPEG technologies for Metaverse-related experiences.docx> [retrieved on 20231020] *
JOVANOVA B.: "Virtual human representation, adaptation, delivery and interoperability for virtual worlds", INSTITUT NATIONAL DES TELECOMMUNICATIONS, DOCTORAL DISSERTATION, 26 June 2012 (2012-06-26), pages 1 - 190, XP093182434 *
MINGYANG SUN ET AL: "Human 3D Avatar Modeling with Implicit Neural Representation: A Brief Survey", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 6 June 2023 (2023-06-06), XP091531644 *

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