[go: up one dir, main page]

WO2025078267A1 - Procédé de codage de nuage de points hybride avec représentation de surface locale - Google Patents

Procédé de codage de nuage de points hybride avec représentation de surface locale Download PDF

Info

Publication number
WO2025078267A1
WO2025078267A1 PCT/EP2024/077874 EP2024077874W WO2025078267A1 WO 2025078267 A1 WO2025078267 A1 WO 2025078267A1 EP 2024077874 W EP2024077874 W EP 2024077874W WO 2025078267 A1 WO2025078267 A1 WO 2025078267A1
Authority
WO
WIPO (PCT)
Prior art keywords
point cloud
geometry
octree
bitstream
attribute
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/EP2024/077874
Other languages
English (en)
Inventor
Bertrand Chupeau
Gustavo Sandri
Franck Thudor
Maja KRIVOKUCA
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 WO2025078267A1 publication Critical patent/WO2025078267A1/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
    • H04N19/50—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
    • 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
    • G06T17/005—Tree description, e.g. octree, quadtree
    • 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
    • G06T9/40—Tree coding, e.g. quadtree, octree

Definitions

  • Point clouds are data that may be used in numerous business domains, such as autonomous driving, robotics, ARA/R, civil engineering, computer graphics, to the animation / movie industry.
  • 3D LiDAR sensors have been deployed in self-driving cars, and affordable LiDAR sensors include Velodyne Velabit, Apple iPad Pro 2020, and Intel RealSense LiDAR camera L515. With advances in sensing technologies, 3D point cloud data is becoming more widespread, such as in the applications and industries mentioned above.
  • a first example method in accordance with some embodiments may include: obtaining a point cloud, the point cloud comprising: a first set of information describing a geometry of the point cloud, and a second set of information describing attributes of the point cloud; performing a geometry encoding process, wherein the geometry encoding process generates a geometry bitstream, and wherein the geometry bitstream comprises a pruned octree associated with a first part of the geometry of the point cloud and a surface model associated with a second part of the geometry of the point cloud; performing an attribute coding process, wherein the attribute coding process generates a first part of an attribute bitstream, and wherein the first part of the attribute bitstream comprises transformation coefficients; performing a texture atlas process, wherein the texture atlas process generates a second part of the attribute bitstream, and wherein the second part of the attribute bitstream comprises a video bitstream and texture atlas coordinates; and outputting an output bitstream comprising the geometry bitstream and the attribute bitstream.
  • the geometry encoding process comprises: initializing an octree process; and responsive to determining an octree threshold is satisfied for a current node, performing the octree process, the octree process comprising: performing an 8-way split of a portion of the geometry associated with the current node; and responsive to determining the geometry associated with the current node is a leaf, generating, upon exiting the octree process, a pruned octree associated with the current node; and incrementing the current node; and returning to a start of the octree process to determine if the octree threshold is satisfied.
  • the geometry encoding process comprises: initializing an octree process; and responsive to determining the octree threshold is failed for a current node, performing a meshing process to generate a surface mode associated with the current node.
  • the octree threshold is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • an average geometric distance between a reconstructed version of the point cloud for a decoded mesh representation and the point cloud originally obtained is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • an average point to point distance for a closest point in another point cloud is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • an average point to plane distance in a direction of a normal vector is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • the texture atlas process comprises: performing a texture mapping process to generate texture atlas mesh node data and atlas coordinates; and encoding the texture atlas mesh node data to generate the video bitstream.
  • the attribute coding process is performed using the pruned octree associated with the first portion of the geometry of the point cloud.
  • the texture atlas process is performed using the surface model associated with the second portion of the geometry of the point cloud.
  • the attribute coding process comprises a Region-Adaptive Hierarchical Transform (RAHT) process.
  • RAHT Region-Adaptive Hierarchical Transform
  • a first 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 one of the methods listed above.
  • a second example method in accordance with some embodiments may include: obtaining a geometry bitstream associated with a point cloud and an attribute bitstream associated with the point cloud, wherein the geometry bitstream comprises octree data and surface model data, and wherein the attribute bitstream comprises one or more transformation coefficients and texture atlas data; performing an octree reconstruction process using the octree data, wherein the octree reconstruction process generates a first portion of a geometry of the point cloud; reconstructing surface data of the point cloud using the surface model data; performing a point cloud attribute decoding on the transformation coefficients to generate a first set of attributes associated with the point cloud; and performing texture atlas decoding to generate a second set of attributes associated with the point cloud.
  • performing texture atlas decoding comprises: passing the texture atlas data through a decoder; mapping an output of the decoder onto mesh faces to generate a mapped texture; and sampling the mapped texture to generate the second set of attributes associated with the point cloud.
  • performing texture atlas decoding further comprises sampling the rasterized and reconstructed surface as part of generating the second set of attributes associated with the point cloud.
  • the reconstructed surface data is the second portion of the geometry of the point cloud.
  • 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 one of the methods listed above.
  • a third example method in accordance with some embodiments may include: obtaining a point cloud, the point cloud comprising: a first set of information describing a geometry of the point cloud, and a second set of information describing attributes of the point cloud; performing a geometry encoding process, wherein the geometry encoding process generates a geometry bitstream, and wherein the geometry bitstream comprises a pruned octree associated with a first part of the geometry of the point cloud and a surface model associated with a second part of the geometry of the point cloud; performing an attribute coding process, wherein the attribute coding process generates a first part of an attribute bitstream, and wherein the first part of the attribute bitstream comprises transformation coefficients; and outputting an output bitstream comprising the geometry bitstream and the attribute bitstream.
  • 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 one of the methods listed above.
  • a fourth example method in accordance with some embodiments may include: obtaining a geometry bitstream associated with a point cloud and an attribute bitstream associated with the point cloud, wherein the geometry bitstream comprises octree data and surface model data, and wherein the attribute bitstream comprises one or more transformation coefficients and texture atlas data; performing an octree reconstruction process using the octree data, wherein the octree reconstruction process generates a first portion of a geometry of the point cloud; reconstructing surface data of the point cloud using the surface model data; and performing a point cloud attribute decoding on the transformation coefficients to generate a first set of attributes associated with the point cloud.
  • 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 one of the methods listed above.
  • a fifth example method of point cloud encoding based on a point-based octree representation of geometry combined with a surface-based 3D-mesh representation of individual nodes may include: responsive to determining, during an octree generation process, for any current node at any current level, an associated point set is able to be approximated with a meshed surface with minimal loss, performing a sub-process, wherein the sub-process comprises: stopping the octree generation process; replacing, for the current node, an output of the octree generation process with a local 3D-mesh representation; and combining a point-based method for octree generation process outputs for at least one other node with a texture atlas for 3D-meshed nodes.
  • 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 one of the methods listed above.
  • a sixth example method of point cloud decoding based on a point-based octree representation of geometry combined with a surface-based 3D-mesh representation of individual nodes may include: decoding a pruned octree; reconstructing an associated point cloud geometry; decoding an attribute transform to generate associated attributes; reconstructing a surface mesh model; decoding a texture atlas; mapping the decoded texture atlas onto mesh faces; rasterizing the surface mesh model; and sampling the mapped texture.
  • 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 one 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.
  • An example signal in accordance with some embodiments may include a bitstream generated according to any one of the methods listed above.
  • FIG. 1A is a system diagram illustrating an example communications system according to some embodiments.
  • FIG. 1 B is a system diagram illustrating an example wireless transmit/receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1A according to some embodiments.
  • WTRU wireless transmit/receive unit
  • FIG. 1C is a system diagram illustrating an example set of interfaces for a system according to some embodiments.
  • FIG. 2A is a functional block diagram of block-based video encoder, such as an encoder used for Versatile Video Coding (VVC), according to some embodiments.
  • VVC Versatile Video Coding
  • FIG. 2B is a functional block diagram of a block-based video decoder, such as a decoder used for VVC, according to some embodiments.
  • 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.
  • XR extended reality
  • 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.
  • 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.
  • FIG. 4 is a process diagram illustrating an example global point cloud compression according to some embodiments.
  • FIG. 5 is a schematic illustration showing an example Geometry-based Point Cloud Compression (G-PCC) encoding for dense dynamic point clouds according to some embodiments.
  • G-PCC Geometry-based Point Cloud Compression
  • FIG. 7 is an illustration showing example scenes with fine topology according to some embodiments.
  • FIG. 8 is a schematic illustration showing an example hybrid octree / mesh geometry representation according to some embodiments.
  • FIG. 9A is a schematic illustration showing example faces of a mesh representation of a geometry used with a texture atlas encoding of attributes of a single TriSoup node according to some embodiments.
  • FIG. 9B is a schematic illustration showing an example projection of attributes of each face in a 2D texture atlas used with a texture atlas encoding of attributes of a single TriSoup node according to some embodiments.
  • FIG. 10A is a schematic illustration showing an example sampling of a texture atlas according to some embodiments.
  • FIG. 10B is a schematic illustration showing an example recovery of attributes of 3D rasterized points of a mesh face according to some embodiments.
  • FIG. 11 is a process diagram illustrating an example hybrid point cloud encoding according to some embodiments.
  • FIG. 12 is a process diagram illustrating an example hybrid point cloud decoding according to some embodiments.
  • FIG. 13 is a flowchart illustrating an example hybrid point cloud encoding according to some embodiments.
  • FIG. 14 is a flowchart illustrating an example hybrid point cloud decoding 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 communications systems 100 may also include a base station 114a and/or a base station 114b.
  • Each of the base stations 114a, 114b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d to facilitate access to one or more communication networks, such as the CN 106, the Internet 110, and/or the other networks 112.
  • the base stations 114a, 114b may be a base transceiver station (BTS), a Node-B, an eNode B, a Home Node B, a Home eNode B, a gNB, a NR NodeB, a site controller, an access point (AP), a wireless router, and the like. While the base stations 114a, 114b are each depicted as a single element, it will be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and/or network elements.
  • the base station 114a may be part of the RAN 104/113, which may also include other base stations and/or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc.
  • BSC base station controller
  • RNC radio network controller
  • the base station 114a and/or the base station 114b may be configured to transmit and/or receive wireless signals on one or more carrier frequencies, which may be referred to as a cell (not shown). These frequencies may be in licensed spectrum, unlicensed spectrum, or a combination of licensed and unlicensed spectrum.
  • a cell may provide coverage for a wireless service to a specific geographical area that may be relatively fixed or that may change over time. The cell may further be divided into cell sectors.
  • the cell associated with the base station 114a may be divided into three sectors.
  • the base station 114a may include three transceivers, i.e., one for each sector of the cell.
  • the base station 114a may employ multiple-input multiple output (MIMO) technology and may utilize multiple transceivers for each sector of the cell.
  • MIMO multiple-input multiple output
  • beamforming may be used to transmit and/or receive signals in desired spatial directions.
  • the base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.).
  • the air interface 116 may be established using any suitable radio access technology (RAT).
  • RAT radio access technology
  • the communications system 100 may be a multiple access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, and the like.
  • the base station 114a in the RAN 104/113 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 116 using wideband CDMA (WCDMA).
  • WCDMA may include communication protocols such as High-Speed Packet Access (HSPA) and/or Evolved HSPA (HSPA+).
  • HSPA may include High-Speed Downlink (DL) Packet Access (HSDPA) and/or High-Speed UL Packet Access (HSUPA).
  • the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE) and/or LTE-Advanced (LTE-A) and/or LTE-Advanced Pro (LTE-A Pro).
  • E-UTRA Evolved UMTS Terrestrial Radio Access
  • LTE Long Term Evolution
  • LTE-A LTE-Advanced
  • LTE-A Pro LTE-Advanced Pro
  • the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR Radio Access , which may establish the air interface 116 using New Radio (NR).
  • a radio technology such as NR Radio Access , which may establish the air interface 116 using New Radio (NR).
  • the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies.
  • the base station 114a and the WTRUs 102a, 102b, 102c may implement LTE radio access and NR radio access together, for instance using dual connectivity (DC) principles.
  • DC dual connectivity
  • the air interface utilized by WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and/or transmissions sent to/from multiple types of base stations (e.g., a eNB and a gNB).
  • the base station 114a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.11 (i.e., Wireless Fidelity (WiFi), IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), and the like.
  • IEEE 802.11 i.e., Wireless Fidelity (WiFi)
  • IEEE 802.16 i.e., Worldwide Interoperability for Microwave Access (WiMAX)
  • CDMA2000, CDMA2000 1X, CDMA2000 EV-DO Code Division Multiple Access 2000
  • IS-95 Interim Standard 95
  • IS-856 Interim Standard 856
  • GSM Global System for
  • the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN).
  • 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).
  • WLAN wireless local area network
  • WPAN wireless personal area network
  • 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.
  • a cellular-based RAT e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR etc.
  • 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 RAN 104/113 and/or the CN 106 may be in direct or indirect communication with other RANs that employ the same RAT as the RAN 104/113 or a different RAT.
  • the CN 106 may also be in communication with another RAN (not shown) employing a GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or WiFi radio technology.
  • the CN 106 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and/or the other networks 112.
  • the PSTN 108 may include circuit-switched telephone networks that provide plain old telephone service (POTS).
  • POTS plain old telephone service
  • the Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the transmission control protocol (TCP), user datagram protocol (UDP) and/or the internet protocol (IP) in the TCP/IP internet protocol suite.
  • the networks 112 may include wired and/or wireless communications networks owned and/or operated by other service providers.
  • the networks 112 may include another CN connected to one or more RANs, which may employ the same RAT as the RAN 104/113 or a different RAT.
  • Some or all of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links).
  • the WTRU 102c shown in FIG. 1A may be configured to communicate with the base station 114a, which may employ a cellular-based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.
  • FIG. 1 B is a system diagram illustrating an example WTRU 102.
  • the WTRU 102 may include a processor 118, a transceiver 120, a transmit/receive element 122, a speaker/microphone 124, a keypad 126, a display/touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and/or other peripherals 138, among others.
  • GPS global positioning system
  • the processor 118 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like.
  • the processor 118 may perform signal coding, data processing, power control, input/output processing, and/or any other functionality that enables the WTRU 102 to operate in a wireless environment.
  • the processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit/receive element 122. While FIG. 1 B depicts the processor 118 and the transceiver 120 as separate components, it will be appreciated that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.
  • the transmit/receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 114a) over the air interface 116.
  • the transmit/receive element 122 may be an antenna configured to transmit and/or receive RF signals.
  • the transmit/receive element 122 may be an emitter/detector configured to transmit and/or receive IR, UV, or visible light signals, for example.
  • the transmit/receive element 122 may be configured to transmit and/or receive both RF and light signals. It will be appreciated that the transmit/receive element 122 may be configured to transmit and/or receive any combination of wireless signals.
  • the WTRU 102 may include any number of transmit/receive elements 122. More specifically, the WTRU 102 may employ MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit/receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.
  • the WTRU 102 may include two or more transmit/receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.
  • the transceiver 120 may be configured to modulate the signals that are to be transmitted by the transmit/receive element 122 and to demodulate the signals that are received by the transmit/receive element 122.
  • the WTRU 102 may have multi-mode capabilities.
  • the transceiver 120 may include multiple transceivers for enabling the WTRU 102 to communicate via multiple RATs, such as NR and IEEE 802.11 , for example.
  • 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 non-removable memory 130 may include random-access memory (RAM), read-only memory (ROM), a hard disk, or any other type of memory storage device.
  • the removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like.
  • SIM subscriber identity module
  • SD secure digital
  • the processor 118 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as on a server or a home computer (not shown).
  • the processor 118 may receive power from the power source 134, and may be configured to distribute and/or control the power to the other components in the WTRU 102.
  • the power source 134 may be any suitable device for powering the WTRU 102.
  • the power source 134 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium- ion (Li-ion), etc.), solar cells, fuel cells, and the like.
  • 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 peripherals 138 may include one or more sensors, the sensors may be one or more of a gyroscope, an accelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor; a geolocation sensor; an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and/or a humidity sensor.
  • a gyroscope an accelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor; a geolocation sensor; an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and/or a humidity sensor.
  • the WTRU 102 may include a full duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for both the UL (e.g., for transmission) and downlink (e.g., for reception) may be concurrent and/or simultaneous.
  • the full duplex radio may include an interference management unit to reduce and or substantially eliminate self-interference via either hardware (e.g., a choke) or signal processing via a processor (e.g., a separate processor (not shown) or via processor 118).
  • 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 WTRU is described in FIGs. 1 A-1 B as a wireless terminal, it is contemplated that in certain representative embodiments that such a terminal may use (e.g., temporarily or permanently) wired communication interfaces with the communication network.
  • the other network 112 may be a WLAN.
  • one or more, or all, of the functions described herein may be performed by one or more emulation devices (not shown).
  • the emulation devices may be one or more devices configured to emulate one or more, or all, of the functions described herein.
  • the emulation devices may be used to test other devices and/or to simulate network and/or WTRU functions.
  • the emulation devices may be designed to implement one or more tests of other devices in a lab environment and/or in an operator network environment.
  • the one or more emulation devices may perform the one or more, or all, functions while being fully or partially implemented and/or deployed as part of a wired and/or wireless communication network in order to test other devices within the communication network.
  • the one or more emulation devices may perform the one or more, or all, functions while being temporarily implemented/deployed as part of a wired and/or wireless communication network.
  • the emulation device may be directly coupled to another device for purposes of testing and/or may performing testing using over-the-air wireless communications.
  • 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. 1C 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 WC (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
  • WC Very Video Coding
  • 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 input devices of block 172 have associated respective input processing elements as known in the art.
  • the RF portion can be associated with elements suitable for (i) selecting a desired frequency (also referred to as selecting a signal, or band-limiting a signal to a band of frequencies), (ii) downconverting the selected signal, (iii) band-limiting again to a narrower band of frequencies to select (for example) a signal frequency band which can be referred to as a channel in certain embodiments, (iv) demodulating the downconverted and band-limited signal, (v) performing error correction, and (vi) demultiplexing to select the desired stream of data packets.
  • 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.
  • 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.
  • 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.
  • 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.
  • a CU can be up to 128x128 pixels.
  • a coding tree unit (CTU) is split into CUs to adapt to varying local characteristics based on quad/binary/ternary-tree.
  • 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. Also, if multiple reference pictures are supported, 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.
  • MVs motion vectors
  • 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 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.
  • 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.
  • Point clouds have arisen as one of the main 3D scene representations for such applications.
  • a point cloud frame is a set of 3D points, each point being represented with its 3D position and possibly several attributes such as color, transparency, and reflectance.
  • a standardization activity for point cloud compression is carried out by the ISO/IEC JTC1/SC29/WG7 "MPEG 3D Graphics and Haptics Coding” group. See Graziosi, Damillo, et al., An Overview of Ongoing Point Cloud Compression Standardization Activities: Video-Based (V-PCC) and Geometry-Based (G-PCC), 9:1 APSIPA TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING 1-15 (2020) (“Graz/os/”). The first edition of the Geometry-based Point Cloud Compression (G-PCC) standard, part 9 of the ISO/IEC 23090 series on the coded representation of immersive media has been published.
  • G-PCC Geometry-based Point Cloud Compression
  • FIG. 4 is a process diagram illustrating an example global point cloud compression according to some embodiments.
  • Input geometry 402 and input attributes 404 may be sequentially compressed as illustrated by a process 400 in FIG. 4.
  • the geometry is first compressed (encoded) by the geometry encoder 406 to generate a geometry bitstream 416.
  • the encoded (compressed) geometry is then decoded by a geometry decoder 408, and a point cloud is reconstructed at full resolution by a geometry reconstruction process 410.
  • the reconstructed geometry is used as an input into an attribute transfer process 412 and as an input into the attribute encoder 414.
  • the input attributes 404 are transferred onto the reconstructed geometry (after decompression) and compressed.
  • the output of the attribute encoder 414 is an attribute bitstream 418.
  • the reconstructed geometry is available when decoding the attributes.
  • FIG. 5 is a schematic illustration showing an example Geometry-based Point Cloud Compression (G-PCC) encoding for dense dynamic point clouds according to some embodiments.
  • G-PCC Geometry-based Point Cloud Compression
  • the geometry is encoded by a GeS-TM codec with an octree representation 504 for the N-T coarsest resolution levels 502 (beginning from the root node at level 0) followed by a surface approximation (triangle soup or "TriSoup” 506) of all occupied nodes at level N-T-1. See GeS TM 1.0.
  • the left diagram is a 2D tree representation of the 3D octree recursive subdivision of each cube into 8 sub-cubes at the finer level.
  • a parent node has 8 children.
  • the 8 circles correspond to 8 sub-cubes.
  • a recursive process begins at the root level, level 0. When incrementing a level by 1 , each occupied parent cube is divided into 8 child cubes. This recursive process may continue until each cube contains at most one point (leaf level) or a stopping decision is made (which may be at an arbitrary level for some embodiments).
  • FIG. 6 is a schematic illustration showing an example TriSoup rasterization.
  • the compressed geometry is decoded and a point cloud is reconstructed at full resolution prior to attribute encoding.
  • the decoded TriSoup surface representation 602 is rasterized to recover 3D sampled points 600, as illustrated in FIG. 6.
  • an attribute transfer step (or "recoloring”) is necessary to project the attributes from 3D points of the input geometry to 3D points of the reconstructed geometry, which may differ for a lossy compression.
  • FIG. 7 is an illustration showing example scenes with fine topology according to some embodiments.
  • 3D scene representations such as 3D meshes and point clouds.
  • One area of difference between these two schemes relates to volumes with fine topologies, such as hair 702, fur 706, and other examples 704, 708 seen in FIG. 7.
  • An advantage of a point cloud representation over 3D meshes is being able to represent such volumes, which cannot be approximated with surface models.
  • a drawback to a point cloud representation is the huge volume of raw data, which requires efficient data compression techniques. This drawback is particularly true for dense dynamic point clouds, such as ones addressed by the G-PCC, Second Edition.
  • the G-PCC, Second Edition standard discusses compressing the geometry of dynamic dense point clouds using a surface-based modelling approach, the so-called "TriSoup” process.
  • This systematic meshing of the leaf nodes of the octree representation is understood to be in contradiction with the above-mentioned advantage of point cloud over mesh representations.
  • the attained compression performance is understood to be at the expense of a loss of precision in all scene parts with fine topology, which cannot be represented with elementary triangles.
  • the color attribute compression of TriSoup modelled nodes does not take advantage of the compressed representation with triangles, since a rasterization process is applied to come back to a point-based representation prior to color transformation.
  • a problem to solve is how to improve compression performance of a point cloud encoding system by leveraging surface modelling for both geometry and attribute compression but only in relevant 3D scene parts.
  • the advantages of point-based and surface-based models may be combined depending on the local characteristics of a point cloud for both geometry and attributes.
  • a point cloud encoding/decoding scheme based on a point-based octree representation of the geometry is combined with a surface-based 3D-mesh representation (e.g., with a triangle soup) of individual nodes if applicable.
  • a node at any level in which the associated point set may be approximated with a meshed surface with minimal loss an octree decomposition may be replaced with a local 3D-mesh representation of the node.
  • the compression of attributes combines a point-based method (e.g., RAHT) for the octree parts with a texture atlas for the 3D- meshed nodes.
  • a point cloud encoding/decoding scheme is based on a hybrid of point-based and 3D-mesh-based representations of the geometry.
  • FIG. 8 is a schematic illustration showing an example hybrid octree / mesh geometry representation according to some embodiments.
  • the principle of a geometry encoding process 800 is illustrated in FIG. 8.
  • An octree representation is generated, starting with the root node (level 0, in which the voxel size is 2 w -i X 2 w -i X 2 w -i) down to the leaf nodes 806 (level N-1 , in which the voxel size 1 x1 x1).
  • recursive node splitting of a node at any level may be stopped, and the node geometry may be represented with a more compact 3D mesh.
  • the final geometry representation may combine a pruned octree, which may reach the finest resolution level N-1 , for some parts of the 3D scene, with a number of "mesh nodes” of different sizes for the remaining parts.
  • the mesh representation may be a G-PCC TriSoup representation as mentioned in Graziosi.
  • any variant of 3D meshes may be applied.
  • the decision to stop the octree split and use a mesh representation for a given node may be based on the average geometric distance between the reconstructed point cloud for a decoded mesh representation and the original point cloud part for the node. If this average geometric distance is above a (predetermined) threshold, the octree recursive split may continue to a finer level.
  • a reconstructed point cloud is obtained by rasterizing the mesh, as explained above.
  • the distance used is the average point to point distance for the closest point in the other point cloud, also known as “D1”.
  • the distance used is the average point to plane distance in the direction of a normal vector, also known as “D2”.
  • FIG. 9A is a schematic illustration showing example faces of a mesh representation of a geometry used with a texture atlas encoding of attributes of a single TriSoup node according to some embodiments.
  • FIG. 9B is a schematic illustration showing an example projection of attributes of each face in a 2D texture atlas used with a texture atlas encoding of attributes of a single TriSoup node according to some embodiments.
  • All triangles in FIG. 9A are projected onto the 2D texture atlas image of FIG. 9B as triangles 952 without overlap.
  • Each triangle vertex with 3D coordinates 902 (x, y, z) is mapped with 2D coordinates (u, v) in the image plane.
  • Such a list of coordinates (u, v) for triangle vertices allows association of any valid pixel (inside a triangle) in the texture atlas with its attribute value to a position (x, y, z) in the 3D space 900, and vice versa.
  • Any 3D position (x, y, z) belonging to a triangle 904 in the 3D space 900 may be mapped to a coordinate (u, v) in the 2D atlas frame 950.
  • Attribute values projected in the texture atlas may be compressed using conventional 2D video coding and, after video decoding, may be de-projected in the 3D space to reconstruct the point cloud.
  • the attributes are separately encoded using a (classical) texture atlas representation, in which each triangle 904 in 3D space 900 is mapped to a triangle 952 in a 2D atlas frame 950.
  • the attributes of a mesh node are encoded as a 2D compressed color image associated with the (u,v) coordinates in an atlas of each vertex in a mesh representation.
  • the texture atlas representation is illustrated for a single mesh node in FIGs. 9A and 9B. If there are multiple mesh nodes, all of their attributes may be mapped to a single texture atlas. FIGs.
  • FIG. 9A and 9B show a texture atlas encoding of the attributes of a single TriSoup node.
  • FIG. 9A shows the faces of a mesh representation
  • FIG. 9B shows the projection of attributes of each face in a 2D texture atlas.
  • any (x, y, z) to (u, v) mapping may be applied in theory. But good practice of efficient texture mapping algorithms project perpendicularly to the 3D surface to avoid spatial distortion and to keep uniform sampling. For some embodiments, the pixel sampling rate of triangles may vary, making the 2D size of each pixel bigger or smaller.
  • the positions of the triangles do not matter as long as the triangles do not overlap.
  • FIG. 10A is a schematic illustration showing an example sampling of a texture atlas according to some embodiments.
  • FIG. 10B is a schematic illustration showing an example recovery of attributes of 3D rasterized points of a mesh face according to some embodiments.
  • the decoded texture atlas is sampled according to the rasterization of the mesh.
  • FIGs. 10A and 10B illustrate an example reconstruction for a given triangle 1002 of a triangle soup representation of the geometry of a leaf node.
  • Each rasterized point 1004 (x, y, z) is associated with a position (u, v) in the texture atlas.
  • FIG. 10A shows a rasterized sampling of a texture atlas.
  • FIG. 10B shows how each rasterized point 1004 (x, y, z) has been mapped and associated with a position (u, v) in the U-V space 1050.
  • the points in FIG. 10A lie in (x, y, z) 3D space 1000 but all points intersect with triangles 1052, 1054 that represent the appropriated surface.
  • FIG. 11 is a process diagram illustrating an example hybrid point cloud encoding according to some embodiments.
  • a pruned octree is generated by deciding at every node creation whether to continue the 8-ary split or to model the node as a meshed surface.
  • a two-part geometry bitstream is generated, with octree-represented points in the first part of the geometry bitstream and meshed surfaces with faces described by connected vertices in the second part of the geometry bitstream.
  • a point cloud attribute transform e.g., RAHT
  • RAHT texture atlas is generated for the attribute bitstream (the second part of the geometry).
  • the process 1100 shown in FIG. 11 may be implemented as described here for some embodiments.
  • an iteration counter (i) is set to 0.
  • a decision 1108 is performed to determine if the current level is a leaf. If the current level is not a leaf, then the process 1100 loops back to check 1106 the surface criteria for the current level.
  • a pruned octree 1114 is generated as the first part of the geometry bitstream. If the surface criteria was met for a particular node at a particular level, then a meshing process 1112 is performed to generate a surface model 1116 for this given node, which is added to the second part of the geometry bitstream.
  • a pruned octree 1114 was generated, then the pruned octree 1114 and attributes 1102 of the point cloud are as inputs to a point cloud attribute coding process (e.g., RAHT) 1118.
  • Point cloud attribute coding is performed to generate transformed coefficients as the first part of the attribute bitstream.
  • a surface model 1116 was generated, then the surface model 1116 and attributes 1102 of the point cloud are as inputs to a texture mapping process 1120. Texture mapping is performed to generate a texture atlas. The texture atlas is passed through a 2D video encoder 1122 to generate the video bitstream. The (u, v) coordinates come from the texture mapping and are combined with the video bitstream to form the second part of the attribute bitstream.
  • FIG. 12 is a process diagram illustrating an example hybrid point cloud decoding according to some embodiments.
  • the pruned octree 1202 is decoded, and the associated point cloud geometry is reconstructed 1206.
  • the associated attributes come from decoding of the transform coefficients 1220 (via a "point cloud attribute decoding” process 1212).
  • FIG. 13 is a flowchart illustrating an example hybrid point cloud encoding according to some embodiments.
  • an example process 1300 may include obtaining 1302 a point cloud, the point cloud including: a first set of information describing a geometry of the point cloud, and a second set of information describing attributes of the point cloud.
  • the example process 1300 may further include performing 1304 a geometry encoding process, wherein the geometry encoding process generates a geometry bitstream, and wherein the geometry bitstream includes a pruned octree associated with a first part of the geometry of the point cloud and a surface model associated with a second part of the geometry of the point cloud.
  • FIG. 14 is a flowchart illustrating an example hybrid point cloud decoding according to some embodiments.
  • an example process 1400 may include obtaining 1402 a geometry bitstream associated with a point cloud and an attribute bitstream associated with the point cloud, wherein the geometry bitstream includes octree data and surface model data, and wherein the attribute bitstream includes one or more transformation coefficients and texture atlas data.
  • the example process 1400 may further include performing 1404 an octree reconstruction process using the octree data, wherein the octree reconstruction process generates a first portion of a geometry of the point cloud.
  • the example process 1400 may further include reconstructing 1406 surface data of the point cloud using the surface model data.
  • the example process 1400 may further include performing 1408 a point cloud attribute decoding on the transformation coefficients to generate a first set of attributes associated with the point cloud.
  • the example process 1400 may further include performing 1410 texture atlas decoding to generate a second set of attributes associated with the point cloud.
  • XR extended reality
  • some embodiments may be applied to any XR contexts such as, e.g., virtual reality (VR) / mixed reality (MR) / augmented reality (AR) contexts.
  • VR virtual reality
  • MR mixed reality
  • AR augmented reality
  • head mounted display HMD
  • some embodiments may be applied to a wearable device (which may or may not be attached to the head) capable of, e.g., XR, VR, AR, and/or MR for some embodiments.
  • a first example method in accordance with some embodiments may include: obtaining a point cloud, wherein the point cloud may include: a first set of information describing a geometry of the point cloud, and a second set of information describing attributes of the point cloud; performing a geometry encoding process, wherein the geometry encoding process generates a geometry bitstream, and wherein the geometry bitstream including a pruned octree associated with a first part of the geometry of the point cloud and a surface model associated with a second part of the geometry of the point cloud; performing an attribute coding process, wherein the attribute coding process generates a first part of an attribute bitstream, and wherein the first part of attribute bitstream includes transformation coefficients; performing a texture atlas process, wherein the texture atlas process generates a second part of an attribute bitstream, and wherein the second part of attribute bitstream includes a video bitstream and texture atlas coordinates; and outputting an output bitstream including the geometry bitstream and the attribute bitstream.
  • the geometry encoding process may include: initializing an octree process; responsive to determining an octree threshold is satisfied for a current node, performing the octree process, wherein the octree process may include: performing an 8-way split of a portion of the geometry associated with the current node; and responsive to determining the geometry associated with the current node is a leaf, generating, upon exiting the octree process, a pruned octree associated with the current node; and incrementing the current node; and returning to a start of the octree process to determine if the octree threshold is satisfied; and responsive to determining the octree threshold is failed for the current node, performing a meshing process to generate a surface mode associated with the current node.
  • the octree threshold is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • an average geometric distance between a reconstructed version of the point cloud for a decoded mesh representation and the point cloud originally obtained is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • an average point to point distance for a closest point in another point cloud is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • an average point to plane distance in a direction of a normal vector is used to determine a division of the geometry of the point cloud into the first portion and the second portion.
  • the texture atlas process may include: performing a texture mapping process to generate texture atlas mesh node data and atlas coordinates; and encoding the texture atlas mesh node data to generate the video bitstream.
  • the attribute coding process is performed using the pruned octree associated with the first portion of the geometry of the point cloud.
  • the texture atlas process is performed using the surface model associated with the second portion of the geometry of the point cloud.
  • the attribute coding process may include a Region-Adaptive Hierarchical Transform (RAHT) process.
  • RAHT Region-Adaptive Hierarchical Transform
  • a first 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 one of the methods listed above.
  • a second example method in accordance with some embodiments may include: obtaining a geometry bitstream associated with a point cloud and an attribute bitstream associated with the point cloud, wherein the geometry bitstream may include octree data and surface model data, and wherein the attribute bitstream may include one or more transformation coefficients and texture atlas data; performing an octree reconstruction process using the octree data, wherein the octree reconstruction process generates a first portion of a geometry of the point cloud; reconstructing surface data of the point cloud using the surface model data; performing a point cloud attribute decoding on the transformation coefficients to generate a first set of attributes associated with the point cloud; and performing texture atlas decoding to generate a second set of attributes associated with the point cloud.
  • performing texture atlas decoding may include: passing the texture atlas data through a decoder; mapping an output of the decoder onto mesh faces to generate a mapped texture; and sampling the mapped texture to generate the second set of attributes associated with the point cloud.
  • performing texture atlas decoding further may include sampling the rasterized and reconstructed surface as part of generating the second set of attributes associated with the point cloud.
  • reconstructing the surface data may include: performing a surface reconstruction process using the surface model data to generate a reconstructed surface; and rasterizing the reconstructed surface to generate a second portion of the geometry of the point cloud.
  • the reconstructed surface data is the second portion of the geometry of the point cloud.
  • 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 one of the methods listed above.
  • a third example point cloud encoding method based on a point-based octree representation of geometry combined with a surface-based 3D-mesh representation of individual nodes may include: responsive to determining, during an octree generation process, for any current node at any current level, an associated point set is able to be approximated with a meshed surface with minimal loss, performing a sub-process, wherein the sub-process may include: stopping the octree generation process; replacing, for the current node, an output of the octree generation process with a local 3D-mesh representation; and combining a point-based method for octree generation process outputs for at least one other node with a texture atlas for 3D-meshed nodes.
  • 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 one of the methods listed above.
  • a fourth example point cloud decoding method based on a point-based octree representation of geometry combined with a surface-based 3D-mesh representation of individual nodes may include: decoding a pruned octree; reconstructing an associated point cloud geometry; decoding an attribute transform to generate associated attributes; reconstructing a surface mesh model; decoding a texture atlas; mapping the decoded texture atlas onto mesh faces; rasterizing the surface mesh model; and sampling the mapped texture.
  • 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 one of the methods listed above.
  • a fifth example apparatus in accordance with some embodiments may include at least one processor configured to perform any one of the methods listed above.
  • a sixth 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 seventh 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.
  • An example signal in accordance with some embodiments may include a bitstream generated according to 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.
  • At least one of the aspects generally relates to video encoding and decoding, and at least one other aspect generally relates to transmitting a bitstream generated or encoded.
  • At least one of the aspects can be implemented as a method, an apparatus, a computer readable storage medium having stored thereon instructions for encoding or decoding video data according to any of the methods described, and/or a computer readable storage medium having stored thereon a bitstream generated according to any of the methods described.
  • 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.
  • HDR high dynamic range
  • SDR standard dynamic range
  • each of the methods comprises one or more steps or actions for achieving the described method. Unless a specific order of steps or actions is required for proper operation of the method, the order and/or use of specific steps and/or actions may be modified or combined. Additionally, terms such as “first”, “second”, etc. may be used in various embodiments to modify an element, component, step, operation, etc., such as, for example, a "first decoding” and a "second decoding”. Use of such terms does not imply an ordering to the modified operations unless specifically required. So, in this example, the first decoding need not be performed before the second decoding, and may occur, for example, before, during, or in an overlapping time period with the second decoding.
  • 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.
  • 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.
  • Decoding can encompass all or part of the processes performed, for example, on a received encoded sequence in order to produce a final output suitable for display.
  • processes include one or more of the processes typically performed by a decoder, for example, entropy decoding, inverse quantization, inverse transformation, and differential decoding.
  • processes also, or alternatively, include processes performed by a decoder of various implementations described in this disclosure, for example, extracting a picture from a tiled (packed) picture, determining an upsampling filter to use and then upsampling a picture, and flipping a picture back to its intended orientation.
  • decoding refers only to entropy decoding
  • decoding refers only to differential decoding
  • decoding refers to a combination of entropy decoding and differential decoding. Whether the phrase “decoding process” is intended to refer specifically to a subset of operations or generally to the broader decoding process will be clear based on the context of the specific descriptions.
  • encoding can encompass all or part of the processes performed, for example, on an input video sequence in order to produce an encoded bitstream.
  • processes include one or more of the processes typically performed by an encoder, for example, partitioning, differential encoding, transformation, quantization, and entropy encoding.
  • processes also, or alternatively, include processes performed by an encoder of various implementations described in this disclosure.
  • encoding refers only to entropy encoding
  • encoding refers only to differential encoding
  • encoding refers to a combination of differential encoding and entropy encoding.
  • Various embodiments refer to rate distortion optimization.
  • the rate distortion optimization is usually formulated as minimizing a rate distortion function, which is a weighted sum of the rate and of the distortion.
  • the approaches may be based on an extensive testing of all encoding options, including all considered modes or coding parameters values, with a complete evaluation of their coding cost and related distortion of the reconstructed signal after coding and decoding.
  • Faster approaches may also be used, to save encoding complexity, in particular with computation of an approximated distortion based on the prediction or the prediction residual signal, not the reconstructed one.
  • a mix of these two approaches can also be used, such as by using an approximated distortion for only some of the possible encoding options, and a complete distortion for other encoding options.
  • Other approaches only evaluate a subset of the possible encoding options.
  • many approaches employ any of a variety of techniques to perform the optimization, but the optimization is not necessarily a complete evaluation of both the coding cost and related distortion.
  • the implementations and aspects described herein can be implemented in, for example, a method or a process, an apparatus, a software program, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method), the implementation of features discussed can also be implemented in other forms (for example, an apparatus or program).
  • An apparatus can be implemented in, for example, appropriate hardware, software, and firmware.
  • the methods can be implemented in, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device.
  • processors also include communication devices, such as, for example, computers, cell phones, portable/personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users.
  • PDAs portable/personal digital assistants
  • references to "one embodiment” or “an embodiment” or “one implementation” or “an implementation”, as well as other variations thereof, means that a particular feature, structure, characteristic, and so forth described in connection with the embodiment is included in at least one embodiment.
  • the appearances of the phrase “in one embodiment” or “in an embodiment” or “in one implementation” or “in an implementation”, as well any other variations, appearing in various places throughout this disclosure are not necessarily all referring to the same embodiment.
  • Determining the information can include one or more of, for example, estimating the information, calculating the information, predicting the information, or retrieving the information from memory.
  • 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.
  • this disclosure may refer to "receiving” various pieces of information.
  • Receiving is, as with “accessing”, intended to be a broad term.
  • Receiving the information can include one or more of, for example, accessing the information, or retrieving the information (for example, from memory).
  • “receiving” is typically involved, in one way or another, during operations such as, for example, storing the information, processing the information, transmitting the information, moving the information, copying the information, erasing 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.
  • the word "signal” refers to, among other things, indicating something to a corresponding decoder.
  • the encoder signals a particular one of a plurality of parameters for region-based filter parameter selection for de-artifact filtering.
  • the same parameter is used at both the encoder side and the decoder side.
  • an encoder can transmit (explicit signaling) a particular parameter to the decoder so that the decoder can use the same particular parameter.
  • signaling can be used without transmitting (implicit signaling) to simply allow the decoder to know and select the particular parameter.
  • signaling can be accomplished in a variety of ways. For example, one or more syntax elements, flags, and so forth are used to signal information to a corresponding decoder in various embodiments. While the preceding relates to the verb form of the word "signal”, the word “signal” can also be used herein as a noun.
  • 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.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Computer Graphics (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • Signal Processing (AREA)
  • Processing Or Creating Images (AREA)

Abstract

Certains modes de réalisation d'un procédé peuvent consister à : obtenir un nuage de points, le nuage de points comprenant : un premier ensemble d'informations décrivant une géométrie du nuage de points, ainsi qu'un second ensemble d'informations décrivant des attributs du nuage de points ; effectuer un processus de codage de géométrie, le processus de codage de géométrie générant un flux binaire de géométrie, et le flux binaire de géométrie comprenant un octree élagué associé à une première partie de la géométrie du nuage de points et un modèle de surface associé à une seconde partie de la géométrie du nuage de points ; effectuer un processus de codage d'attribut, le processus de codage d'attribut générant une première partie d'un flux binaire d'attribut, et la première partie du flux binaire d'attribut comprenant des coefficients de transformation ; effectuer un processus d'atlas de texture, le processus d'atlas de texture générant une seconde partie d'un flux binaire d'attribut, puis générer un flux binaire de sortie comprenant le flux binaire de géométrie et le flux binaire d'attribut.
PCT/EP2024/077874 2023-10-09 2024-10-03 Procédé de codage de nuage de points hybride avec représentation de surface locale Pending WO2025078267A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP23306740.4 2023-10-09
EP23306740 2023-10-09

Publications (1)

Publication Number Publication Date
WO2025078267A1 true WO2025078267A1 (fr) 2025-04-17

Family

ID=88600583

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2024/077874 Pending WO2025078267A1 (fr) 2023-10-09 2024-10-03 Procédé de codage de nuage de points hybride avec représentation de surface locale

Country Status (1)

Country Link
WO (1) WO2025078267A1 (fr)

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
ALEXANDRE ZAGHETTO (SONY) ET AL: "[AI-GC][EE 5.3-ralated] Hybrid S-DPCC Geometry + V-PCC Attribute Coding", no. m62679, 19 April 2023 (2023-04-19), XP030309752, Retrieved from the Internet <URL:https://dms.mpeg.expert/doc_end_user/documents/142_Antalya/wg11/m62679-v1-m62679.S-DPCC+VPCC.zip m62679.S-DPCC VPCC.docx> [retrieved on 20230419] *
DOREA CAMILO ET AL: "Adaptive Block Partitioning of Point Clouds for Video-Based Color Compression", 2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), IEEE, 25 October 2020 (2020-10-25), pages 2746 - 2749, XP033869887, DOI: 10.1109/ICIP40778.2020.9191065 *
KATHARIYA BIRENDRA ET AL: "Scalable Point Cloud Geometry Coding with Binary Tree Embedded Quadtree", 2018 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), IEEE, 23 July 2018 (2018-07-23), pages 1 - 6, XP033417560, DOI: 10.1109/ICME.2018.8486481 *
ZHOU QINGYANG ET AL: "GPCGC: A Green Point Cloud Geometry Coding Method", 2023 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), IEEE, 8 October 2023 (2023-10-08), pages 480 - 484, XP034468133, DOI: 10.1109/ICIP49359.2023.10223048 *

Similar Documents

Publication Publication Date Title
EP3895431A1 (fr) Système et procédé d&#39;exécution de colorisation de données spatiales
EP4588242A1 (fr) Suréchantillonnage basé sur un voxel sensible au contexte pour un traitement de nuage de points
WO2024220568A1 (fr) Codage prédictif génératif pour compression de nuage de points
KR20250108615A (ko) 이기종 메시 자동 인코더
WO2025049125A1 (fr) Traitement amélioré des caractéristiques pour la compression d&#39;images basé sur l&#39;apprentissage de la distribution des caractéristiques
JP2025536907A (ja) テクスチャメッシュの点ベースの属性転送
WO2025078267A1 (fr) Procédé de codage de nuage de points hybride avec représentation de surface locale
WO2025078201A1 (fr) Schéma de codage d&#39;attribut de nuage de points à deux étages avec transformées locales et globales imbriquées
EP4636611A1 (fr) Prédiction basée sur l&#39;apprentissage raht
US20250365427A1 (en) Multi-resolution motion feature for dynamic pcc
WO2025080594A1 (fr) Caractéristique d&#39;arbre octal pour compression de nuage de points basée sur des caractéristiques profondes
WO2025149464A1 (fr) Procédés de prédiction alternative pour la transformation en ondelettes par relèvement sur des surfaces de maillages par subdivision
WO2025080447A1 (fr) Codage prédictif implicite pour compression de nuage de points
WO2025078337A1 (fr) Représentation multimédia d&#39;avatar pour transmission
WO2025153193A1 (fr) Codec multimedia d&#39;avatar géométrique pour une transmission
US20250343920A1 (en) Rate control for point cloud coding with a hyperprior model
US20250324089A1 (en) Reproducible learning-based point cloud coding
WO2025080446A1 (fr) Codage prédictif explicite pour compression de nuage de points
WO2025080438A1 (fr) Dynamique intra-trame pour compression de nuage de points lidar
US20250337952A1 (en) Providing segmentation information for immersive video
EP4633166A1 (fr) Intra-prédiction multicouche inter-blocs pour transformation hiérarchique s&#39;adaptant à la région
WO2025101793A1 (fr) Mesure de géométrie adaptative pour des nuages de points 3d
WO2025049126A1 (fr) Traitement de caractéristiques amélioré pour compression de nuage de points sur la base d&#39;un apprentissage de distribution de caractéristiques
WO2025153195A1 (fr) Représentation multimédia d&#39;avatar pour une transmission
WO2025014553A1 (fr) Codage prédictif génératif pour compression de nuage de points lidar

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 24786409

Country of ref document: EP

Kind code of ref document: A1