[go: up one dir, main page]

WO2025149464A1 - Procédés de prédiction alternative pour la transformation en ondelettes par relèvement sur des surfaces de maillages par subdivision - Google Patents

Procédés de prédiction alternative pour la transformation en ondelettes par relèvement sur des surfaces de maillages par subdivision

Info

Publication number
WO2025149464A1
WO2025149464A1 PCT/EP2025/050213 EP2025050213W WO2025149464A1 WO 2025149464 A1 WO2025149464 A1 WO 2025149464A1 EP 2025050213 W EP2025050213 W EP 2025050213W WO 2025149464 A1 WO2025149464 A1 WO 2025149464A1
Authority
WO
WIPO (PCT)
Prior art keywords
samples
signal
mesh
input signal
sample
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/EP2025/050213
Other languages
English (en)
Inventor
Maja KRIVOKUCA
Olivier Mocquard
Jean-Eudes Marvie
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 WO2025149464A1 publication Critical patent/WO2025149464A1/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
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/105—Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
    • 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
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/12—Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
    • 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
    • H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
    • H04N19/51—Motion estimation or motion compensation
    • H04N19/537—Motion estimation other than block-based
    • H04N19/54—Motion estimation other than block-based using feature points or meshes
    • 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
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/63—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets

Definitions

  • V3C Visual volumetric video-based coding
  • V3C Information technology — Coded representation of immersive media — Part 5: Visual volumetric video-based coding (V3C) and video-based point cloud compression (V-PCC).
  • V-DMC Video-based dynamic mesh coding
  • the V-DMC framework may involve different attributes specified for a dynamic mesh sequence.
  • the underlying static mesh codec may decode mesh attributes per face or per vertex. These attributes may provide additional information about the static mesh e.g., color, texture coordinates, normals, reflectance information, transparency information, and/or user-defined attributes.
  • V3C For V-DMC, a framework is developed by extending V3C.
  • V3C is described at ISO/IEC 23090- 5:2021, Information technology — Coded representation of immersive media — Part 5: Visual volumetric video-based coding (V3C) and video-based point cloud compression (V-PCC).
  • V3C Visual volumetric video-based coding
  • V-PCC video-based point cloud compression
  • a first example method in accordance with some embodiments may include: obtaining an input signal corresponding to a mesh; splitting the input signal into a plurality of odd-indexed samples and a plurality of even-indexed samples, wherein the plurality of odd-indexed samples of the input signal correspond to vertices in the mesh at a lower resolution level, and wherein the plurality of even-indexed samples of the input signal correspond to vertices in the mesh at a higher resolution level; determining at least one sample of a predicted signal using at least three of the plurality of odd-indexed samples; and subtracting the predicted signal from the plurality of even-indexed samples to generate a wavelet coefficient signal.
  • Some embodiments of the first example method may further include subtracting the wavelet coefficient signal from the plurality of odd-indexed samples.
  • determining the at least one sample of the predicted signal may include determining at least one weighted value based on four samples of the plurality of odd-indexed samples, wherein the four samples are nearest neighbors of the at least one sample of the predicted signal.
  • the nearest neighbors are vertices of triangles adjacent to the at least one sample of the predicted signal.
  • determining the at least one weighted value based on the four samples of the plurality of odd-indexed samples includes determining an unequal weighting of the four samples.
  • determining the at least one weighted value is based on relative distances of the four samples to the at least one sample of the predicted signal.
  • determining the at least one sample of the predicted signal includes determining at least one weighted value based on three samples of the plurality of odd-indexed samples, wherein the three samples are nearest neighbors of the at least one sample of the predicted signal.
  • the nearest neighbors are vertices of triangles adjacent to the at least one sample of the predicted signal.
  • determining the at least one weighted value based on the three samples of the plurality of odd-indexed samples includes determining an unequal weighting of the three samples.
  • the at least one sample of the predicted signal may include a boundary point of the mesh.
  • 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 wavelet-transformed coarse input signal corresponding to a mesh, wherein the wavelet-transformed coarse input signal includes a first plurality of samples; obtaining a wavelet coefficients input signal corresponding to the mesh; determining at least one sample of a predicted signal using at least three of the first plurality of samples of the mesh signal; adding the predicted signal to the wavelet coefficients input signal to generate a second plurality of samples; and merging the first plurality of samples with the second plurality of samples to generate an output signal corresponding to the mesh.
  • the first plurality of samples corresponds to even-indexed samples of the output signal
  • the second plurality of samples corresponds to odd- indexed samples of the output signal
  • Some embodiments of the second example method may further include subtracting the wavelet coefficients input signal from the wavelet-transformed coarse input signal.
  • determining the at least one sample of the predicted signal may include determining at least one weighted value based on four samples of the first plurality of samples, wherein the four samples are nearest neighbors of the at least one sample of the predicted signal.
  • determining the at least one weighted value is based on relative distances of the four samples to the at least one sample of the predicted signal.
  • the nearest neighbors are vertices of triangles adjacent to the at least one sample of the predicted signal.
  • determining the at least one weighted value based on the three samples of the first plurality of samples includes determining an unequal weighting of the three samples.
  • determining the at least one weighted value is based on relative distances of the three samples to the at least one sample of the predicted signal.
  • a third example method in accordance with some embodiments may include: obtaining an input signal corresponding to a mesh; splitting the input signal into a first plurality of samples and a second plurality of samples, determining at least one sample of a predicted signal using at least three of the first plurality of samples; and subtracting the predicted signal from the second plurality of samples to generate a wavelet coefficient signal.
  • the first plurality of samples of the input signal correspond to vertices in the mesh at a higher resolution level
  • the second plurality of samples of the input signal correspond to vertices in the mesh at a lower resolution level
  • the first plurality of samples of the input signal correspond to even-indexed samples of the input signal
  • the second plurality of samples of the input signal correspond to odd-indexed samples of the input signal
  • An example method of performing a wavelet transform on an input signal corresponding to a mesh in accordance with some embodiments may include: splitting the input signal into lower-resolution samples and higher-resolution samples; generating a prediction signal based on at least three lower-resolution samples for each sample of the prediction signal; and subtracting the prediction signal from the higher- resolution samples to generate a wavelet coefficient signal.
  • 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 apparatus in accordance with some embodiments may include at least one processor configured to perform any one of the methods listed above.
  • a seventh 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.
  • An eighth 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 signal conveying a wavelet coefficient signal generated according to a method 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. 1 C 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 (WC), according to some embodiments.
  • WC Versatile Video Coding
  • FIG. 2B is a functional block diagram of a block-based video decoder, such as a decoder used for WC, 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. 4A is a schematic illustration showing an example base mesh according to some embodiments.
  • FIG. 4B is a schematic illustration showing an example mesh after 1 subdivision iteration according to some embodiments.
  • FIG. 4C is a schematic illustration showing an example mesh after 2 subdivision iterations according to some embodiments.
  • FIG. 4D is a schematic illustration showing an example mesh after 3 subdivision iterations according to some embodiments.
  • FIG. 4E is a schematic illustration showing an example mesh after 4 subdivision iterations according to some embodiments.
  • FIG. 4F is a schematic illustration showing an example mesh after 5 subdivision iterations according to some embodiments.
  • FIG. 5 is a schematic illustration showing an example wavelet coefficient computation in linear polyhedral subdivision according to some embodiments.
  • FIG. 6A is a schematic illustration showing an example regular connectivity of a triangular mesh according to some embodiments.
  • FIG. 6B is a schematic illustration showing an example irregular connectivity of a triangular mesh according to some embodiments.
  • FIG. 7C is a process diagram illustrating an example inverse lifting wavelet transform according to some embodiments.
  • FIG. 7D is a process diagram illustrating an example inverse lifting wavelet transform according to some embodiments.
  • FIG. 8B is a schematic illustration showing an example non-manifold mesh according to some embodiments.
  • FIG. 10A is a schematic illustration showing an example mesh containing a new vertex not on a mesh boundary according to some embodiments.
  • FIG. 15 is a schematic illustration showing an example adjacent triangle of a new vertex on a mesh boundary according to some embodiments.
  • 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 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 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 114b in FIG. 1A may be a wireless router, Home Node B, Home eNode B, or access point, for example, and may utilize any suitable RAT for facilitating wireless connectivity in a localized area, such as a place of business, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), a roadway, and the like.
  • 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).
  • WLAN wireless local area network
  • the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN).
  • the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR etc.) to establish a picocell or femtocell.
  • the base station 114b may have a direct connection to the Internet 110.
  • the base station 114b may not be required to access the Internet 110 via the CN 106.
  • the RAN 104/113 may be in communication with the CN 106, which may be any type of network configured to provide voice, data, applications, and/or voice over internet protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d.
  • the data may have varying quality of service (QoS) requirements, such as differing throughput requirements, latency requirements, error tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, and the like.
  • QoS quality of service
  • the CN 106 may provide call control, billing services, mobile location-based services, pre-paid calling, Internet connectivity, video distribution, etc., and/or perform high-level security functions, such as user authentication.
  • the 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 ofthe 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 I R, 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.
  • 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 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.
  • 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
  • the input to the elements of system 150 can be provided through various input devices as indicated in block 172.
  • Such input devices include, but are not limited to, (i) a radio frequency (RF) portion that receives an RF signal transmitted, for example, over the air by a broadcaster, (ii) a Component (COMP) input terminal (or a set of COMP input terminals), (iii) a Universal Serial Bus (USB) input terminal, and/or (iv) a High Definition Multimedia Interface (HDMI) input terminal.
  • RF radio frequency
  • COMP Component
  • USB Universal Serial Bus
  • HDMI High Definition Multimedia Interface
  • the 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 RF portion of various embodiments includes one or more elements to perform these functions, for example, frequency selectors, signal selectors, band-limiters, channel selectors, filters, downconverters, demodulators, error correctors, and demultiplexers.
  • the RF portion can include a tuner that performs various of these functions, including, for example, downconverting the received signal to a lower frequency (for example, an intermediate frequency or a near-baseband frequency) or to baseband.
  • the RF portion and its associated input processing element receives an RF signal transmitted over a wired (for example, cable) medium, and performs frequency selection by filtering, downconverting, and filtering again to a desired frequency band.
  • Adding elements can include inserting elements in between existing elements, such as, for example, inserting amplifiers and an analog-to-digital converter.
  • the RF portion includes an antenna.
  • the USB and/or HDMI terminals can include respective interface processors for connecting system 150 to other electronic devices across USB and/or HDMI connections. It is to be understood that 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.
  • USB or HDMI interface processing can be implemented within separate interface ICs or within processor 152 as necessary.
  • the demodulated, error corrected, and demultiplexed stream is provided to various processing elements, including, for example, processor 152, and encoder/decoder 156 operating in combination with the memory and storage elements to process the datastream as necessary for presentation on an output device.
  • connection arrangement 174 for example, an internal bus as known in the art, including the Inter- IC (I2C) bus, wiring, and printed circuit boards.
  • I2C Inter- IC
  • the system 150 includes communication interface 160 that enables communication with other devices via communication channel 162.
  • the communication interface 160 can include, but is not limited to, a transceiver configured to transmit and to receive data over communication channel 162.
  • the communication interface 160 can include, but is not limited to, a modem or network card and the communication channel 162 can be implemented, for example, within a wired and/or a wireless medium.
  • Data is streamed, or otherwise provided, to the system 150, in various embodiments, using a wireless network such as a Wi-Fi network, for example IEEE 802.11 (IEEE refers to the Institute of Electrical and Electronics Engineers).
  • the Wi-Fi signal of these embodiments is received over the communications channel 162 and the communications interface 160 which are adapted for Wi-Fi communications.
  • the communications channel 162 of these embodiments is typically connected to an access point or router that provides access to external networks including the Internet for allowing streaming applications and other over-the-top communications.
  • Other embodiments provide streamed data to the system 150 using a set-top box that delivers the data over the HDMI connection of the input block 172.
  • Still other embodiments provide streamed data to the system 150 using the RF connection of the input block 172.
  • various embodiments provide data in a non-streaming manner.
  • various embodiments use wireless networks other than Wi-Fi, for example a cellular network or a Bluetooth network.
  • the system 150 can provide an output signal to various output devices, including a display 176, speakers 178, and other peripheral devices 180.
  • the display 176 of various embodiments includes one or more of, for example, a touchscreen display, an organic light-emitting diode (OLED) display, a curved display, and/or a foldable display.
  • the display 176 can be for a television, a tablet, a laptop, a cell phone (mobile phone), or other device.
  • the display 176 can also be integrated with other components (for example, as in a smart phone), or separate (for example, an external monitor for a laptop).
  • the other peripheral devices 180 include, in various examples of embodiments, one or more of a stand-alone digital video disc (or digital versatile disc) (DVR, for both terms), a disk player, a stereo system, and/or a lighting system.
  • Various embodiments use one or more peripheral devices 180 that provide a function based on the output of the system 150. For example, a disk player performs the function of playing the output of the system 150.
  • control signals are communicated between the system 150 and the display 176, speakers 178, or other peripheral devices 180 using signaling such as AV.Link, Consumer Electronics Control (CEC), or other communications protocols that enable device-to-device control with or without user intervention.
  • the output devices can be communicatively coupled to system 150 via dedicated connections through respective interfaces 164, 166, and 168. Alternatively, the output devices can be connected to system 150 using the communications channel 162 via the communications interface 160.
  • the display 176 and speakers 178 can be integrated in a single unit with the other components of system 150 in an electronic device such as, for example, a television.
  • the display interface 164 includes a display driver, such as, for example, a timing controller (T Con) chip.
  • the 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.
  • 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.
  • 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
  • FIG. 2B gives a block diagram of a block-based video decoder 250.
  • a bitstream is decoded by the decoder elements as described below.
  • Video decoder 250 generally performs a decoding pass reciprocal to the encoding pass as described in FIG. 2A.
  • the encoder 200 also generally performs video decoding as part of encoding video data.
  • the input of the decoder includes a video bitstream 252, which can be generated by video encoder 200.
  • the video bit-stream 252 is first unpacked and entropy decoded at entropy decoding unit 254 to obtain transform coefficients, motion vectors, and other coded information.
  • Picture partition information indicates how the picture is partitioned.
  • the decoder may therefore divide 256 the picture according to the decoded picture partitioning information.
  • the coding mode and prediction information are sent to either the spatial prediction unit 258 (if intra coded) or the temporal prediction unit 260 (if inter coded) to form the prediction block.
  • the residual transform coefficients are sent to inverse quantization unit 262 and inverse transform unit 264 to reconstruct the residual block.
  • the prediction block and the residual block are then added together at 266 to generate the reconstructed block.
  • the reconstructed block may further go through in-loop filtering 268 before it is stored in reference picture store 270 for use in predicting future video blocks.
  • FIG. 3A is a schematic side view illustrating an example waveguide display that may be used with extended reality (XR) applications according to some embodiments.
  • An image is projected by an image generator 302.
  • the image generator 302 may use one or more of various techniques for projecting an image.
  • the image generator 302 may be a laser beam scanning (LBS) projector, a liquid crystal display (LCD), a light-emitting diode (LED) display (including an organic LED (OLED) or micro LED (piLED) display), a digital light processor (DLP), a liquid crystal on silicon (LCoS) display, or other type of image generator or light engine.
  • LBS laser beam scanning
  • LCD liquid crystal display
  • LED light-emitting diode
  • LED organic LED
  • piLED micro LED
  • DLP digital light processor
  • LCDoS liquid crystal on silicon
  • Light representing an image 312 generated by the image generator 302 is coupled into a waveguide 304 by a diffractive in-coupler 306.
  • the in-coupler 306 diffracts the light representing the image 312 into one or more diffractive orders.
  • light ray 308 which is one of the light rays representing a portion of the bottom of the image, is diffracted by the in-coupler 306, and one of the diffracted orders 310 (e.g. the second order) is at an angle that is capable of being propagated through the waveguide 304 by total internal reflection.
  • the image generator 302 displays images as directed by a control module 324, which operates to render image data, video data, point cloud data, or other displayable data.
  • V-DMC implements the coding using a Lifting Wavelet Transform (Sweldens, W., The Lifting Scheme: A Construction of Second Generation Wavelets, 29:2 SIAM J. MATHEMATICAL ANALYSIS 511-546 (1998) (“Sweldens”)).
  • the subdivision wavelets scheme is based on surface subdivision.
  • a base mesh which may be obtained by a mesh simplification (or decimation) process, such as the process described in Garland, M. and Heckbert, P. S., Surface Simplification using Quadric Error, SIGGRAPH’97 (1997) (“Garland'). from a higher-resolution mesh.
  • the base mesh contains a relatively small number of vertices and faces.
  • the mesh is progressively refined using a subdivision process that iteratively adds new vertices and faces to the mesh by subdividing the existing faces into smaller sub-faces. The new vertices are then displaced to new positions according to some pre-defined rules, to progressively refine the mesh shape, as shown in the example in FIGs. 4A to 4F.
  • FIG. 4A is a schematic illustration showing an example base mesh according to some embodiments.
  • FIG. 4B is a schematic illustration showing an example mesh after 1 subdivision iteration according to some embodiments.
  • FIG. 4C is a schematic illustration showing an example mesh after 2 subdivision iterations according to some embodiments.
  • FIG. 4D is a schematic illustration showing an example mesh after 3 subdivision iterations according to some embodiments.
  • FIG. 4E is a schematic illustration showing an example mesh after 4 subdivision iterations according to some embodiments.
  • FIG. 4F is a schematic illustration showing an example mesh after 5 subdivision iterations according to some embodiments.
  • V-DMC surface subdivision scheme
  • the default choice is a midpoint subdivision scheme, which inserts at each iteration a new vertex at the midpoint of each existing edge.
  • FIGs. 4A-4F illustrate a subdivision process.
  • FIG. 4A shows a base mesh 402, which is to be refined.
  • FIGs. 4B to 4F show the resulting mesh models 404, 406, 408, 410, 412 after a different number of subdivision iterations.
  • the model 412 in FIG. 4F has been rendered with interpolated shading to demonstrate its smoothness, while the meshes 402, 404, 406, 408, 410 in FIGs. 4A-4E are shown in their faceted form to illustrate the addition of new vertices and sub-faces at each subdivision iteration.
  • the simplest form of subdivision wavelets as described in Lounsberry 1 and Lounsberry 2, which has linear time complexity for analysis and synthesis, may be implemented by a piecewise linear subdivision that is basically equivalent to the Lifting Wavelet Transform (Sweldens).
  • the lowest-resolution approximation of the mesh shape is represented by the base mesh, and the wavelet coefficients between any two successive resolution (subdivision) levels represent the differences between the “child” vertex x, y, z positions at the higher resolution level and the prediction of these child positions from the positions of their “parents” at the lower resolution level.
  • the resulting wavelet coefficient w is the difference between the final position of v and its prediction m .
  • the base mesh, and therefore the mesh geometry, may be progressively refined by successively adding more wavelet coefficients to inserted vertices at higher resolution (subdivision) levels.
  • the subdivision wavelets framework relies on the fact that the connectivity of the base mesh may be refined in a predictable manner (by using a set of standard subdivision rules known to both the encoder and decoder) to obtain the final higher-resolution mesh.
  • most mesh models as understood, do not have a predictable regular or semi-regular connectivity.
  • FIG. 6A is a schematic illustration showing an example regular connectivity of a triangular mesh according to some embodiments.
  • FIG. 6B is a schematic illustration showing an example irregular connectivity of a triangular mesh according to some embodiments.
  • FIG. 6C is a schematic illustration showing an example semi-regular connectivity of a triangular mesh according to some embodiments.
  • V-DMC the original input mesh is first downsampled (e.g., by using the method in Garland) to obtain a base mesh, and then a midpoint subdivision scheme is applied to iteratively upsample the base mesh again to reach approximately the same resolution (number of vertices and faces) as the original mesh.
  • a midpoint subdivision scheme is applied to iteratively upsample the base mesh again to reach approximately the same resolution (number of vertices and faces) as the original mesh.
  • the number of vertices and faces in the upsampled mesh is usually much larger than in the original mesh.
  • FIGs 6A-6C show examples of different connectivity types for a triangular mesh:
  • FIG. 6A shows an example 600 of regular connectivity, in which all the vertices have the same number of incident edges.
  • FIG. 6B shows an example 630 of irregular connectivity, in which the vertices may have different numbers of incident edges.
  • FIG. 6C shows an example 660 of semi-regular connectivity, in which most vertices have a regular connectivity, while some have irregular connectivity.
  • FIG. 7B shows an example transform 720 using higher resolution level samples as odd-indexed samples with the following steps: an odd/even split 722, a prediction (P) 724, a computation 726 of wavelet coefficients, and an update (U) block 728.
  • the input to the odd/even split block 702 is a signal (in this case, the x, and z components of the displacement vectors, which are treated separately) that is split into even-indexed and odd-indexed samples, such that each group contains half the samples of the original signal.
  • This splitting step is sometimes called a “Lazy Wavelet Transform”.
  • the odd-indexed and even-indexed samples correspond to vertices at different resolution levels.
  • the odd-indexed samples normally correspond to vertices at a lower resolution level (analogous to the result of a low-pass filter in a traditional wavelet transform), and the even-indexed samples correspond to vertices at a higher resolution level.
  • odd-indexed samples may correspond to higher resolution level samples and even-indexed samples may correspond to lower-resolution level samples.
  • FIGs. 7B and 7D Such a scenario is shown in FIGs. 7B and 7D, while the converse is shown in FIGs. 7A and 7C.
  • the prediction (P) 704 step computes a prediction (approximation) for the even samples based on the odd samples (also may be the other way around).
  • the prediction is computed as shown in Eq. 2: in which v 12 represents a new vertex that is added in the middle of the edge (v 1; v 2 ), and Signal(v ⁇ ) and Signal(v 2 ) are the values of the signals (displacement values, in this case) at the vertices and v 2 , respectively.
  • the predicted value for the displacement at vertex v 12 is the average of the signal (displacement) values on the vertices v r and v 2 .
  • the Update (U) 708 step adds the wavelet coefficients to the odd signal samples (which represent the coarser signal “approximation”). This addition recovers some of the energy lost during signal splitting and prepares the signal for the next prediction step (if there is one).
  • V-DMC the update is currently computed as shown in Eq. 4: in which w E vindicates the wavelet coefficients for the neighboring vertices of vertex v.
  • the V-DMC TM also has an option to skip the Update step altogether.
  • FIG. 7A shows the Forward Lifting Wavelet Transform 700 used in V-DMC and shown in Mammou.
  • FIG. 7C shows the Inverse Wavelet Transform 740, which is used at the decoder to reconstruct the input signal (displacements) from the coarse approximation and the wavelet coefficients, proceeds in the reverse direction to the Forward Wavelet Transform.
  • the Inverse Wavelet Transform is also performed at the encoder to reconstruct the mesh geometry so that texture transfer may be applied before texture compression. See FIG. 11.
  • This application describes a modification to the “Predict” step (Eq. 2) of the Lifting Wavelet Transform.
  • This prediction is based on a linear interpolation (averaging) between the signals on the two parent vertices on the edge where the new child vertex is inserted.
  • the value of the signal at the child vertex is predicted by using the signal values of its parents on the same edge and the signal values on the other vertices of the triangles adjacent to this edge.
  • FIG. 8A is a schematic illustration showing an example manifold mesh according to some embodiments.
  • FIG. 8B is a schematic illustration showing an example non-manifold mesh according to some embodiments.
  • FIG. 8C is a schematic illustration showing an example non-manifold mesh according to some embodiments.
  • FIG. 8A For a manifold triangle mesh 800 with boundaries, see FIG. 8A.
  • the edges on the boundary each have only one adjacent triangle, while the edges away from the boundary each have two adjacent triangles.
  • FIGs. 8B and 8C are non-manifold meshes 830, 860.
  • each edge that is not on a boundary is shared by only two faces and not more, and one ring of connected faces must be around each vertex, not a broken ring, as in FIG. 8B.
  • Boundary edges are shared by only one face.
  • FIG. 10A is a schematic illustration showing an example mesh containing a new vertex not on a mesh boundary according to some embodiments.
  • FIG. 10B is a schematic illustration showing an example mesh containing a new vertex on a mesh boundary according to some embodiments.
  • FIG. 10A shows an example of a manifold triangle mesh 1000 in which the edge 1002 containing the newly inserted vertex 1004 is not on a mesh boundary.
  • Point c (1004) is a newly inserted vertex.
  • Points a (1006) and b (1008) are the direct parent nodes.
  • Points d (1010) and e (1012) are additional neighbors that may be used in addition to points a (1006) and b (1008) to predict the location of point e (1004), which may be expressed as a signal value of the newly inserted vertex.
  • the predicted signal at each new vertex may be calculated as an average of the signal values of the neighbors, as shown in FIG. 10A and in Eq. 5:
  • Pred c 4 (5) in which Si ⁇ (... ) is the signal value (e.g., displacement value in V-DMC) of the corresponding vertex.
  • FIG. 10B the corresponding prediction is shown in Eq. 6:
  • 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.
  • 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.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Discrete Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Certains modes de réalisation d'un procédé peuvent consister à : obtenir un signal d'entrée correspondant à un maillage ; diviser le signal d'entrée en une pluralité d'échantillons à indice impair et une pluralité d'échantillons à indice pair, la pluralité d'échantillons à indice impair du signal d'entrée correspondant à des sommets dans le maillage à un niveau de résolution inférieur, et la pluralité d'échantillons à indice pair du signal d'entrée correspondant à des sommets dans le maillage à un niveau de résolution supérieur ; déterminer au moins un échantillon d'un signal prédit à l'aide d'au moins trois échantillons de la pluralité d'échantillons à indice impair ; et soustraire le signal prédit de la pluralité d'échantillons à indice pair pour générer un signal de coefficient d'ondelettes.
PCT/EP2025/050213 2024-01-11 2025-01-07 Procédés de prédiction alternative pour la transformation en ondelettes par relèvement sur des surfaces de maillages par subdivision Pending WO2025149464A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP24305075 2024-01-11
EP24305075.4 2024-01-11

Publications (1)

Publication Number Publication Date
WO2025149464A1 true WO2025149464A1 (fr) 2025-07-17

Family

ID=89767020

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2025/050213 Pending WO2025149464A1 (fr) 2024-01-11 2025-01-07 Procédés de prédiction alternative pour la transformation en ondelettes par relèvement sur des surfaces de maillages par subdivision

Country Status (1)

Country Link
WO (1) WO2025149464A1 (fr)

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
"V-DMC codec description", no. n23036, 16 October 2023 (2023-10-16), XP030323710, Retrieved from the Internet <URL:https://dms.mpeg.expert/doc_end_user/documents/143_Geneva/wg11/MDS23036_WG07_N00644.zip MDS23036_WG07_N00644_VDMC_codec_description.docx> [retrieved on 20231016] *
KAMMOUN AYMEN ET AL: "Sparsity-based optimization of two lifting-based wavelet transforms for semi-regular mesh compression", COMPUTERS AND GRAPHICS., vol. 36, no. 4, 14 March 2012 (2012-03-14), GB, pages 272 - 282, XP093214568, ISSN: 0097-8493, DOI: 10.1016/j.cag.2012.02.004 *
KRIVOKUCA MAJA ET AL: "Zerotree Coding of Subdivision Wavelet Coefficients in Dynamic Time-Varying Meshes", 2 December 2023 (2023-12-02), pages 1 - 10, XP093260987, Retrieved from the Internet <URL:https://www.techrxiv.org/doi/full/10.36227/techrxiv.24615081.v1> *
LOOP CHARLES TEORELL: "Smooth Subdivision Surfaces Based on Triangles", MASTER THESIS. DEPARTMENT OF MATHEMATICS, 1 August 1987 (1987-08-01), pages 1 - 74, XP093261481, Retrieved from the Internet <URL:https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/thesis-10.pdf> *
PATRICE RONDAO ALFACE (NOKIA) ET AL: "[V-DMC][NEW] Butterfly Lifting Transform", no. m61599, 9 January 2023 (2023-01-09), XP030307397, Retrieved from the Internet <URL:https://dms.mpeg.expert/doc_end_user/documents/141_OnLine/wg11/m61599-v1-m61599_butterfly_lifting.zip m61599-ButterflyLiftingTransform.docx> [retrieved on 20230109] *
SWELDENS WIM ET AL: "Building your own wavelets at home", 1 January 2000 (2000-01-01), XP009557709, ISBN: 978-3-540-66951-7, Retrieved from the Internet <URL:http://link.springer.com/10.1007/BFb0011093> *

Similar Documents

Publication Publication Date Title
US20250119579A1 (en) Coordinate refinement and upsampling from quantized point cloud reconstruction
WO2024086165A1 (fr) Suréchantillonnage basé sur un voxel sensible au contexte pour un traitement de nuage de points
EP4300964A2 (fr) Affinement de précision pour compensation de mouvement à flux optique
WO2024220568A1 (fr) Codage prédictif génératif pour compression de nuage de points
WO2024102920A1 (fr) Autocodeurs maillés hétérogènes
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
WO2025149464A1 (fr) Procédés de prédiction alternative pour la transformation en ondelettes par relèvement sur des surfaces de maillages par subdivision
EP4636611A1 (fr) Prédiction basée sur l&#39;apprentissage raht
CN115136602A (zh) 具有多个测量结果的3d点云增强
WO2025078267A1 (fr) Procédé de codage de nuage de points hybride avec représentation de surface locale
US20250365427A1 (en) Multi-resolution motion feature for dynamic pcc
US20250337952A1 (en) Providing segmentation information for immersive video
WO2025080594A1 (fr) Caractéristique d&#39;arbre octal pour compression de nuage de points basée sur des caractéristiques profondes
WO2025078201A1 (fr) Schéma de codage d&#39;attribut de nuage de points à deux étages avec transformées locales et globales imbriquées
US20250324089A1 (en) Reproducible learning-based point cloud coding
WO2025080447A1 (fr) Codage prédictif implicite pour compression de nuage de points
WO2025080438A1 (fr) Dynamique intra-trame pour compression de nuage de points lidar
WO2025080446A1 (fr) Codage prédictif explicite pour compression de nuage de points
WO2025101793A1 (fr) Mesure de géométrie adaptative pour des nuages de points 3d
US20250343920A1 (en) Rate control for point cloud coding with a hyperprior model
WO2025153193A1 (fr) Codec multimedia d&#39;avatar géométrique pour une transmission
WO2025168559A1 (fr) Convolutions de micro-patch pour compression d&#39;attribut de nuage de points
TW202545191A (zh) 用於點雲屬性壓縮的微補片卷積
WO2025078337A1 (fr) Représentation multimédia d&#39;avatar pour transmission

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: 25701050

Country of ref document: EP

Kind code of ref document: A1