WO2020190097A1 - Dispositif de réception de données de nuage de points, procédé de réception de données de nuage de points, dispositif de traitement de données de nuage de points, et procédé de traitement de données de nuage de points - Google Patents

Dispositif de réception de données de nuage de points, procédé de réception de données de nuage de points, dispositif de traitement de données de nuage de points, et procédé de traitement de données de nuage de points Download PDF

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Publication number
WO2020190097A1
WO2020190097A1 PCT/KR2020/003892 KR2020003892W WO2020190097A1 WO 2020190097 A1 WO2020190097 A1 WO 2020190097A1 KR 2020003892 W KR2020003892 W KR 2020003892W WO 2020190097 A1 WO2020190097 A1 WO 2020190097A1
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WIPO (PCT)
Prior art keywords
point cloud
patch
data
image
unit
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PCT/KR2020/003892
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English (en)
Korean (ko)
Inventor
이장원
오세진
오현묵
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엘지전자 주식회사
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Publication of WO2020190097A1 publication Critical patent/WO2020190097A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—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
    • 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
    • H04N19/593—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving spatial prediction techniques
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/597—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/235—Processing of additional data, e.g. scrambling of additional data or processing content descriptors
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/236—Assembling of a multiplex stream, e.g. transport stream, by combining a video stream with other content or additional data, e.g. inserting a URL [Uniform Resource Locator] into a video stream, multiplexing software data into a video stream; Remultiplexing of multiplex streams; Insertion of stuffing bits into the multiplex stream, e.g. to obtain a constant bit-rate; Assembling of a packetised elementary stream

Definitions

  • the embodiments are point cloud content to provide users with various services such as VR (Virtual Reality), AR (Augmented Reality, Augmented Reality), MR (Mixed Reality, Mixed Reality), and autonomous driving service. Content).
  • a point cloud is a set of points in a three-dimensional space. There is a problem in that it is difficult to generate point cloud data because the amount of points in the 3D space is large.
  • the technical problem according to the embodiments is to provide a point cloud data processing apparatus, a processing method, a point cloud data receiving apparatus, and a receiving method for efficiently transmitting and receiving a point cloud in order to solve the above-described problems.
  • a technical problem according to embodiments is to provide a point cloud data processing apparatus, a processing method, a point cloud data receiving apparatus, and a receiving method for solving latency and encoding/decoding complexity.
  • the method for receiving point cloud data includes receiving a bitstream including point cloud data, decoding point cloud data, and rendering the decoded point cloud data. Includes steps.
  • the point cloud data receiving apparatus includes a receiving unit receiving a bitstream including point cloud data, a decoder for decoding point cloud data, and a renderer for rendering the decoded point cloud data.
  • a method of processing point cloud data includes demultiplexing a bitstream including point cloud data to output one or more sub-bitstreams.
  • One or more sub-bitstreams are a first sub-bitstream corresponding to geometry, a second sub-bitstream corresponding to an attribute, a third sub-bitstream corresponding to an ocupancy map, and one or more patches And a fourth sub-bitstream corresponding to.
  • the point cloud data processing method includes the steps of decompressing one or more sub-bitstreams to output geometry data, attribute data, ocupancy map data, and patch data corresponding to the one or more patches, and And reconstructing point cloud data based on geometry data, attribute data, ocupancy map data, and patch data.
  • the point cloud data processing apparatus includes a demultiplexer that outputs one or more sub-bitstreams by demultiplexing a bitstream including point cloud data.
  • One or more sub-bitstreams may include a first sub-bitstream corresponding to a geometry, a second sub-bitstream corresponding to an attribute, a third sub-bitstream corresponding to an ocupancy map, and one or more. It includes a fourth sub-bitstream corresponding to patches.
  • the point cloud data processing apparatus includes one or more processors and one or more memories.
  • One or more processors according to embodiments execute one or more programs stored in one or more memories, and the one or more programs include instructions for instructing to process point cloud data.
  • Instructions according to embodiments output geometry data, attribute data, occupancy map data, and patch data corresponding to one or more patches by decompressing the one or more sub-bitstreams, and geometry data, attribute data , Instructing to reconstruct the point cloud data based on the map data and the patch data when occupied.
  • the point cloud data receiving method, the point cloud data receiving apparatus, the point cloud data processing method, and the point cloud data processing apparatus may provide a point cloud service with high quality.
  • a point cloud data receiving method, a point cloud data receiving apparatus, a point cloud data processing method, and a point cloud data processing apparatus may achieve various video codec methods.
  • the point cloud data receiving method, the point cloud data receiving apparatus, the point cloud data processing method, and the point cloud data processing apparatus may provide general-purpose point cloud content such as an autonomous driving service.
  • FIG. 1 shows an example of a structure of a transmission/reception system for providing Point Cloud content according to embodiments.
  • FIG. 2 shows an example of capturing point cloud data according to embodiments.
  • FIG. 3 shows an example of a point cloud, geometry, and texture image according to embodiments.
  • FIG. 4 shows an example of V-PCC encoding processing according to embodiments.
  • FIG. 5 shows an example of a tangent plane and a normal vector of a surface according to embodiments.
  • FIG. 6 shows an example of a bounding box of a point cloud according to embodiments.
  • FIG 7 shows an example of positioning an individual patch of an occupancy map according to embodiments.
  • FIG. 8 shows an example of a relationship between a normal, a tangent, and a bitangent axis according to embodiments.
  • FIG. 9 illustrates an example of a configuration of a minimum mode and a maximum mode of a projection mode according to embodiments.
  • FIG 10 shows an example of an EDD code according to embodiments.
  • FIG. 11 illustrates an example of recoloring using color values of adjacent points according to embodiments.
  • FIG 12 illustrates an example of push-pull background filling according to embodiments.
  • FIG. 13 shows an example of a traversal order possible for a block having a size of 4*4 according to embodiments.
  • FIG. 15 shows an example of a 2D video/image encoder according to embodiments.
  • V-PCC decoding process shows an example of a V-PCC decoding process according to embodiments.
  • FIG. 17 shows an example of a 2D Video/Image Decoder according to embodiments.
  • FIG. 18 shows an example of a flowchart of an operation of a transmission device according to embodiments.
  • FIG. 19 illustrates an example of a flowchart of an operation of a reception device according to embodiments.
  • FIG 20 shows an example of an architecture for V-PCC-based point cloud data storage and streaming according to embodiments.
  • FIG. 21 shows an example of a configuration diagram of an apparatus for storing and transmitting point cloud data according to embodiments.
  • FIG. 22 shows an example of a configuration diagram of an apparatus for receiving point cloud data according to embodiments.
  • FIG. 23 shows an example of a structure capable of interworking with a method/device for transmitting and receiving point cloud data according to embodiments.
  • 26 is an example of a safeguard insertion method according to embodiments.
  • 29 is a syntax of patch data unit information according to embodiments.
  • FIG. 30 is a flow diagram of a method for receiving point cloud data according to embodiments.
  • 31 is a flow diagram of a method for processing point cloud data according to embodiments.
  • FIG. 1 shows an example of a structure of a transmission/reception system for providing Point Cloud content according to embodiments.
  • Point Cloud content is provided to provide users with various services such as VR (Virtual Reality), AR (Augmented Reality, Augmented Reality), MR (Mixed Reality, Mixed Reality), and autonomous driving service.
  • VR Virtual Reality
  • AR Augmented Reality
  • MR Magnetic Reality
  • autonomous driving service Provide a solution.
  • Point cloud content represents data representing an object as points, and may be referred to as point cloud, point cloud data, point cloud video data, point cloud image data, and the like.
  • the point cloud data transmission device (transmission device) 10000 includes a point cloud video acquisition unit (Point Cloud Video Acquisition unit, 10001), a point cloud video encoder (Point Cloud Video Encoder, 10002), a file/segment encapsulation It includes a ration unit 10003 and/or a transmitter (or communication module) 10004.
  • the transmission device according to the embodiments may secure, process, and transmit a point cloud video (or point cloud content).
  • the transmission device includes a fixed station, a base transceiver system (BTS), a network, an artificial intelligence (AI) device and/or system, a robot, an AR/VR/XR device and/or server, etc. can do.
  • the transmission device 10000 uses a radio access technology (eg, 5G NR (New RAT), LTE (Long Term Evolution)) to communicate with a base station and/or other wireless devices, Robots, vehicles, AR/VR/XR devices, portable devices, home appliances, Internet of Thing (IoT) devices, AI devices/servers, etc. may be included.
  • a radio access technology eg, 5G NR (New RAT), LTE (Long Term Evolution)
  • the Point Cloud Video Acquisition unit 10001 acquires a Point Cloud video through a process of capturing, synthesizing, or generating a Point Cloud video.
  • a point cloud video encoder 10002 encodes the point cloud video data acquired by the point cloud video acquisition unit 10001.
  • the point cloud video encoder 10002 may be referred to as a point cloud encoder, a point cloud data encoder, an encoder, or the like.
  • point cloud compression coding (encoding) according to the embodiments is not limited to the above-described embodiments.
  • the point cloud video encoder may output a bitstream including encoded point cloud video data.
  • the bitstream may include not only the encoded point cloud video data, but also signaling information related to encoding of the point cloud video data.
  • the point cloud video encoder 10002 may support both a Geometry-based Point Cloud Compression (G-PCC) encoding method and/or a Video-based Point Cloud Compression (V-PCC) encoding method.
  • the point cloud video encoder 10002 may encode the point cloud (referring to point cloud data or all points) and/or signaling data related to the point cloud.
  • the file/segment encapsulation module 10003 encapsulates point cloud data in the form of files and/or segments.
  • the point cloud data transmission method/apparatus according to the embodiments may transmit point cloud data in the form of a file and/or a segment.
  • a transmitter (or communication module) 10004 transmits the encoded point cloud video data in the form of a bitstream.
  • a file or segment may be transmitted to a receiving device through a network, or may be stored in a digital storage medium (eg, USB, SD, CD, DVD, Blu-ray, HDD, SSD, etc.).
  • the transmitter according to the embodiments is capable of wired/wireless communication with a receiving device (or a receiver and a network such as 4G, 5G, 6G, etc.)
  • the transmitter can communicate with a network system A necessary data processing operation may be performed depending on the network system), and the transmission device may transmit encapsulated data according to an on demand method.
  • the point cloud data receiving device 10005 includes a receiver 10006, a file/segment decapsulation unit 10007, a point cloud video decoder 10008, and/ Or it includes a renderer (10009).
  • the receiving device uses a wireless access technology (eg, 5G NR (New RAT), LTE (Long Term Evolution)) to communicate with a base station and/or other wireless devices, a robot, a vehicle, AR/VR/XR devices, portable devices, home appliances, Internet of Things (IoT) devices, AI devices/servers, etc. may be included.
  • 5G NR New RAT
  • LTE Long Term Evolution
  • IoT Internet of Things
  • the receiver 10006 receives a bitstream including point cloud video data. According to embodiments, the receiver 10006 may transmit feedback information to the point cloud data transmission apparatus 10000.
  • the file/segment decapsulation module 10007 decapsulates a file and/or segment including point cloud data.
  • a point cloud video decoder 10008 decodes the received point cloud video data.
  • the renderer 10009 renders the decoded point cloud video data. According to embodiments, the renderer 10009 may transmit the feedback information obtained at the receiving end to the point cloud video decoder 10008.
  • the point cloud video data may transmit feedback information to the receiver 10006.
  • the feedback information received by the point cloud transmission device may be provided to the point cloud video encoder 10002.
  • the feedback information is information for reflecting an interaction ratio with a user who consumes point cloud content, and includes user information (eg, head orientation information, viewport information, etc.).
  • user information eg, head orientation information, viewport information, etc.
  • the feedback information is the content sending side (for example, the transmission device 10000) and/or a service provider.
  • the feedback information may be used not only in the transmitting device 10000 but also in the receiving device 10005, and may not be provided.
  • Head orientation information is information on a position, direction, angle, and movement of a user's head.
  • the reception device 10005 may calculate viewport information based on the head orientation information.
  • the viewport information is information on the area of the point cloud video that the user is viewing.
  • the viewpoint is a point at which the user is watching the point cloud video, and may mean a center point of the viewport area. That is, the viewport is an area centered on a viewpoint, and the size and shape of the area may be determined by a field of view (FOV).
  • FOV field of view
  • the receiving device 10005 may extract viewport information based on a vertical or horizontal FOV supported by the device in addition to the head orientation information.
  • the receiving device 10005 performs a gaze analysis and the like to check the point cloud consumption method of the user, the point cloud video area the user is staring, and the gaze time.
  • the receiving device 10005 may transmit feedback information including the result of the gaze analysis to the transmitting device 10000.
  • Feedback information may be obtained during rendering and/or display.
  • Feedback information may be secured by one or more sensors included in the receiving device 10005.
  • the feedback information may be secured by the renderer 10009 or a separate external element (or device, component, etc.).
  • a dotted line in FIG. 1 shows a process of transmitting feedback information secured by the renderer 10009.
  • the point cloud content providing system may process (encode/decode) point cloud data based on feedback information.
  • the point cloud video data decoder 10008 may perform a decoding operation based on the feedback information.
  • the receiving device 10005 may transmit feedback information to the transmitting device.
  • the transmission device (or point cloud video encoder 10002) may perform an encoding operation based on feedback information. Therefore, the point cloud content providing system does not process (encode/decode) all point cloud data, but efficiently processes necessary data (e.g., point cloud data corresponding to the user's head position) based on feedback information. Point cloud content can be provided to users.
  • the transmission device 10000 may be referred to as an encoder, a transmission device, a transmitter, and the like
  • the reception device 10005 may be referred to as a decoder, a reception device, a receiver, or the like.
  • Point cloud data (processed in a series of acquisition/encoding/transmission/decoding/rendering) processed in the point cloud content providing system of FIG. 1 according to embodiments may be referred to as point cloud content data or point cloud video data.
  • the point cloud content data may be used as a concept including metadata or signaling information related to the point cloud data.
  • Elements of the point cloud content providing system shown in FIG. 1 may be implemented by hardware, software, processor, and/or a combination thereof.
  • the embodiments are point cloud content to provide various services such as VR (Virtual Reality, virtual reality), AR (Augmented Reality, augmented reality), MR (Mixed Reality, mixed reality), and autonomous driving service. Can provide.
  • VR Virtual Reality, virtual reality
  • AR Algmented Reality, augmented reality
  • MR Mated Reality, mixed reality
  • autonomous driving service Can provide.
  • a Point Cloud video may be obtained first.
  • the acquired Point Cloud video is transmitted to the receiving side through a series of processes, and the receiving side can process and render the received data back into the original Point Cloud video.
  • This allows Point Cloud videos to be presented to users.
  • the embodiments provide a method necessary to effectively perform this series of processes.
  • the overall process (point cloud data transmission method and/or point cloud data reception method) for providing the Point Cloud content service may include an acquisition process, an encoding process, a transmission process, a decoding process, a rendering process, and/or a feedback process. have.
  • a process of providing point cloud content may be referred to as a point cloud compression process.
  • the point cloud compression process may mean a video-based point cloud compression (hereinafter referred to as V-PCC) process.
  • Each element of the point cloud data transmission device and the point cloud data reception device may mean hardware, software, a processor, and/or a combination thereof.
  • the Point Cloud Compression system may include a transmitting device and a receiving device.
  • the transmission device may be referred to as an encoder, a transmission device, a transmitter, a point cloud transmission device, and the like.
  • the reception device may be referred to as a decoder, a reception device, a receiver, a point cloud reception device, or the like.
  • the transmitting device can encode the Point Cloud video and output the bitstream, and can deliver it to the receiving device through a digital storage medium or network in the form of a file or streaming (streaming segment).
  • Digital storage media may include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, and SSD.
  • the transmission device may include a Point Cloud video acquisition unit, a Point Cloud video encoder, a file/segment encapsulation unit, and a transmission unit (or transmitter).
  • the receiving device may include a receiving unit, a file/segment decapsulation unit, a Point Cloud video decoder, and a renderer.
  • the encoder may be referred to as a Point Cloud video/image/picture/frame encoding device
  • the decoder may be referred to as a Point Cloud video/image/picture/frame decoding device.
  • the renderer may include a display unit, and the renderer and/or display unit may be configured as a separate device or an external component.
  • the transmitting device and the receiving device may further include separate internal or external modules/units/components for a feedback process.
  • Each element included in the transmitting device and the receiving device according to the embodiments may be configured with hardware, software and/or a processor.
  • the operation of the receiving device may follow the reverse process of the operation of the transmitting device.
  • the point cloud video acquisition unit may perform a process of acquiring a point cloud video through a process of capturing, synthesizing, or generating a point cloud video.
  • 3D location (x, y, z)/attribute (color, reflectance, transparency, etc.) data for multiple points for example, PLY (Polygon File format or the Stanford Triangle format) file, is created by the acquisition process Can be.
  • PLY Polygon File format or the Stanford Triangle format
  • one or more files may be obtained.
  • point cloud related metadata for example, metadata related to capture, etc.
  • An apparatus for transmitting point cloud data may include an encoder for encoding point cloud data and a transmitter for transmitting (or a bitstream including) point cloud data.
  • the point cloud data receiving apparatus may include a receiving unit receiving a bitstream including point cloud data, a decoder for decoding point cloud data, and a renderer for rendering point cloud data.
  • the method/apparatus according to the embodiments represents a point cloud data transmission device and/or a point cloud data reception device.
  • FIG. 2 shows an example of capturing point cloud data according to embodiments.
  • Point cloud data (or point cloud video data) according to embodiments may be obtained by a camera or the like.
  • the capture method according to embodiments may include, for example, in-word-facing and/or out-of-facing.
  • Inword-pacing is a capture method in which an object of point cloud data is captured by one or more cameras from the outside to the inside.
  • the outward-facing according to the embodiments is a method in which one or more cameras capture an object of point cloud data from the inside to the outside of the object to obtain it. For example, according to embodiments, there may be four cameras.
  • Point cloud data or point cloud content may be video or still images of objects/environments expressed in various types of 3D space.
  • the point cloud content may include a video/audio/image for an object (object, etc.).
  • the equipment for capturing Point Cloud content can be composed of a combination of camera equipment that can acquire depth (a combination of an infrared pattern projector and infrared camera) and RGB cameras that can extract color information corresponding to the depth information. have.
  • the depth information may be extracted through LiDAR, which uses a radar system that measures the position coordinates of the reflector by measuring the return time after shooting a laser pulse.
  • a shape of a geometry composed of points in a 3D space may be extracted from depth information, and an attribute representing the color/reflection of each point may be extracted from RGB information.
  • the Point Cloud content may be composed of information about the location (x, y, z) and color (YCbCr or RGB) or reflectance (r) of the points.
  • Point cloud content may include an outward-facing method for capturing an external environment and an inward-facing method for capturing a central object.
  • objects e.g., key objects such as characters, players, objects, actors, etc.
  • the composition of the capture camera uses the in-word-facing method. Can be used.
  • the configuration of the capture camera may use the outward-facing method. Since Point Cloud content can be captured through multiple cameras, it may be necessary to calibrate the camera before capturing the content in order to set the global coordinate system between the cameras.
  • the Point Cloud content may be a video or still image of an object/environment displayed in various types of 3D space.
  • an arbitrary Point Cloud video can be synthesized based on the captured Point Cloud video. Or, if you want to provide Point Cloud video for a virtual space created by a computer, capture through an actual camera may not be performed. In this case, the capture process may be replaced with a process in which related data is simply generated.
  • the captured Point Cloud video may need post-processing to improve the quality of the content.
  • the maximum/minimum depth value can be adjusted within the range provided by the camera equipment, but point data of the unwanted area may be included even after that, so the unwanted area (eg, background) is removed, or the connected space is recognized.
  • Post-treatment of filling the spatial hole can be performed.
  • the Point Cloud extracted from the cameras sharing the spatial coordinate system can be integrated into one content through the conversion process to the global coordinate system for each point based on the position coordinates of each camera acquired through the calibration process. Through this, a wide range of Point Cloud content can be created, or Point Cloud content with a high density of points can be obtained.
  • the Point Cloud video encoder 10002 may encode an input Point Cloud video into one or more video streams.
  • One point cloud video may include a plurality of frames, and one frame may correspond to a still image/picture.
  • a Point Cloud video may include a Point Cloud image/frame/picture, and the Point Cloud video may be used interchangeably with a Point Cloud image/frame/picture.
  • the Point Cloud video encoder 10002 may perform a Video-based Point Cloud Compression (V-PCC) procedure.
  • the Point Cloud video encoder 10002 may perform a series of procedures such as prediction, transform, quantization, and entropy coding for compression and coding efficiency.
  • the encoded data (encoded video/video information) may be output in the form of a bitstream.
  • the Point Cloud video encoder 10002 divides the Point Cloud video into a geometry video, an attribute video, an occupancy map video, and auxiliary information, as described later. Can be encoded.
  • the geometry video may include a geometry image
  • the attribute video may include an attribute image
  • the occupancy map video may include an accupancy map image.
  • the additional information (or referred to as additional data) may include auxiliary patch information.
  • the attribute video/image may include a texture video/image.
  • the encapsulation unit may encapsulate the encoded point cloud video data and/or point cloud video related metadata in the form of a file or the like.
  • the metadata related to the point cloud video may be transmitted from a metadata processing unit.
  • the metadata processing unit may be included in the point cloud video encoder 10002 or may be configured as a separate component/module.
  • the encapsulation unit 10003 may encapsulate the data in a file format such as ISOBMFF, or may process the data in the form of other DASH segments.
  • the encapsulation unit 10003 may include metadata related to a point cloud video in a file format according to an embodiment.
  • Point cloud video-related metadata may be included in boxes of various levels in the ISOBMFF file format, for example, or may be included as data in separate tracks within the file.
  • the encapsulation unit 10003 may encapsulate the metadata related to the point cloud video as a file.
  • the transmission processing unit may apply processing for transmission to the encapsulated point cloud video data according to the file format.
  • the transmission processing unit may be included in the transmission unit 10004 or may be configured as a separate component/module.
  • the transmission processor may process point cloud video data according to an arbitrary transmission protocol.
  • the processing for transmission may include processing for transmission through a broadcasting network and processing for transmission through a broadband.
  • the transmission processing unit may receive not only the point cloud video data, but also the point cloud video related metadata from the metadata processing unit, and may apply processing for transmission to this.
  • the transmission unit 10004 may transmit the encoded video/video information or data output in the form of a bitstream to the receiver 10006 of the receiving device through a digital storage medium or a network in a file or streaming form.
  • Digital storage media may include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, and SSD.
  • the transmission unit may include an element for generating a media file through a predetermined file format, and may include an element for transmission through a broadcast/communication network.
  • the receiver may extract the bitstream and transmit it to the decoding device.
  • the receiver 10006 may receive point cloud video data transmitted by the point cloud video transmission device according to the present invention. Depending on the transmitted channel, the receiver may receive point cloud video data through a broadcasting network or may receive point cloud video data through a broadband. Alternatively, point cloud video data can be received through a digital storage medium.
  • the reception processing unit may perform processing according to a transmission protocol on the received point cloud video data.
  • the reception processing unit may be included in the receiver 10006 or may be configured as a separate component/module.
  • the reception processing unit may perform the reverse process of the transmission processing unit described above so as to correspond to the transmission processing performed by the transmission side.
  • the reception processing unit may transmit the acquired point cloud video data to the decapsulation unit 10007, and the acquired point cloud video related metadata may be transmitted to the metadata processing unit (not shown).
  • the point cloud video related metadata acquired by the reception processing unit may be in the form of a signaling table.
  • the decapsulation unit may decapsulate the point cloud video data in the form of a file transmitted from the reception processing unit.
  • the decapsulation processing unit 10007 may decapsulate files according to ISOBMFF and the like to obtain a point cloud video bitstream or metadata related to a point cloud video (metadata bitstream).
  • the acquired point cloud video bitstream may be transferred to the point cloud video decoder 10008, and the acquired point cloud video related metadata (metadata bitstream) may be transferred to a metadata processing unit (not shown).
  • the point cloud video bitstream may include metadata (metadata bitstream).
  • the metadata processing unit may be included in the point cloud video decoder 10008, or may be configured as a separate component/module.
  • the metadata related to the point cloud video acquired by the decapsulation processing unit 10007 may be in the form of a box or a track in a file format.
  • the decapsulation processing unit 10007 may receive metadata necessary for decapsulation from the metadata processing unit, if necessary.
  • the point cloud video related metadata may be transmitted to the point cloud video decoder 10008 and used for a point cloud video decoding procedure, or may be transmitted to the renderer 10009 and used for a point cloud video rendering procedure.
  • the point cloud video decoder 10008 may receive a bitstream and perform an operation corresponding to an operation of a point cloud video encoder to decode a video/image.
  • the Point Cloud video decoder 10008 may divide and decode the Point Cloud video into a geometry video, an attribute video, an occupancy map video, and auxiliary information, as described later.
  • the geometry video may include a geometry image
  • the attribute video may include an attribute image
  • the occupancy map video may include an accupancy map image.
  • the additional information may include auxiliary patch information.
  • the attribute video/image may include a texture video/image.
  • the 3D geometry is reconstructed using the decoded geometry image, the accupancy map, and additional patch information, and then the smoothing process can be performed.
  • a color point cloud image/picture may be reconstructed by assigning a color value to the smoothed 3D geometry using a texture image.
  • the renderer 10009 may render the reconstructed geometry and color point cloud image/picture.
  • the rendered video/image may be displayed through a display unit (not shown). The user can view all or part of the rendered result through a VR/AR display or a general display.
  • the feedback process may include a process of transferring various feedback information that can be obtained during the rendering/display process to a transmitter or a decoder at a receiver. Through the feedback process, interactivity can be provided in Point Cloud video consumption.
  • head orientation information, viewport information indicating an area currently viewed by the user, and the like may be transmitted in the feedback process.
  • the user may interact with those implemented in the VR/AR/MR/autonomous driving environment.In this case, information related to the interaction may be transmitted to the transmitting side or the service provider side in the feedback process. have.
  • the feedback process may not be performed.
  • the head orientation information may mean information on the position, angle, and movement of the user's head. Based on this information, information about the area that the user is currently viewing in the Point Cloud video, that is, viewport information can be calculated.
  • the viewport information may be information on an area currently viewed by the user in the Point Cloud video.
  • a gaze analysis is performed, which allows you to check how the user consumes the Point Cloud video, which area of the Point Cloud video and how much they gaze at.
  • the gaze analysis may be performed at the receiving side and transmitted to the transmitting side through a feedback channel.
  • a device such as a VR/AR/MR display may extract a viewport area based on the position/direction of the user's head and a vertical or horizontal FOV supported by the device.
  • the above-described feedback information is not only transmitted to the transmitting side, but may be consumed by the receiving side. That is, decoding and rendering of the receiver may be performed using the above-described feedback information. For example, using head orientation information and/or viewport information, only a point cloud video for a region currently viewed by the user may be preferentially decoded and rendered.
  • the viewport or the viewport area may mean an area that the user is viewing in the Point Cloud video.
  • a viewpoint is a point that a user is viewing in a Point Cloud video, and may mean a center point of a viewport area. That is, the viewport is an area centered on the viewpoint, and the size, shape, etc. occupied by the area may be determined by a field of view (FOV).
  • FOV field of view
  • the present specification relates to Point Cloud video compression as described above.
  • the method/embodiment disclosed in this document may be applied to a point cloud compression or point cloud coding (PCC) standard of Moving Picture Experts Group (MPEG) or a next-generation video/image coding standard.
  • PCC point cloud compression or point cloud coding
  • MPEG Moving Picture Experts Group
  • a picture/frame may generally mean a unit representing one image in a specific time period.
  • a pixel or pel may mean a minimum unit constituting one picture (or image).
  • sample' may be used as a term corresponding to a pixel.
  • a sample may generally represent a pixel or pixel value, and may represent only the pixel/pixel value of the luma component, only the pixel/pixel value of the chroma component, or the depth component. It may also represent only the pixel/pixel value of.
  • a unit may represent a basic unit of image processing.
  • the unit may include at least one of a specific area of a picture and information related to the corresponding area.
  • a unit may be used interchangeably with terms such as a block or an area or a module, depending on the case.
  • the MxN block may include samples (or sample arrays) consisting of M columns and N rows, or a set (or array) of transform coefficients.
  • FIG. 3 shows an example of a point cloud, geometry, and texture image according to embodiments.
  • the point cloud according to the embodiments may be input to the V-PCC encoding process of FIG. 4 to be described later to generate a geometry image and a texture image.
  • the point cloud may have the same meaning as point cloud data.
  • the figure on the left in FIG. 3 is a point cloud, where a point cloud object is located in a 3D space and shows a point cloud that can be represented by a bounding box or the like.
  • the middle figure of FIG. 3 shows a geometry image
  • the right figure shows a texture image (non-padding).
  • a geometry image is also referred to as a geometry patch frame/picture or a geometry frame/picture.
  • the texture image is also referred to as an attribute patch frame/picture or an attribute frame/picture.
  • V-PCC Video-based Point Cloud Compression
  • HEVC Efficiency Video Coding
  • VVC Very Video Coding
  • Occupancy map A binary map that tells whether or not data exists at the corresponding location of the 2D plane by dividing the points of the point cloud into patches and mapping them to the 2D plane with a value of 0 or 1. Represents.
  • Patch A set of points constituting a point cloud, indicating that points belonging to the same patch are adjacent to each other in a 3D space and are mapped in the same direction among the six-sided bounding box planes in the process of mapping to a 2D image.
  • Geometry image Represents an image in the form of a depth map that expresses the geometry of each point constituting a point cloud in patch units.
  • the geometry image may consist of pixel values of one channel.
  • Texture image Represents an image that expresses color information of each point constituting a point cloud in patch units.
  • the texture image may be composed of pixel values (e.g. 3 channels R, G, B) of multiple channels.
  • the texture is included in the attribute.
  • textures and/or attributes may be interpreted as the same object and/or containment relationship.
  • Auxiliary patch info Represents metadata necessary to reconstruct a point cloud from individual patches.
  • the additional patch information may include information on the location and size of the patch in 2D/3D space.
  • Point cloud data represents PCC data according to a Video-based Point Cloud Compression (V-PCC) method.
  • Point cloud data may include a plurality of components. For example, it may include an accufancy map, patch, geometry and/or texture.
  • FIG. 4 shows an example of a point cloud video encoder according to embodiments.
  • FIG. 4 illustrates a V-PCC encoding process for generating and compressing an occupancy map, a geometry image, a texture image, and auxiliary patch information.
  • the V-PCC encoding process of FIG. 4 may be processed by the point cloud video encoder 10002 of FIG. 1.
  • Each component of FIG. 4 may be implemented by software, hardware, a processor, and/or a combination thereof.
  • the patch generation receives a point cloud frame (may be in the form of a bitstream including point cloud data).
  • the patch generation unit 40000 generates a patch from point cloud data. Also, patch information including information on patch generation is generated.
  • Patch packing packs one or more patches.
  • an accufancy map including information on patch packing is generated.
  • the geometry image generation (geometry image generation unit, 40002) generates a geometry image based on point cloud data, patch information (or additional patch information), and/or accufancy map information.
  • the geometry image refers to data (ie, three-dimensional coordinate values of points) including geometry related to point cloud data, and is also referred to as a geometry frame.
  • the texture image generation (texture image generation or texture image generation unit) 40003 generates a texture image based on point cloud data, a patch, a packed patch, patch information (or additional patch information), and/or a smoothed geometry. Texture images are also referred to as attribute frames.
  • the smoothing (smoothing or smoothing unit) 40004 may alleviate or remove errors included in image data. For example, the reconstructed geometry images may be smoothed based on patch information, that is, a portion that may cause errors between data may be smoothly filtered to generate a smoothed geometry.
  • the smoothed geometry is output to the texture image generator 40003.
  • An additional patch information compression (auxiliary patch info compression or additional patch information compression unit) 40005 compresses auxiliary patch information related to patch information generated during a patch generation process.
  • the additional patch information compressed by the additional patch information compression unit 40005 is transmitted to the multiplexer 40013.
  • the geometry image generator 40002 may use additional patch information when generating a geometry image.
  • Image padding may pad a geometry image and a texture image, respectively. That is, the padding data may be padded on the geometry image and the texture image.
  • the group dilation (group dilation unit) 40008 may add data to the texture image, similar to image padding. Additional patch information may be inserted into the texture image.
  • the video compression (video compression or video compression units) 40009, 40010, and 40011 may respectively compress a padded geometry image, a padded texture image, and/or an accupancy map.
  • the video compression units 40009, 40010, and 40011 compress the input geometry frame, attribute frame, and/or accupancy map frame, respectively, and compress the video bitstream of the geometry, the video bitstream of the texture image, and the video of the accupancy map. It can be output as a bitstream.
  • Video compression can encode geometry information, texture information, and accu-fanity information.
  • the entropy compression (entropy compression or entropy compression unit) 40012 may compress the accupancy map based on an entropy method.
  • entropy compression and/or video compression may be performed on a map frame at an accu-fancy according to a case in which point cloud data is lossless and/or lossy.
  • the multiplexer 40013 is a video bitstream of geometry compressed by each compression unit, a video bitstream of a compressed texture image, a video bitstream of a compressed accupancy map, and a bitstream of compressed additional patch information. Is multiplexed into one bitstream.
  • each of the blocks shown in FIG. 4 may operate as at least one of a processor, software, and hardware.
  • the patch generation process refers to a process of dividing a point cloud into patches, which are units that perform mapping, in order to map a point cloud to a 2D image.
  • the patch generation process can be divided into three steps: normal value calculation, segmentation, and patch division.
  • FIG. 5 shows an example of a tangent plane and a normal vector of a surface according to embodiments.
  • the surface of FIG. 5 is used as follows in the patch generation process 40000 of the V-PCC encoding process of FIG. 4.
  • Each point (for example, point) constituting a point cloud has its own direction, which is expressed as a three-dimensional vector called normal.
  • tangent planes and normal vectors of each point constituting the surface of the point cloud as shown in FIG. 5 can be obtained.
  • the search range in the process of finding adjacent points can be defined by the user.
  • tangent plane A plane that passes through a point on the surface and completely contains the tangent to the curve on the surface.
  • FIG. 6 shows an example of a bounding box of a point cloud according to embodiments.
  • the patch generation 4000 may use a bounding box in a process of generating a patch from point cloud data.
  • the bounding box may be used in a process of projecting a point cloud object, which is a target of point cloud data, on a plane of each hexahedron based on a hexahedron in 3D space.
  • the bounding box may be generated and processed by the point cloud video acquisition unit 10001 and the point cloud video encoder 10002 of FIG. 1. Also, based on the bounding box, a patch generation 40000, a patch packing 40001, a geometry image generation 40002, and a texture image generation 40003 of the V-PCC encoding process of FIG. 4 may be performed.
  • Segmentation consists of two processes: initial segmentation and refine segmentation.
  • the point cloud video encoder 10002 projects a point onto one side of a bounding box. Specifically, each point constituting the point cloud is projected on one of the planes of the six bounding box surrounding the point cloud as shown in Fig.6, and the initial segmentation determines one of the planes of the bounding box on which each point is to be projected. It's a process.
  • the normal value of each point obtained in the process of calculating the normal value ( )and The plane where the dot product of is the largest is determined as the projection plane of the corresponding plane.
  • the plane with the normal in the direction most similar to the point normal is determined as the projection plane of the point.
  • the determined plane may be identified as a value in the form of an index (cluster index) from 0 to 5.
  • Refine segmentation is a process of improving the projection plane of each point constituting the point cloud determined in the initial segmentation process in consideration of the projection planes of adjacent points.
  • the projection plane of the current point and the projection plane of the adjacent points together with the score normal that achieves similarity between the normal value of each plane of each point considered for determining the projection plane in the initial segmentation process and the normal value of each plane of the bounding box.
  • the score smooth representing the degree of agreement with can be considered simultaneously.
  • Score smooth can be considered by assigning a weight to the score normal, and in this case, the weight value can be defined by the user. Refine segmentation can be performed repeatedly, and the number of repetitions can also be defined by the user.
  • Patch segmentation is a process of dividing the entire point cloud into patches, a set of adjacent points, based on the projection plane information of each point forming the point cloud obtained in the initial/refine segmentation process. Patch division can consist of the following steps.
  • the size of each patch, occupancy map, geometry image, and texture image for each patch are determined.
  • FIG 7 shows an example of positioning an individual patch of an occupancy map according to embodiments.
  • the point cloud encoder 10002 may generate a patch packing and an accufancy map.
  • This process is a process of determining the positions of individual patches in the 2D image in order to map the previously divided patches to one 2D image.
  • Occupancy map is one of 2D images, and it is a binary map that informs whether or not data exists at a corresponding location with a value of 0 or 1.
  • Occupancy map consists of blocks and its resolution can be determined according to the size of the block. For example, when the block size is 1*1, it has a resolution in units of pixels. The size of the block (occupancy packing block size) can be determined by the user.
  • the process of determining the location of an individual patch in the occupancy map can be configured as follows.
  • the (x, y) coordinate value of the patch occupancy map is 1 (there is data at the point in the patch), and the (u+x, v+y) coordinate of the entire occupancy map If the value is 1 (when the occupancy map is filled by the previous patch), change the (x, y) position in the order of raster order and repeat the process of 34. If not, perform step 6.
  • Accupancy Size U It represents the width of the occupancy map, and the unit is the occupancy packing block size.
  • Accupancy Size V Indicates the height of the occupancy map, and the unit is occupancy packing block size.
  • Patch size U0 (patch.sizeU0): Indicates the width of the occupancy map, and the unit is the occupancy packing block size.
  • Patch size V0 (patch.sizeV0): Indicates the height of the occupancy map, and the unit is occupancy packing block size.
  • a box corresponding to a patch having a patch size in a box corresponding to a packing size block in accupant exists, and points (x, y) in the box may be located.
  • FIG. 8 shows an example of a relationship between a normal, a tangent, and a bitangent axis according to embodiments.
  • the point cloud video encoder 10002 may generate a geometry image.
  • the geometry image refers to image data including geometry information of a point cloud.
  • the geometry image generation process may use three axes (normal, tangent, and bitangent) of the patch of FIG. 8.
  • depth values constituting the geometry image of individual patches are determined, and the entire geometry image is created based on the location of the patch determined in the patch packing process.
  • the process of determining the depth values constituting the geometry image of an individual patch can be configured as follows.
  • the parameters may include the following information.
  • the location of the patch is included in the patch information.
  • the index representing the normal axis The normal is obtained from the previous patch generation process, the tangent axis is the axis that coincides with the horizontal (u) axis of the patch image among the axes perpendicular to the normal, and the bitangent axis is the vertical ( As an axis coincident with the v) axis, the three axes can be expressed as shown in FIG. 8.
  • FIG. 9 illustrates an example of a configuration of a minimum mode and a maximum mode of a projection mode according to embodiments.
  • the point cloud video encoder 10002 may perform patch-based projection to generate a geometric image, and projection modes according to embodiments include a minimum mode and a maximum mode.
  • the patch's 3D space coordinates can be calculated from the smallest bounding box surrounding the patch. For example, the minimum value in the tangent direction of the patch (patch 3d shift tangent axis), the minimum value in the bitangent direction of the patch (patch 3d shift bitangent axis), the minimum value in the normal direction of the patch (patch 3d shift normal axis), etc. Can be included.
  • Patch 2D Size This indicates the horizontal and vertical size of the patch when it is packed into a 2D image.
  • the horizontal size (patch 2d size u) is the difference between the maximum and minimum values in the tangent direction of the bounding box
  • the vertical size (patch 2d size v) can be obtained as the difference between the maximum and the minimum values in the bitangent direction of the bounding box.
  • the projection mode may be one of a min mode and a max mode.
  • the geometry information of the patch is expressed as a depth value.When projecting each point of the patch in the normal direction of the patch, the image consisting of the maximum value of the depth value and the image consisting of the minimum value are created. I can.
  • the minimum depth may be configured in d0, and the maximum depth existing within the surface thickness from the minimum depth may be configured as d1.
  • the point cloud when the point cloud is located in 2D as shown in FIG. 9, there may be a plurality of patches including a plurality of points. As shown in FIG. 9, it indicates that points marked with shades of the same style may belong to the same patch.
  • the drawing shows the process of projecting a patch of points indicated by blank spaces.
  • a number for calculating the depth of the points to the right while increasing the depth by 1, such as 0, 1, 2, ..6, 7, 8, 9 based on the left can be marked.
  • the same method can be applied to all point clouds by user definition, or can be applied differently for each frame or patch.
  • a projection mode capable of increasing compression efficiency or minimizing a missing point may be adaptively selected.
  • d0 image is converted to depth0, which is the value obtained by subtracting the minimum value in the normal direction of the patch (patch 3d shift normal axis) calculated in step 1 from the minimum value in the normal direction of the patch to the minimum value of the normal axis of each point. Make up. If there is another depth value within the range between depth0 and surface thickness at the same location, this value is set to depth1. If not present, the value of depth0 is also assigned to depth1.
  • the d1 image is constructed with the Depth1 value.
  • the minimum value may be calculated (4 2 4 4 4 0 6 0 0 9 9 0 8 0).
  • a larger value among two or more points is calculated, or when there is only one point, the value may be calculated (4 4 4 4 6 6 6 8 9 9 8 8 9 ).
  • some points may be lost during the process of encoding and reconstructing the points of the patch (eg, 8 points are lost in the drawing).
  • the d0 image is the value of the maximum value of the normal axis of each point minus the minimum value in the normal direction (patch 3d shift normal axis) calculated in step 1 from the minimum value in the normal direction of the patch (patch 3d shift normal axis). Configure. If there is another depth value within the range between depth0 and surface thickness at the same location, this value is set to depth1. If not present, the value of depth0 is also assigned to depth1.
  • the d1 image is constructed with the Depth1 value.
  • the maximum value may be calculated (4 4 4 4 6 6 6 8 9 9 8 8 9).
  • a small value among two or more points may be calculated, or if there is only one point, the value may be calculated (4 2 4 4 5 6 0 6 9 9 0 8 0 ).
  • some points may be lost during the process of encoding and reconstructing the points of the patch (eg, 6 points are lost in the drawing).
  • the entire geometry image can be created by placing the geometry image of the individual patch created through the above process on the entire geometry image using the location information of the patch previously determined in the patch packing process.
  • the d1 layer of the entire generated geometry image can be encoded in several ways.
  • the first is a method of encoding the depth values of the previously generated d1 image as it is (absolute d1 encoding method).
  • the second is a method of encoding the difference between the depth value of the d1 image created earlier and the depth value of the d0 image (differential encoding method).
  • EDD Enhanced-Delta- Depth
  • FIG 10 shows an example of an EDD code according to embodiments.
  • the point cloud video encoder 10002 and/or a part/overall process of V-PCC encoding may encode geometric information of points based on the EOD code.
  • Smoothing is an operation for removing discontinuities that may occur at the patch boundary due to deterioration of image quality occurring in the compression process, and may be performed by the point cloud video encoder 10002 or the smoothing unit 40004 in the following process.
  • Reconstruction of a point cloud from a geometry image This process can be said to be the reverse process of the geometry image creation described above.
  • the reverse process of encoding may be reconstruction.
  • the point is located on the patch boundary. For example, if there is an adjacent point having a projection plane (cluster index) different from the current point, it may be determined that the point is located at the patch boundary.
  • FIG. 11 illustrates an example of recoloring using color values of adjacent points according to embodiments.
  • the point cloud video encoder 10002 or the texture image generator 40003 may generate a texture image based on recoloring.
  • the process of creating a texture image is similar to the process of creating a geometry image described above, and consists of creating a texture image of individual patches and placing them at a determined location to create an entire texture image. However, in the process of generating the texture image of an individual patch, an image with the color values (e.g. R, G, B) of the points constituting the point cloud corresponding to the corresponding location is created instead of the depth value for geometry generation.
  • an image with the color values e.g. R, G, B
  • the geometry that has previously been smoothed can be used. Since the smoothed point cloud may be in a state in which the positions of some points have been moved from the original point cloud, a recoloring process to find a color suitable for the changed position may be required. Recoloring can be performed using color values of adjacent points. For example, as shown in FIG. 11, a new color value may be calculated in consideration of a color value of the nearest point and color values of the adjacent points.
  • recoloring is performed based on the average of the attribute information of the closest original points to the point and/or the average of the attribute information of the closest original position to the point. Can be calculated.
  • a texture image can also be created with two layers of t0/t1 like a geometry image created with two layers of d0/d1.
  • the point cloud video encoder 10002 or the additional patch information compression unit 40005 may compress additional patch information (additional information about the point cloud).
  • the additional patch information compression unit 40005 compresses additional patch information generated in the above-described patch generation, patch packing, and geometry generation processes. Additional patch information may include the following parameters:
  • Cluster index that identifies the projection plane (normal)
  • Patch 3D space position minimum value in the tangent direction of the patch (patch 3d shift tangent axis), minimum value in the bitangent direction of the patch (patch 3d shift bitangent axis), minimum value in the normal direction of the patch (patch 3d shift normal axis)
  • Patch 2D space location and size horizontal size (patch 2d size u), vertical size (patch 2d size v), horizontal minimum value (patch 2d shift u), vertical minimum value (patch 2d shift u)
  • Mapping information of each block and patch includes candidate index (When the patches are placed in order based on the 2D spatial location and size information of the above patch, multiple patches can be duplicated on one block. At this time, the mapped patches are It composes a candidate list, and an index indicating which patch data exists in the corresponding block), a local patch index (an index indicating one of all patches existing in the frame).
  • Table 1 is a pseudo code that shows the block and patch match process using candidate list and local patch index.
  • the maximum number of candidate lists can be defined by the user.
  • FIG 12 illustrates an example of push-pull background filling according to embodiments.
  • Image padding and group dilation (40006, 40007, 40008)
  • the image fader according to the embodiments may fill a space outside the patch area with meaningless additional data based on a push-pull background filling method.
  • Image padding (40006, 40007) is a process of filling a space other than the patch area with meaningless data for the purpose of improving compression efficiency.
  • a method of filling an empty space by copying pixel values of a column or row corresponding to the boundary side inside the patch may be used.
  • a push-pull background filling method may be used in which an unpadded image is gradually reduced in resolution and then an empty space is filled with pixel values from a low resolution image in a process of increasing the resolution again.
  • Group dilation (40008) is a method of filling the empty space of a geometry and texture image consisting of two layers d0/d1 and t0/t1. This is the process of filling with the average value of the values for the same location of.
  • FIG. 13 shows an example of a traversal order possible for a block having a size of 4*4 according to embodiments.
  • the accupancy map compressor is a process of compressing the previously generated occupancy map, and there are two methods: video compression for lossy compression and entropy compression for lossless compression. Video compression is described below.
  • the entropy compression process can be performed as follows.
  • the entropy compression unit 40012 may code (encode) a block based on a traversal order method as shown in FIG. 14.
  • the best traversal order with the smallest number of runs is selected and the index is encoded.
  • FIG. 14 is a case in which the third traversal order of FIG. 13 is selected. In this case, since the number of runs can be minimized to 2, this may be selected as the best traversal order.
  • Video compression (40009, 40010, 40011)
  • the video compression units 40009, 40010, and 40011 encode sequences such as geometry images, texture images, and occupancy map images generated by the above-described process using 2D video codec such as HEVC and VVC. .
  • FIG. 15 shows an example of a 2D video/image encoder according to embodiments, and is also referred to as an encoding device.
  • FIG. 15 is an embodiment to which the above-described video compression units 40009, 40010, and 40011 are applied, and shows a schematic block diagram of a 2D video/image encoder 15000 in which encoding of a video/video signal is performed.
  • the 2D video/image encoder 15000 may be included in the point cloud video encoder 10002 described above, or may be composed of internal/external components.
  • Each component of Fig. 15 may correspond to software, hardware, a processor, and/or a combination thereof.
  • the input image may be one of the above-described geometry image, texture image (attribute(s) image), and occupancy map image.
  • the image input to the 2D video/image encoder 15000 is a padded geometry image, and a bitstream output from the 2D video/image encoder 15000 Is a bitstream of compressed geometry image.
  • the image input to the 2D video/image encoder 15000 is a padded texture image, and a bitstream output from the 2D video/image encoder 15000 Is a bitstream of compressed texture image.
  • the image input to the 2D video/image encoder 15000 is an occupancy map image
  • a bitstream output from the 2D video/image encoder 15000 Is the bitstream of the compressed occupancy map image.
  • the inter prediction unit 15090 and the intra prediction unit 15100 may be collectively referred to as a prediction unit. That is, the prediction unit may include an inter prediction unit 15090 and an intra prediction unit 15100.
  • the transform unit 15030, the quantization unit 15040, the inverse quantization unit 15050, and the inverse transform unit 15060 may be combined to be referred to as a residual processing unit.
  • the residual processing unit may further include a subtraction unit 15020.
  • the inter prediction unit 15090 may be configured by one hardware component (eg, an encoder or a processor) according to an embodiment.
  • the memory 15080 may include a decoded picture buffer (DPB), and may be configured by a digital storage medium.
  • DPB decoded picture buffer
  • the image segmentation unit 15010 may divide an input image (or picture, frame) input to the encoding apparatus 15000 into one or more processing units.
  • the processing unit may be referred to as a coding unit (CU).
  • the coding unit may be recursively partitioned from a coding tree unit (CTU) or a largest coding unit (LCU) according to a quad-tree binary-tree (QTBT) structure.
  • CTU coding tree unit
  • LCU largest coding unit
  • QTBT quad-tree binary-tree
  • one coding unit may be divided into a plurality of coding units of a deeper depth based on a quad tree structure and/or a binary tree structure.
  • a quad tree structure may be applied first and a binary tree structure may be applied later.
  • the binary tree structure may be applied first.
  • the coding procedure according to the present specification may be performed based on the final coding unit that is no longer divided. In this case, based on the coding efficiency according to the image characteristics, the maximum coding unit can be directly used as the final coding unit, or if necessary, the coding unit is recursively divided into coding units of lower depth to be optimal. A coding unit of the size of may be used as the final coding unit.
  • the coding procedure may include a procedure such as prediction, transformation, and restoration described later.
  • the processing unit may further include a prediction unit (PU) or a transform unit (TU).
  • the prediction unit and the transform unit may be divided or partitioned from the above-described final coding unit, respectively.
  • the prediction unit may be a unit of sample prediction
  • the transform unit may be a unit for inducing a transform coefficient and/or a unit for inducing a residual signal from the transform coefficient.
  • a unit may be used interchangeably with terms such as a block or an area or a module, depending on the case.
  • the MxN block may represent a set of samples or transform coefficients consisting of M columns and N rows.
  • a sample may represent a pixel or a value of a pixel, may represent only a pixel/pixel value of a luminance component, or may represent only a pixel/pixel value of a saturation component.
  • a sample may be used as a term corresponding to one picture (or image) as a pixel or pel.
  • the subtraction unit 15020 of the encoding apparatus 15000 is a prediction signal (predicted block, prediction sample array) output from the inter prediction unit 15090 or the intra prediction unit 15100 from the input image signal (original block, original sample array). ) May be subtracted to generate a residual signal (residual signal, residual block, residual sample array), and the generated residual signal is transmitted to the converter 15030.
  • the prediction unit may perform prediction on a block to be processed (hereinafter, referred to as a current block) and generate a predicted block including prediction samples for the current block.
  • the prediction unit may determine whether intra prediction or inter prediction is applied in units of the current block or CU.
  • the prediction unit may generate various information related to prediction, such as prediction mode information, as described later in the description of each prediction mode, and transmit it to the entropy encoding unit 15110.
  • the information on prediction may be encoded by the entropy encoding unit 15110 and output in the form of a bitstream.
  • the intra prediction unit 15100 of the prediction unit may predict the current block by referring to samples in the current picture.
  • the referenced samples may be located in the vicinity of the current block or may be located away from each other according to the prediction mode.
  • prediction modes may include a plurality of non-directional modes and a plurality of directional modes.
  • the non-directional mode may include, for example, a DC mode and a planar mode (Planar mode).
  • the directional mode may include, for example, 33 directional prediction modes or 65 directional prediction modes according to a detailed degree of the prediction direction. However, this is an example, and more or less directional prediction modes may be used depending on the setting.
  • the intra prediction unit 15100 may determine a prediction mode applied to the current block by using the prediction mode applied to the neighboring block.
  • the inter prediction unit 15090 of the prediction unit may derive a predicted block for the current block based on a reference block (reference sample array) specified by a motion vector on the reference picture.
  • motion information may be predicted in units of blocks, subblocks, or samples based on correlation between motion information between neighboring blocks and the current block.
  • the motion information may include a motion vector and a reference picture index.
  • the motion information may further include inter prediction direction (L0 prediction, L1 prediction, Bi prediction, etc.) information.
  • the neighboring block may include a spatial neighboring block existing in the current picture and a temporal neighboring block existing in the reference picture.
  • the reference picture including the reference block and the reference picture including the temporal neighboring block may be the same or different.
  • the temporal neighboring block may be called a collocated reference block, a co-located CU (colCU), or the like, and a reference picture including a temporal neighboring block may be referred to as a collocated picture (colPic).
  • the inter prediction unit 15090 constructs a motion information candidate list based on neighboring blocks, and generates information indicating which candidate is used to derive a motion vector and/or a reference picture index of the current block. can do. Inter prediction may be performed based on various prediction modes.
  • the inter prediction unit 15090 may use motion information of a neighboring block as motion information of a current block.
  • a residual signal may not be transmitted.
  • MVP motion vector prediction
  • the motion vector of the current block is calculated by using the motion vector of the neighboring block as a motion vector predictor and signaling a motion vector difference. I can instruct.
  • the prediction signal generated by the inter prediction unit 15090 or the intra prediction unit 15100 may be used to generate a reconstructed signal or may be used to generate a residual signal.
  • the transform unit 15030 may generate transform coefficients by applying a transform technique to the residual signal.
  • the transformation technique uses at least one of DCT (Discrete Cosine Transform), DST (Discrete Sine Transform), KLT (Karhunen-Loeve Transform), GBT (Graph-Based Transform), or CNT (Conditionally Non-linear Transform).
  • DCT Discrete Cosine Transform
  • DST Discrete Sine Transform
  • KLT Kerhunen-Loeve Transform
  • GBT Graph-Based Transform
  • CNT Supplementally Non-linear Transform
  • Can include GBT refers to the transformation obtained from this graph when the relationship information between pixels is expressed in a graph.
  • CNT refers to a transformation obtained based on generating a prediction signal using all previously reconstructed pixels.
  • the conversion process may be applied to a pixel block having the same size of a square, or may be applied to a block having a variable size other than a square.
  • the quantization unit 15040 quantizes the transform coefficients and transmits it to the entropy encoding unit 15110, and the entropy encoding unit 15110 encodes the quantized signal (information on quantized transform coefficients) and outputs it as a bitstream. have. Information on the quantized transform coefficients may be called residual information.
  • the quantization unit 15040 may rearrange the quantized transform coefficients in a block form into a one-dimensional vector form based on a coefficient scan order, and quantized transform coefficients based on the quantized transform coefficients in a one-dimensional vector form. You can also create information about them.
  • the entropy encoding unit 15110 may perform various encoding methods such as exponential Golomb, context-adaptive variable length coding (CAVLC), and context-adaptive binary arithmetic coding (CABAC).
  • the entropy encoding unit 15110 may encode information necessary for video/image restoration (eg, values of syntax elements) together or separately, in addition to the quantized transform coefficients.
  • the encoded information (eg, encoded video/video information) may be transmitted or stored in a bitstream format in units of network abstraction layer (NAL) units.
  • NAL network abstraction layer
  • the bitstream may be transmitted over a network or may be stored in a digital storage medium.
  • the network may include a broadcasting network and/or a communication network
  • the digital storage medium may include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, and SSD.
  • a transmission unit (not shown) for transmitting the signal output from the entropy encoding unit 15110 and/or a storage unit (not shown) for storing may be configured as an inner/external element of the encoding device 15000, or the transmission unit It may be included in the entropy encoding unit 15110.
  • the quantized transform coefficients output from the quantization unit 15040 may be used to generate a prediction signal.
  • a residual signal residual block or residual samples
  • the addition unit 15200 adds the reconstructed residual signal to the prediction signal output from the inter prediction unit 15090 or the intra prediction unit 15100 to obtain a reconstructed signal (reconstructed picture, reconstructed block, reconstructed sample array). Generate.
  • the predicted block may be used as a reconstructed block.
  • the addition unit 15200 may be referred to as a restoration unit or a restoration block generation unit.
  • the generated reconstructed signal may be used for intra prediction of the next processing target block in the current picture, and may be used for inter prediction of the next picture through filtering as described later.
  • the filtering unit 15070 may apply filtering to the reconstructed signal output from the addition unit 15200 to improve subjective/objective image quality.
  • the filtering unit 15070 may apply various filtering methods to the reconstructed picture to generate a modified reconstructed picture, and store the modified reconstructed picture in the memory 15080, specifically DPB of the memory 15080. Can be saved.
  • Various filtering methods may include, for example, deblocking filtering, sample adaptive offset, adaptive loop filter, bilateral filter, and the like.
  • the filtering unit 15070 may generate a variety of filtering information and transmit it to the entropy encoding unit 15110 as described later in the description of each filtering method. Filtering information may be encoded by the entropy encoding unit 15110 and output in a bitstream form.
  • the modified reconstructed picture stored in the memory 15080 may be used as a reference picture in the inter prediction unit 15090.
  • the encoding device may avoid prediction mismatch between the encoding device 15000 and the decoding device, and may improve encoding efficiency.
  • the DPB of the memory 15080 may store the modified reconstructed picture to be used as a reference picture in the inter prediction unit 15090.
  • the memory 15080 may store motion information of a block from which motion information in a current picture is derived (or encoded) and/or motion information of blocks in a picture that have already been reconstructed.
  • the stored motion information may be transmitted to the inter prediction unit 15090 to be used as motion information of spatial neighboring blocks or motion information of temporal neighboring blocks.
  • the memory 15080 may store reconstructed samples of reconstructed blocks in the current picture, and may be transmitted to the intra prediction unit 15100.
  • prediction, transformation, and quantization procedures may be omitted.
  • prediction, transformation, and quantization procedures may be omitted, and the values of the original samples may be encoded as they are and output as a bitstream.
  • V-PCC decoding process shows an example of a V-PCC decoding process according to embodiments.
  • V-PCC decoding process or the V-PCC decoder may follow the reverse process of the V-PCC encoding process (or encoder) of FIG. 4.
  • Each component of FIG. 16 may correspond to software, hardware, a processor, and/or a combination thereof.
  • the demultiplexer (16000) demultiplexes the compressed bitstream to output a compressed texture image, a compressed geometry image, a compressed accupancy map image, and compressed additional patch information.
  • the video decompression (video decompression units, 16001, 16002) decompresses the compressed texture image and the compressed geometry image, respectively.
  • the accupancy map decompression (or accupancy map decompression unit, 16003) decompresses the compressed accupancy map image.
  • An auxiliary patch information decompression (or additional patch information decompression unit, 16004) decompresses the compressed additional patch information.
  • the geometry reconstruction reconstructs (reconstructs) geometry information based on the decompressed geometry image, the decompressed accupancy map, and/or the decompressed additional patch information. . For example, it is possible to reconstruct the geometry changed during the encoding process.
  • Smoothing may apply smoothing to the reconstructed geometry. For example, smoothing filtering may be applied.
  • a texture reconstruction reconstructs a texture from a decompressed texture image and/or a smoothed geometry.
  • Color smoothing (color smoothing unit, 16008) smoothes color values from the reconstructed texture. For example, smoothing peeling may be applied.
  • FIG. 16 shows a V-PCC decoding process for reconstructing a point cloud by decompressing (or decoding) the compressed occupancy map, geometry image, texture image, and auxiliary path information.
  • Each of the units described in FIG. 16 may operate as at least one of a processor, software, and hardware. Detailed operations of the units of FIG. 16 according to embodiments are as follows.
  • This is a process of decoding a bitstream of a compressed geometry image, a bitstream of a compressed texture image, and/or a bitstream of a compressed occupancy map image by performing the reverse process of video compression.
  • FIG. 17 shows an example of a 2D Video/Image Decoder according to embodiments, and is also referred to as a decoding device.
  • the 2D video/image decoder may follow the reverse process of the 2D video/image encoder of FIG. 15.
  • the 2D video/image decoder of FIG. 17 is an embodiment of the video decompression units (16001, 16002) of FIG. 16, and is a schematic of a 2D video/image decoder 17000 in which decoding of a video/image signal is performed. Show the block diagram.
  • the 2D video/image decoder 17000 may be included in the point cloud video decoder 10008 described above, or may be composed of internal/external components.
  • the input bitstream may be one of a geometry image bitstream, a texture image (attribute(s) image) bitstream, and an occupancy map image bitstream.
  • the bitstream input to the 2D video/image decoder is a bitstream of a compressed texture image, and restoration output from the 2D video/image decoder The image is a decompressed texture image.
  • the bitstream input to the 2D video/image decoder is a bitstream of the compressed geometry image, and restoration output from the 2D video/image decoder The image is a decompressed geometry image.
  • the 2D video/image decoder of FIG. 17 may perform decompression by receiving a bitstream of the compressed accupancy map image.
  • the inter prediction unit 17070 and the intra prediction unit 17080 may be collectively referred to as a prediction unit. That is, the prediction unit may include an inter prediction unit 17070 and an intra prediction unit 17080.
  • the inverse quantization unit 17020 and the inverse transform unit 17030 may be collectively referred to as a residual processing unit. That is, the residual processing unit may include an inverse quantization unit 17020 and an inverse transform unit 1702.
  • the entropy decoding unit 17010, inverse quantization unit 17020, inverse transform unit 17030, addition unit 17040, filtering unit 17050, inter prediction unit 17070, and intra prediction unit 17080 of FIG. 17 are implemented. It may be configured by one hardware component (eg, a decoder or a processor) according to an example. Further, the memory 17060 may include a decoded picture buffer (DPB), and may be configured by a digital storage medium.
  • DPB decoded picture buffer
  • the decoding apparatus 17000 may restore an image in response to a process in which the video/image information is processed by the encoding device of FIG. 15.
  • the decoding device 17000 may perform decoding using a processing unit applied in the encoding device.
  • the processing unit of decoding may be, for example, a coding unit, and the coding unit may be divided from a coding tree unit or a maximum coding unit along a quad tree structure and/or a binary tree structure.
  • the reconstructed image signal decoded and output through the decoding device 17000 may be reproduced through the playback device.
  • the decoding device 17000 may receive a signal output from the encoding device in the form of a bitstream, and the received signal may be decoded through the entropy decoding unit 17010.
  • the entropy decoding unit 17010 may parse the bitstream to derive information (eg, video/video information) necessary for image restoration (or picture restoration).
  • the entropy decoding unit 17010 decodes information in the bitstream based on a coding method such as exponential Golomb encoding, CAVLC, or CABAC, and a value of a syntax element required for image restoration and a quantized value of a transform coefficient for a residual. Can be printed.
  • the CABAC entropy decoding method receives a bin corresponding to each syntax element in a bitstream, and includes information on a syntax element to be decoded and information on a neighboring and decoding target block or information on a symbol/bin decoded in a previous step.
  • a context model is determined using the context model, and a symbol corresponding to the value of each syntax element can be generated by performing arithmetic decoding of the bin by predicting the probability of occurrence of a bin according to the determined context model. have.
  • the CABAC entropy decoding method may update the context model using information of the decoded symbol/bin for the context model of the next symbol/bin after the context model is determined.
  • the entropy decoding unit 17010 Among the information decoded by the entropy decoding unit 17010, information about prediction is provided to the prediction unit (inter prediction unit 17070 and intra prediction unit 17080), and the register on which entropy decoding is performed by the entropy decoding unit 17010 The dual value, that is, quantized transform coefficients and related parameter information, may be input to the inverse quantization unit 17020. In addition, information about filtering among information decoded by the entropy decoding unit 17010 may be provided to the filtering unit 17050. Meanwhile, a receiving unit (not shown) for receiving a signal output from the encoding device may be further configured as an inner/outer element of the decoding device 17000, or the receiving unit may be a component of the entropy decoding unit 17010.
  • the inverse quantization unit 17020 may inverse quantize the quantized transform coefficients and output transform coefficients.
  • the inverse quantization unit 17020 may rearrange the quantized transform coefficients in a two-dimensional block shape. In this case, reordering may be performed based on the coefficient scan order performed by the encoding device.
  • the inverse quantization unit 17020 may perform inverse quantization on quantized transform coefficients by using a quantization parameter (eg, quantization step size information) and obtain transform coefficients.
  • a quantization parameter eg, quantization step size information
  • the inverse transform unit 17030 inversely transforms the transform coefficients to obtain a residual signal (residual block, residual sample array).
  • the prediction unit may perform prediction on the current block and generate a predicted block including prediction samples for the current block.
  • the prediction unit may determine whether intra prediction or inter prediction is applied to the current block based on information on prediction output from the entropy decoding unit 17010, and may determine a specific intra/inter prediction mode.
  • the intra prediction unit 17080 of the prediction unit may predict the current block by referring to samples in the current picture.
  • the referenced samples may be located in the vicinity of the current block or may be located away from each other according to the prediction mode.
  • prediction modes may include a plurality of non-directional modes and a plurality of directional modes.
  • the intra prediction unit 17080 may determine a prediction mode applied to the current block by using the prediction mode applied to the neighboring block.
  • the inter prediction unit 17070 of the prediction unit may derive a predicted block for the current block based on a reference block (reference sample array) specified by a motion vector on a reference picture.
  • motion information may be predicted in units of blocks, subblocks, or samples based on correlation between motion information between neighboring blocks and the current block.
  • the motion information may include a motion vector and a reference picture index.
  • the motion information may further include inter prediction direction (L0 prediction, L1 prediction, Bi prediction, etc.) information.
  • the neighboring block may include a spatial neighboring block existing in the current picture and a temporal neighboring block existing in the reference picture.
  • the inter prediction unit 17070 may construct a motion information candidate list based on neighboring blocks, and derive a motion vector and/or a reference picture index of the current block based on the received candidate selection information.
  • Inter prediction may be performed based on various prediction modes, and information on prediction may include information indicating a mode of inter prediction for a current block.
  • the addition unit 17040 adds the residual signal obtained from the inverse transform unit 17030 to the prediction signal (predicted block, prediction sample array) output from the inter prediction unit 17070 or the intra prediction unit 17080 to obtain a reconstructed signal. You can create (restored picture, reconstructed block, reconstructed sample array). When there is no residual for a block to be processed, such as when the skip mode is applied, the predicted block may be used as a reconstructed block.
  • the addition unit 17040 may be referred to as a restoration unit or a restoration block generation unit.
  • the generated reconstructed signal may be used for intra prediction of the next processing target block in the current picture, and may be used for inter prediction of the next picture through filtering as described later.
  • the filtering unit 17050 may apply filtering to the reconstructed signal output from the addition unit 17040 to improve subjective/objective image quality.
  • the filtering unit 17050 may generate a modified reconstructed picture by applying various filtering methods to the reconstructed picture, and store the modified reconstructed picture in the memory 17060, specifically DPB of the memory 17060. Can be transmitted.
  • Various filtering methods may include, for example, deblocking filtering, sample adaptive offset, adaptive loop filter, bilateral filter, and the like.
  • the reconstructed (modified) picture stored in the DPB of the memory 17060 may be used as a reference picture in the inter prediction unit 17070.
  • the memory 17060 may store motion information of a block from which motion information in a current picture is derived (or decoded) and/or motion information of blocks in a picture that have already been reconstructed.
  • the stored motion information may be transmitted to the inter prediction unit 17070 to be used as motion information of spatial neighboring blocks or motion information of temporal neighboring blocks.
  • the memory 17060 may store reconstructed samples of reconstructed blocks in the current picture, and may be transmitted to the intra prediction unit 17080.
  • the embodiments described in the filtering unit 15070, the inter prediction unit 15090, and the intra prediction unit 15100 of the encoding apparatus 15000 of FIG. 15 are respectively a filtering unit 17050 of the decoding apparatus 17000.
  • the inter prediction unit 17070 and the intra prediction unit 17080 may be the same or applied to correspond to each other.
  • prediction, inverse transformation, and inverse quantization procedures may be omitted.
  • prediction, inverse transform, and inverse quantization procedures may be omitted, and the value of the decoded sample may be used as a sample of the reconstructed image.
  • This is an inverse process of occupancy map compression described above, and is a process for reconstructing an occupancy map by decoding a compressed occupancy map bitstream.
  • This is a reverse process of the auxiliary patch information compression described above, and is a process for restoring auxiliary patch information by decoding the compressed auxiliary patch information bitstream.
  • a patch is extracted from a geometry image using the restored occupancy map and 2D location/size information of the patch included in the auxiliary patch information, and the mapping information of the block and patch.
  • the point cloud is restored in the 3D space by using the extracted geometry image of the patch and the 3D location information of the patch included in the auxiliary patch information.
  • the geometry value corresponding to an arbitrary point (u, v) in one patch is called g(u, v), and the normal axis, tangent axis, and bitangent axis coordinate values of the patch's three-dimensional space are (d0 , s0, r0), d(u, v), s(u, v), r, which are coordinate values of the normal axis, tangent axis, and bitangent axis of a position in 3D space mapped to a point (u, v).
  • (u, v) can be expressed as follows.
  • color values corresponding to the texture image pixels at the same location as in the geometry image in 2D space are converted to the point cloud corresponding to the same location in 3D space. It can be done by giving it to a point.
  • Color smoothing can be performed in the following process.
  • the distribution of color values is examined to determine whether or not smoothing is performed. For example, when the entropy of the luminance value is less than or equal to the threshold local entry (when there are many similar luminance values), smoothing may be performed by determining as a non-edge part.
  • smoothing method a method of changing the color value of the corresponding point with the average value of the adjacent points can be used.
  • FIG. 18 shows an example of a flowchart of an operation of a transmission apparatus for compressing and transmitting V-PCC-based point cloud data according to embodiments.
  • the transmission device may correspond to the transmission device of FIG. 1, the encoding process of FIG. 4, and the 2D video/image encoder of FIG. 15, or perform some/all operations thereof.
  • Each component of the transmission device may correspond to software, hardware, a processor, and/or a combination thereof.
  • the operation process of the transmitter for compressing and transmitting point cloud data using V-PCC may be as shown in the figure.
  • the point cloud data transmission apparatus may be referred to as a transmission apparatus, a transmission system, and the like.
  • the patch generator 18000 receives point cloud data and generates a patch for 2D image mapping of a point cloud. Patch information and/or additional patch information is generated as a result of patch creation, and the generated patch information and/or additional patch information is generated by a geometry image, a texture image, and smoothing or smoothing. It can be used in the geometry restoration process for
  • the patch packing unit 18001 performs a patch packing process of mapping patches generated by the patch generating unit 18000 into a 2D image. For example, one or more patches may be packed.
  • An occupancy map is generated as a result of the patch packing, and the accupancy map can be used in a geometry image generation, geometry image padding, texture image padding, and/or a geometry restoration process for smoothing.
  • the geometry image generation unit 18002 generates a geometry image using point cloud data, patch information (or additional patch information), and/or an accufancy map.
  • the generated geometry image is preprocessed by the encoding preprocessor 18003 and then encoded as a bitstream by the video encoding unit 18006.
  • the encoding preprocessor 18003 may include an image padding procedure. In other words, the generated geometry image and some spaces of the generated texture image may be padded with meaningless data.
  • the encoding preprocessor 18003 may further include a group dilation process for the generated texture image or the texture image on which image padding has been performed.
  • the geometry reconstruction unit 18010 reconstructs a 3D geometry image using a geometry bitstream, additional patch information, and/or an accupancy map encoded by the video encoding unit 18006.
  • the smoothing unit 18009 smoothes the 3D geometry image reconstructed and output by the geometry restoration unit 18010 based on the additional patch information, and outputs the smoothing to the texture image generation unit 18004.
  • the texture image generator 18004 may generate a texture image by using the smoothed 3D geometry, point cloud data, patch (or packed patch), patch information (or additional patch information), and/or an accufancy map. .
  • the generated texture image may be preprocessed by the encoding preprocessor 18003 and then encoded into one video bitstream by the video encoding unit 18006.
  • the metadata encoding unit 18005 may encode the additional patch information into one metadata bitstream.
  • the video encoding unit 18006 may encode a geometry image and a texture image output from the encoding preprocessor 18003 into respective video bitstreams, and encode the accupancy map into one video bitstream. According to an embodiment, the video encoding unit 18006 encodes each input image by applying the 2D video/image encoder of FIG. 15 respectively.
  • the multiplexer 18007 includes a video bitstream of a geometry output from the video encoding unit 18006, a video bitstream of a texture image, a video bitstream of an accufancy map, and metadata output from the metadata encoding unit 18005. (Including patch information)
  • the bitstream is multiplexed into one bitstream.
  • the transmitter 18008 transmits the bitstream output from the multiplexer 18007 to the receiver.
  • a file/segment encapsulation unit is further provided between the multiplexer 18007 and the transmission unit 18008, and the bitstream output from the multiplexer 18007 is encapsulated in the form of a file and/or segment, and the transmission unit 18008 It can also be output as
  • the patch generation unit 18000 of FIG. 18, the patch packing unit 18001, the geometry image generation unit 18002, the texture image generation unit 18004, the metadata encoding unit 18005, and the smoothing unit 18009 are shown in FIG. It may correspond to the patch generation unit 40000, the patch packing unit 40001, the geometry image generation unit 40002, the texture image generation unit 40003, the additional patch information compression unit 40005, and the smoothing unit 40004, respectively.
  • the encoding preprocessor 18003 of FIG. 18 may include the image padding units 40006 and 40007 and the group delay unit 40008 of FIG. 4, and the video encoding unit 18006 of FIG. Parts 40009, 40010, 40011 and/or an entropy compression part 40012 may be included. Therefore, for portions not described in FIG.
  • FIGS. 4 to 15 the description of FIGS. 4 to 15 will be referred to.
  • the above-described blocks may be omitted or may be replaced by blocks having similar or identical functions.
  • each of the blocks shown in FIG. 18 may operate as at least one of a processor, software, and hardware.
  • FIG. 19 shows an example of a flowchart of an operation of a receiving apparatus for receiving and restoring V-PCC-based point cloud data according to embodiments.
  • the reception device may correspond to the reception device of FIG. 1, the decoding process of FIG. 16, and the 2D video/image encoder of FIG. 17, or perform some/all operations thereof.
  • Each component of the receiving device may correspond to software, hardware, a processor, and/or a combination thereof.
  • the operation process of the receiving end for receiving and restoring point cloud data using V-PCC may be as shown in the figure.
  • the operation of the V-PCC receiver may follow the reverse process of the operation of the V-PCC transmitter of FIG. 18.
  • the point cloud data receiving device may be referred to as a receiving device, a receiving system, or the like.
  • the receiver receives a bitstream of a point cloud (ie, compressed bitstream), and the demultiplexer 19000 receives a bitstream of a texture image, a bitstream of a geometry image, and a bitstream of an accufancy map image from the received point cloud bitstream.
  • the bitstream of metadata ie, additional patch information
  • the bitstream of the demultiplexed texture image, the bitstream of the geometry image, and the bitstream of the accupancy map image are output to the video decoding unit 19001, and the bitstream of the metadata is output to the metadata decoding unit 19002.
  • the file/segment decapsulation unit is provided between the receiving unit and the demultiplexing unit 19000 of the receiving device of FIG. 19.
  • the transmitting device encapsulates and transmits the point cloud bitstream in the form of a file and/or segment
  • the receiving device receives and decapsulates the file and/or segment including the point cloud bitstream.
  • the video decoding unit 19001 decodes a bitstream of a geometry image, a bitstream of a texture image, and a bitstream of an accupancy map image into a geometry image, a texture image, and an accupancy map image, respectively.
  • the video decoding unit 19001 performs decoding by applying the 2D video/image decoder of FIG. 17 to each input bitstream.
  • the metadata decoding unit 19002 decodes the bitstream of metadata into additional patch information, and outputs the decoding to the geometry reconstructor 19003.
  • the geometry reconstruction unit 19003 reconstructs (reconstructs) the 3D geometry based on the geometry image, the accupancy map, and/or additional patch information output from the video decoding unit 19001 and the metadata decoding unit 19002.
  • the smoothing unit 19004 applies smoothing to the 3D geometry reconstructed by the geometry restoration unit 19003.
  • the texture restoration unit 19005 restores a texture using a texture image output from the video decoding unit 19001 and/or a smoothed 3D geometry. That is, the texture restoration unit 19005 restores the color point cloud image/picture by applying a color value to the smoothed 3D geometry using the texture image. Thereafter, in order to improve objective/subjective visual quality, a color smoothing process may be additionally performed on the color point cloud image/picture in the color smoothing unit 1993. The modified point cloud image/picture derived through this is displayed to the user after going through a rendering process of the point cloud renderer 19007. Meanwhile, the color smoothing process may be omitted in some cases.
  • each of the blocks shown in FIG. 19 may operate as at least one of a processor, software, and hardware.
  • FIG 20 shows an example of an architecture for V-PCC-based point cloud data storage and streaming according to embodiments.
  • Some/all of the system of FIG. 20 is the transmitting and receiving device of FIG. 1, the encoding process of FIG. 4, the 2D video/image encoder of FIG. 15, the decoding process of FIG. 16, the transmitting device of FIG. It may include some/all such as.
  • Each component in the drawing may correspond to software, hardware, a processor, and a combination thereof.
  • FIG. 20 is a diagram showing an overall architecture for storing or streaming point cloud data compressed based on Video-based Point Cloud Compression (V-PCC).
  • the process of storing and streaming point cloud data may include an acquisition process, an encoding process, a transmission process, a decoding process, a rendering process and/or a feedback process.
  • Embodiments propose a method of effectively providing point cloud media/content/data.
  • the point cloud acquisition unit 20000 first acquires a point cloud video in order to effectively provide point cloud media/content/data.
  • point cloud data may be acquired through the process of capturing, synthesizing, or creating a point cloud through one or more cameras.
  • a point cloud video including the 3D position (x, y, z position values, etc.) of each point (hereinafter referred to as geometry) and the attributes of each point (color, reflectance, transparency, etc.) can be obtained.
  • the acquired point cloud video may be generated as a PLY (Polygon File format or the Stanford Triangle format) file including this.
  • PLY Polygon File format or the Stanford Triangle format
  • point cloud related metadata eg, metadata related to capture, etc.
  • the captured Point Cloud video may need post-processing to improve the quality of the content.
  • the maximum/minimum depth value can be adjusted within the range provided by the camera equipment, but point data of the unwanted area may be included even after that, so the unwanted area (eg, background) is removed or the connected space is recognized.
  • Post-treatment of filling the spatial hole can be performed.
  • the Point Cloud extracted from the cameras sharing the spatial coordinate system can be integrated into one content through the conversion process to the global coordinate system for each point based on the position coordinates of each camera acquired through the calibration process. Through this, it is possible to acquire a Point Cloud video with a high density of points.
  • the point cloud pre-processing unit (20001) may generate a point cloud video as one or more pictures/frames.
  • a picture/frame may generally mean a unit representing one image in a specific time period.
  • the point cloud preprocessor (20001) divides the points constituting the point cloud video into one or more patches and maps them to the 2D plane, indicating whether data exists at the corresponding position of the 2D plane as a binary value of 0 or 1. It is possible to create an occupancy map picture/frame that is a binary map.
  • a patch is a set of points constituting a point cloud, and points belonging to the same patch are adjacent to each other in 3D space, and are a set of points that are mapped in the same direction among the six-sided bounding box planes during the mapping process to a 2D image.
  • the point cloud preprocessor 20001 may generate a geometry picture/frame, which is a picture/frame in the form of a depth map that expresses the location information (geometry) of each point of the Point Cloud video in a patch unit.
  • the point cloud preprocessor 20001 may generate a texture picture/frame, which is a picture/frame expressing color information of each point of a point cloud video in a patch unit.
  • Metadata necessary to reconstruct the point cloud from individual patches can be generated, and this metadata is information about the patch, such as the location and size of each patch in 2D/3D space (this It may include). These pictures/frames are sequentially generated in chronological order to form a video stream or a metadata stream.
  • the Point Cloud video encoder 20002 may encode one or more video streams associated with Point Cloud video.
  • One video may include a plurality of frames, and one frame may correspond to a still image/picture.
  • a Point Cloud video may include a Point Cloud image/frame/picture, and the Point Cloud video may be used interchangeably with a Point Cloud image/frame/picture.
  • the Point Cloud video encoder 20002 may perform a Video-based Point Cloud Compression (V-PCC) procedure.
  • the Point Cloud video encoder 20002 may perform a series of procedures such as prediction, transform, quantization, and entropy coding for compression and coding efficiency.
  • the encoded data (encoded video/video information) may be output in the form of a bitstream.
  • the Point Cloud video encoder 20002 is used to describe the Point Cloud video to a geometry video, an attribute video, an occupancy map video, and metadata, such as a patch. It can be encoded by dividing it into information about.
  • the geometry video may include a geometry image
  • the attribute video may include an attribute image
  • the occupancy map video may include an accupancy map image.
  • Patch data which is additional information, may include patch related information.
  • the attribute video/image may include a texture video/image.
  • the Point Cloud image encoder 20003 may encode one or more images associated with a Point Cloud video.
  • the Point Cloud image encoder 20003 may perform a Video-based Point Cloud Compression (V-PCC) procedure.
  • the Point Cloud image encoder 20003 may perform a series of procedures such as prediction, transformation, quantization, and entropy coding for compression and coding efficiency.
  • the encoded image may be output in the form of a bitstream.
  • the Point Cloud Image Encoder 20003 uses the Point Cloud image as a geometry image, an attribute image, an occupancy map image, and metadata, for example, to a patch. It can be encoded by dividing it into information about.
  • the point cloud video encoder 20002, the point cloud image encoder 20003, the point cloud video decoder 20006, and the point cloud image decoder 20008 are performed by one encoder/decoder as described above. May be performed, and may be performed in a separate path as shown in the figure.
  • the encapsulation unit may encapsulate the encoded point cloud data and/or point cloud related metadata in the form of a file or a segment for streaming.
  • the point cloud related metadata may be transmitted from a metadata processing unit (not shown).
  • the metadata processing unit may be included in the point cloud video/image encoders 20002 and 20003, or may be configured as a separate component/module.
  • the encapsulation unit 20004 may encapsulate the video/image/metadata in a file format such as ISOBMFF or process the video/image/metadata in the form of a DASH segment.
  • the encapsulation unit 20004 may include point cloud related metadata in a file format according to an embodiment.
  • Point cloud metadata may be included in boxes of various levels in the ISOBMFF file format, for example, or may be included as data in separate tracks within the file.
  • the encapsulation unit 20004 may encapsulate the point cloud related metadata itself as a file.
  • the transmission processing unit may apply processing for transmission to the encapsulated point cloud data according to the file format.
  • the transmission processing unit may be included in the transmission unit (not shown), or may be configured as a separate component/module.
  • the transmission processing unit can process point cloud data according to any transmission protocol.
  • the processing for transmission may include processing for transmission through a broadcasting network and processing for transmission through a broadband.
  • the transmission processing unit may receive not only the point cloud data, but also the point cloud related metadata from the metadata processing unit, and may apply processing for transmission to this.
  • the transmission unit may transmit a point cloud bitstream or a file/segment including the corresponding bitstream to a reception unit (not shown) of the reception device through a digital storage medium or a network.
  • processing according to any transmission protocol can be performed.
  • Data processed for transmission may be delivered through a broadcasting network and/or a broadband. These data may be delivered to the receiving side in an on-demand manner.
  • Digital storage media may include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, and SSD.
  • the transmission unit may include an element for generating a media file through a predetermined file format, and may include an element for transmission through a broadcast/communication network.
  • the receiver may extract the bitstream and transmit it to the decoding device.
  • the receiver may receive point cloud data transmitted by the point cloud data transmission device according to the present specification. Depending on the transmitted channel, the receiver may receive point cloud data through a broadcasting network or may receive point cloud data through a broadband. Alternatively, point cloud video data can be received through a digital storage medium. The receiver may include a process of decoding the received data and rendering it according to a user's viewport.
  • the reception processing unit may perform processing according to a transmission protocol on the received point cloud video data.
  • the receiving processing unit may be included in the receiving unit, or may be configured as a separate component/module.
  • the reception processing unit may perform the reverse process of the transmission processing unit described above so as to correspond to the transmission processing performed by the transmission side.
  • the reception processing unit may transmit the acquired point cloud video to the decapsulation unit 20005, and the acquired point cloud related metadata may be transmitted to the metadata processing unit (not shown).
  • the decapsulation unit may decapsulate point cloud data in the form of a file transmitted from the reception processing unit.
  • the decapsulation unit 20005 may decapsulate files according to ISOBMFF or the like to obtain a point cloud bitstream or point cloud related metadata (or a separate metadata bitstream).
  • the acquired point cloud bitstream can be delivered to the point cloud video decoder 20006 and the point cloud image decoder 2008, and the acquired point cloud related metadata (or metadata bitstream) can be delivered to the metadata processing unit (not shown). have.
  • the point cloud bitstream may include metadata (metadata bitstream).
  • the metadata processing unit may be included in the point cloud video decoder 20006 or may be configured as a separate component/module.
  • the point cloud related metadata acquired by the decapsulation unit 20005 may be in the form of a box or track in a file format. If necessary, the decapsulation unit 20005 may receive metadata required for decapsulation from the metadata processing unit.
  • the point cloud related metadata may be transmitted to the point cloud video decoder 20006 and/or the point cloud image decoder 20008 and used for the point cloud decoding procedure, or transmitted to the renderer 2001 to be used for the point cloud rendering procedure. have.
  • the point cloud video decoder 20006 receives a bitstream and performs a reverse process corresponding to the operation of the point cloud video encoder 20002 to decode a video/image.
  • the Point Cloud video decoder 20006 may divide and decode the Point Cloud video into a geometry video, an attribute video, an occupancy map video, and auxiliary patch information, as described later.
  • the geometry video may include a geometry image
  • the attribute video may include an attribute image
  • the occupancy map video may include an accupancy map image.
  • the additional information may include auxiliary patch information.
  • the attribute video/image may include a texture video/image.
  • the point cloud image decoder 20008 may receive a bitstream and perform a reverse process corresponding to the operation of the point cloud image encoder 20003.
  • the Point Cloud image decoder 20008 divides the Point Cloud image into a geometry image, an attribute image, an occupancy map image, and metadata, for example, auxiliary patch information. I can.
  • the 3D geometry is reconstructed using the decoded geometry video/image, the accupancy map, and additional patch information, and then the smoothing process can be performed.
  • a color point cloud image/picture may be reconstructed by assigning a color value to the smoothed 3D geometry using a texture video/image.
  • the renderer 20011 may render reconstructed geometry and color point cloud images/pictures.
  • the rendered video/image may be displayed through the display unit. The user can view all or part of the rendered result through a VR/AR display or a general display.
  • the sensing/tracking unit obtains orientation information and/or user viewport information from a user or a receiving side and transmits it to a receiving unit and/or a transmitting unit.
  • Orientation information may indicate information about the position, angle, and movement of the user's head, or may indicate information about the position, angle, and movement of the device that the user is viewing. Based on this information, information on a region currently viewed by the user in the 3D space, that is, viewport information may be calculated.
  • the viewport information may be information on a region currently viewed by the user through a device or an HMD in a 3D space.
  • a device such as a display may extract a viewport area based on orientation information and a vertical or horizontal FOV supported by the device.
  • Orientation or viewport information can be extracted or calculated at the receiving end.
  • the orientation or viewport information analyzed by the receiving side may be transmitted to the transmitting side through a feedback channel.
  • the receiving unit uses the orientation information acquired by the sensing/tracking unit 20007 and/or the viewport information indicating the area currently being viewed by the user, so that only media data of the area indicated by the orientation information and/or the viewport information is efficient. Can be extracted or decoded from a file.
  • the transmission unit efficiently encodes only the media data of a specific area, that is, the area indicated by the orientation information and/or the viewport information, using the orientation information and/or the viewport information obtained by the sensing/tracking unit 20007, or generates a file and Can be transmitted.
  • the renderer 20011 may render decoded Point Cloud data in a 3D space.
  • the rendered video/image may be displayed through the display unit.
  • the user can view all or part of the rendered result through a VR/AR display or a general display.
  • the feedback process may include a process of transferring various feedback information that can be obtained during the rendering/display process to a transmitter or a decoder at a receiver. Interactivity in Point Cloud data consumption can be provided through the feedback process.
  • head orientation information, viewport information indicating an area currently viewed by the user, and the like may be transmitted in the feedback process.
  • the user may interact with those implemented in the VR/AR/MR/autonomous driving environment.In this case, information related to the interaction may be transmitted to the transmitting side or the service provider side in the feedback process. have.
  • the feedback process may not be performed.
  • the above-described feedback information is not only transmitted to the transmitting side, but may be consumed by the receiving side. That is, a decapsulation process, decoding, rendering process, etc. of the receiver may be performed using the above-described feedback information. For example, point cloud data for a region currently viewed by a user may be preferentially decapsulated, decoded, and rendered using orientation information and/or viewport information.
  • FIG. 21 shows an example of a configuration diagram of an apparatus for storing and transmitting point cloud data according to embodiments.
  • FIG. 21 shows a point cloud system according to embodiments, and part/all of the system is a transmission/reception device of FIG. 1, an encoding process of FIG. 4, a 2D video/image encoder of FIG. 15, a decoding process of FIG. 16, and It may include some/all of the transmitting device and/or the receiving device of FIG. 19. In addition, it may be included in or correspond to some/all of the system of FIG. 20.
  • the point cloud data transmission apparatus may be configured as shown in the drawing.
  • Each configuration of the transmission device may be a module/unit/component/hardware/software/processor.
  • Point cloud geometry, attributes, auxiliary data (also referred to as auxiliary information), mesh data, etc. may be configured as separate streams or stored in different tracks in the file. Furthermore, it can be included in a separate segment.
  • the point cloud acquisition unit 21000 acquires a point cloud.
  • point cloud data may be acquired through a process of capturing, synthesizing, or creating a point cloud through one or more cameras.
  • point cloud data including the 3D position (x, y, z position value, etc.) of each point (hereinafter referred to as geometry) and the attributes of each point (color, reflectance, transparency, etc.) It can be obtained, and can be created as a PLY (Polygon File format or the Stanford Triangle format) file including the same.
  • PLY Polygon File format or the Stanford Triangle format
  • point cloud related metadata eg, metadata related to capture, etc.
  • the patch generation unit 21001 generates a patch from point cloud data.
  • the patch generation unit 21001 generates point cloud data or point cloud video as one or more pictures/frames.
  • a picture/frame may generally mean a unit representing one image in a specific time period.
  • Point cloud The points constituting the video are one or more patches (a set of points constituting the point cloud, and points belonging to the same patch are adjacent to each other in the 3D space, and in the process of mapping to a 2D image, one of the six-sided bounding box planes When mapping to a 2D plane by dividing it into a set of points mapped in the same direction), occupancy, a binary map that informs whether or not data exists at the corresponding position of the 2D plane with a value of 0 or 1 Map pictures/frames can be created.
  • a geometry picture/frame which is a picture/frame in the form of a depth map that expresses the location information of each point of the Point Cloud video in units of a patch.
  • a texture picture/frame which is a picture/frame that expresses color information of each point of a point cloud video in a patch unit, can be generated.
  • metadata necessary to reconstruct a point cloud from individual patches can be created, and this metadata can include information on patches such as the location and size of each patch in 2D/3D space.
  • the patch can be used for 2D image mapping.
  • point cloud data can be projected onto each side of a cube.
  • a geometry image, one or more attribute images, an accupancy map, auxiliary data, and/or mesh data may be generated based on the generated patch.
  • the Point Cloud preprocessing unit 20001 includes a patch generation unit 21001, a geometry image generation unit 21002, an attribute image generation unit 21003, an accufancy map generation unit 21004, an auxiliary data generation unit 21005, and a mesh. It is assumed that the data generation unit 21006 is included.
  • the geometry image generation unit 21002 generates a geometry image based on the result of the patch generation. Geometry represents a point in three-dimensional space. Based on the patch, a geometry image is generated using an accufancy map including information related to the 2D image packing of the patch, auxiliary data (or additional information, including patch data) and/or mesh data. The geometry image is related to information such as the depth (e.g., near, far) of the patch generated after patch generation.
  • the attribute image generation unit 21003 generates an attribute image.
  • an attribute may represent a texture.
  • the texture may be a color value matching each point.
  • a plurality of (N) attribute images including a texture may be generated.
  • the plurality of attributes may include a material (information on a material), reflectance, and the like.
  • the attribute may additionally include information in which a color may be changed depending on time and light.
  • the occupancy map generation unit 21004 generates an accupancy map from the patch.
  • the accufancy map includes information indicating whether data exists in a pixel such as a corresponding geometry or attribute image.
  • the Auxiliary Data Generation unit 21005 generates auxiliary data (or additional patch information) including information on a patch. That is, Auxiliary data represents metadata about a patch of a Point Cloud object. For example, it may represent information such as a normal vector for a patch. Specifically, according to embodiments, the auxiliary data may include information necessary to reconstruct the point cloud from the patches (for example, information on the position and size of the patch in 2D/3D space, projection ) Identification information, patch mapping information, etc.).
  • the mesh data generation unit 21006 generates mesh data from the patch.
  • Mesh represents connection information between adjacent points. For example, it can represent triangular data.
  • mesh data according to embodiments refers to connectivity information between points.
  • the point cloud preprocessing unit 20001 or the control unit generates metadata related to patch generation, geometric image generation, attribute image generation, accufancy map generation, auxiliary data generation, and mesh data generation.
  • the point cloud transmission device performs video encoding and/or image encoding in response to the result generated by the point cloud preprocessor 20001.
  • the point cloud transmission device may generate point cloud image data as well as point cloud video data. According to embodiments, there may be a case where the point cloud data includes only video data, only image data and/or both video data and image data.
  • the video encoding unit 21007 performs geometry video compression, attribute video compression, accupancy map video compression, auxiliary data compression, and/or mesh data compression.
  • the video encoding unit 21007 generates video stream(s) including each encoded video data.
  • the geometry video compression encodes the point cloud geometry video data.
  • Attribute video compression encodes the attribute video data of the point cloud.
  • Auxiliary data compression encodes Auxiliary data associated with point cloud video data.
  • Mesh data compression encodes the mesh data of Point Cloud video data. Each operation of the point cloud video encoding unit may be performed in parallel.
  • the image encoding unit 21008 performs geometric image compression, attribute image compression, accupancy map image compression, auxiliary data compression, and/or mesh data compression.
  • the image encoding unit generates image(s) including each encoded image data.
  • geometry image compression encodes point cloud geometry image data.
  • Attribute image compression encodes the attribute image data of a point cloud.
  • Auxiliary data compression encodes Auxiliary data associated with point cloud image data.
  • Mesh data compression encodes mesh data associated with point cloud image data. Each operation of the point cloud image encoding unit may be performed in parallel.
  • the video encoding unit 21007 and/or the image encoding unit 21008 may receive metadata from the Point Cloud preprocessor 20001.
  • the video encoding unit 21007 and/or the image encoding unit 21008 may perform each encoding process based on metadata.
  • the File/Segment Encapsulation (21009) unit encapsulates video stream(s) and/or image(s) in the form of files and/or segments.
  • the file/segment encapsulation unit 21009 performs video track encapsulation, metadata track encapsulation, and/or image encapsulation.
  • Video track encapsulation may encapsulate one or more video streams into one or more tracks.
  • Metadata track encapsulation may encapsulate metadata related to a video stream and/or image in one or more tracks.
  • the metadata includes data related to the content of the point cloud data. For example, it may include initial viewing orientation metadata (Initial Viewing Orientation Metadata).
  • the metadata may be encapsulated in a metadata track, or may be encapsulated together in a video track or an image track.
  • Image encapsulation may encapsulate one or more images into one or more tracks or items.
  • 4 video streams and 2 images when 4 video streams and 2 images are input to the encapsulation unit, 4 video streams and 2 images may be encapsulated in one file.
  • the file/segment encapsulation unit 21009 may receive metadata from the point cloud preprocessor 20001.
  • the file/segment encapsulation unit 21009 may perform encapsulation based on metadata.
  • the file and/or segment generated by the file/segment encapsulation is transmitted by the point cloud transmission device or the transmission unit.
  • segment(s) may be delivered based on a DASH-based protocol.
  • the delivery unit may deliver a point cloud bitstream or a file/segment including the corresponding bitstream to a receiving unit of a receiving device through a digital storage medium or a network.
  • processing according to any transmission protocol can be performed.
  • Data processed for transmission may be delivered through a broadcasting network and/or a broadband. These data may be delivered to the receiving side in an on-demand manner.
  • Digital storage media may include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, and SSD.
  • the delivery unit may include an element for generating a media file through a predetermined file format, and may include an element for transmission through a broadcast/communication network.
  • the delivery unit receives orientation information and/or viewport information from the reception unit.
  • the delivery unit converts the obtained orientation information and/or viewport information (or information selected by the user) into a point cloud preprocessor 20001, a video encoding unit 21007, an image encoding unit 21008, and a file/segment encapsulation unit 21009. ) And/or the point cloud encoding unit.
  • the point cloud encoding unit may encode all point cloud data or the point cloud data indicated by the orientation information and/or the viewport information.
  • the file/segment encapsulation unit may encapsulate all point cloud data or the point cloud data indicated by the orientation information and/or the viewport information.
  • the delivery unit may deliver all point cloud data or the point cloud data indicated by the orientation information and/or the viewport information.
  • the point cloud preprocessor 20001 may perform the above-described operation on all point cloud data or the above-described operation on point cloud data indicated by orientation information and/or viewport information.
  • the video encoding unit 21007 and/or the image encoding unit 21008 may perform the above-described operation on all point cloud data, or perform the above-described operation on point cloud data indicated by orientation information and/or viewport information. have.
  • the file/segment encapsulation unit 21009 may perform the above-described operation on all point cloud data or the above-described operation on point cloud data indicated by orientation information and/or viewport information.
  • the transmission unit may perform the above-described operation on all point cloud data or on the point cloud data indicated by orientation information and/or viewport information.
  • FIG. 22 shows an example of a configuration diagram of an apparatus for receiving point cloud data according to embodiments.
  • FIG. 22 shows a point cloud system according to embodiments, and part/all of the system is a transmission/reception device of FIG. 1, an encoding process of FIG. 4, a 2D video/image encoder of FIG. 15, a decoding process of FIG. 16, and It may include some/all of the transmitting device and/or the receiving device of FIG. 19. In addition, it may be included in or correspond to some/all of the systems of FIGS. 20 and 21.
  • Each configuration of the receiving device may be a module/unit/component/hardware/software/processor.
  • a delivery client (22006) may receive point cloud data, a point cloud bitstream, or a file/segment including a corresponding bitstream, transmitted by the point cloud data transmission device according to the embodiments.
  • the receiving device may receive point cloud data through a broadcasting network or may receive point cloud data through a broadband.
  • point cloud data can be received through a digital storage medium.
  • the receiving device may include a process of decoding the received data and rendering it according to the user's viewport.
  • the delivery client 22006 (or a reception processing unit) may perform processing according to a transmission protocol on the received point cloud data.
  • the receiving processing unit may be included in the receiving unit, or may be configured as a separate component/module.
  • the reception processing unit may perform the reverse process of the transmission processing unit described above so as to correspond to the transmission processing performed by the transmission side.
  • the reception processing unit may transmit the acquired point cloud data to the file/segment decapsulation unit 22000, and the acquired point cloud related metadata may be transmitted to the metadata processing unit (not shown).
  • the sensing/tracking unit acquires orientation information and/or viewport information.
  • the sensing/tracking unit 22005 includes a delivery client 22006, a file/segment decapsulation unit 22000, a point cloud decoding unit 22001, 22002, and a point cloud processing unit ( 22003).
  • the delivery client 22006 may receive all point cloud data or point cloud data indicated by the orientation information and/or the viewport information, based on the orientation information and/or the viewport information.
  • the file/segment decapsulation unit 22000 may decapsulate all point cloud data or decapsulate point cloud data indicated by orientation information and/or viewport information based on orientation information and/or viewport information. have.
  • the point cloud decoding unit (video decoding unit 22001 and/or image decoding unit 22002) decodes all point cloud data based on orientation information and/or viewport information, or is indicated by orientation information and/or viewport information. Can decode point cloud data.
  • the point cloud processing unit 22003 may process all point cloud data, or may process point cloud data indicated by orientation information and/or viewport information.
  • the File/Segment decapsulation unit (22000) includes Video Track Decapsulation, Metadata Track Decapsulation, and/or Image Decapsulation. Perform.
  • the file/segment decapsulation unit 22000 may decapsulate point cloud data in the form of a file transmitted from the reception processing unit.
  • the file/segment decapsulation unit 22000 may decapsulate files or segments according to ISOBMFF or the like to obtain a point cloud bitstream or point cloud related metadata (or a separate metadata bitstream).
  • the acquired point cloud bitstream may be transmitted to the point cloud decoding units 22001 and 22002, and the acquired point cloud related metadata (or metadata bitstream) may be transmitted to the metadata processing unit (not shown).
  • the point cloud bitstream may include metadata (metadata bitstream).
  • the metadata processing unit may be included in the point cloud video decoder, or may be configured as a separate component/module.
  • the point cloud related metadata acquired by the file/segment decapsulation unit 22000 may be in the form of a box or track in a file format.
  • the file/segment decapsulation unit 22000 may receive metadata required for decapsulation from the metadata processing unit, if necessary.
  • the point cloud related metadata may be transmitted to the point cloud decoding units 22001 and 22002 and used for a point cloud decoding procedure, or may be transmitted to the point cloud rendering unit 22004 and used for the point cloud rendering procedure.
  • the file/segment decapsulation unit 22000 may generate metadata related to point cloud data.
  • the video track decapsulation in the file/segment decapsulation unit 22000 decapsulates the video track included in the file and/or segment. Decapsulates video stream(s) including geometric video, attribute video, accupancy map, auxiliary data and/or mesh data.
  • Metadata Track Decapsulation in the file/segment decapsulation unit 22000 decapsulates a bitstream including metadata related to point cloud data and/or additional data.
  • Image decapsulation in the file/segment decapsulation unit 22000 decapsulates image(s) including geometric images, attribute images, accupancy maps, auxiliary data, and/or mesh data.
  • a video decoding unit (22001) performs geometry video decompression, attribute video decompression, accupancy map decompression, auxiliary data decompression, and/or mesh data decompression.
  • the video decoding unit decodes geometry video, attribute video, auxiliary data, and/or mesh data in response to a process performed by the video encoding unit of the point cloud transmission apparatus according to the embodiments.
  • the image decoding unit (Image Decoding, 22002) performs geometric image decompression, attribute image decompression, accupancy map decompression, auxiliary data decompression, and/or mesh data decompression.
  • the image decoding unit decodes a geometry image, an attribute image, auxiliary data, and/or mesh data in response to a process performed by the image encoding unit of the point cloud transmission apparatus according to the embodiments.
  • the video decoding unit 22001 and the image decoding unit 22002 according to the embodiments may be processed by one video/image decoder as described above, and may be performed in separate paths as shown in the figure.
  • the video decoding unit 22001 and/or the image decoding unit 22002 may generate video data and/or metadata related to image data.
  • the point cloud processing unit (22003) performs geometry reconstruction and/or attribute reconstruction.
  • the geometry reconstruction reconstructs a geometry video and/or a geometry image based on an accupancy map, auxiliary data, and/or mesh data from decoded video data and/or decoded image data.
  • the attribute reconstruction reconstructs an attribute video and/or an attribute image based on an attribute map, auxiliary data, and/or mesh data from the decoded attribute video and/or the decoded attribute image.
  • an attribute may be a texture.
  • an attribute may mean information on a plurality of attributes.
  • the point cloud processing unit 22003 receives metadata from the video decoding unit 22001, the image decoding unit 22002, and/or the file/segment decapsulation unit 22000, and processes the point cloud based on the metadata. can do.
  • a point cloud rendering unit (22004) renders a reconstructed point cloud.
  • the point cloud rendering unit 22004 receives metadata from the video decoding unit 22001, the image decoding unit 22002, and/or the file/segment decapsulation unit 22000, and renders the point cloud based on the metadata. can do.
  • the display displays the rendered result on an actual display device.
  • the transmitting side encodes the point cloud data into a bitstream, encapsulates it in the form of a file and/or segment, and transmits the file, and And/or the segment shape may be decapsulated into a bitstream including a point cloud and decoded into point cloud data.
  • the point cloud data transmission apparatus encapsulates point cloud data based on a file, wherein the file is a V-PCC track including parameters related to the point cloud, and a geometry track including geometry.
  • An attribute track including an attribute and an accufancy track including an accufancy map may be included.
  • the point cloud data receiving apparatus decapsulates the point cloud data based on a file, and in this case, the file includes a V-PCC track including a parameter related to the point cloud, a geometry track including the geometry, and an attribute. It may include an attribute track to be included and an accufancy track including an accufancy map.
  • the above-described encapsulation operation may be performed by the file/segment encapsulation unit 20004 of FIG. 20, the file/segment encapsulation unit 21009 of FIG. 21, and the like, and the decapsulation operation described above is
  • the file/segment decapsulation unit 20005 of FIG. 22, the file/segment decapsulation unit 22000 of FIG. 22, and the like may be performed.
  • FIG. 23 shows an example of a structure capable of interworking with a method/device for transmitting and receiving point cloud data according to embodiments.
  • the structure according to the embodiments is an AI (Ariticial Intelligence) server 2360, a robot 2310, an autonomous vehicle 2320, an XR device 2330, a smartphone 2340, a home appliance 2350 and/or an HMD ( At least one of the 2370) is connected to the cloud network 2300.
  • the robot 2310, the autonomous vehicle 2320, the XR device 2330, the smartphone 2340, or the home appliance 2350 may be referred to as a device.
  • the XR device 2330 may correspond to a point cloud compressed data (PCC) device according to embodiments or may be interlocked with a PCC device.
  • PCC point cloud compressed data
  • the cloud network 2300 may constitute a part of the cloud computing infrastructure or may mean a network that exists in the cloud computing infrastructure.
  • the cloud network 2300 may be configured using a 3G network, a 4G or long term evolution (LTE) network, or a 5G network.
  • LTE long term evolution
  • the AI server 2360 includes at least one of a robot 2310, an autonomous vehicle 2320, an XR device 2330, a smartphone 2340, a home appliance 2350, and/or an HMD 2370, and a cloud network 2300. ), and may help at least part of the processing of the connected devices 2310 to 2370.
  • the HMD (Head-Mount Display) 2370 represents one of the types in which the XR device 2330 and/or the PCC device according to the embodiments may be implemented.
  • the HMD type device according to the embodiments includes a communication unit, a control unit, a memory unit, an I/O unit, a sensor unit, and a power supply unit.
  • the devices 2310 to 2350 shown in FIG. 23 may be interlocked/coupled with the point cloud data transmission/reception apparatus according to the above-described embodiments.
  • the XR/PCC device 2330 is applied with PCC and/or XR (AR+VR) technology to provide a head-mount display (HMD), a head-up display (HUD) provided in a vehicle, a television, a mobile phone, a smart phone, It may be implemented as a computer, wearable device, home appliance, digital signage, vehicle, fixed robot or mobile robot.
  • HMD head-mount display
  • HUD head-up display
  • vehicle a television
  • mobile phone a smart phone
  • It may be implemented as a computer, wearable device, home appliance, digital signage, vehicle, fixed robot or mobile robot.
  • the XR/PCC device 2330 analyzes 3D point cloud data or image data acquired through various sensors or from an external device to generate location data and attribute data for 3D points, thereby Information can be obtained, and the XR object to be output can be rendered and output.
  • the XR/PCC apparatus 2330 may output an XR object including additional information on the recognized object in correspondence with the recognized object.
  • the autonomous vehicle 2320 may be implemented as a mobile robot, a vehicle, or an unmanned aerial vehicle by applying PCC technology and XR technology.
  • the autonomous driving vehicle 2320 to which the XR/PCC technology is applied may refer to an autonomous driving vehicle having a means for providing an XR image, an autonomous driving vehicle that is an object of control/interaction within the XR image.
  • the autonomous vehicle 2320 which is the object of control/interaction in the XR image, is distinguished from the XR device 2330 and may be interlocked with each other.
  • the autonomous vehicle 2320 having a means for providing an XR/PCC image may acquire sensor information from sensors including a camera, and may output an XR/PCC image generated based on the acquired sensor information.
  • the autonomous vehicle 2320 may provide an XR/PCC object corresponding to a real object or an object in a screen to the occupant by outputting an XR/PCC image with a HUD.
  • the XR/PCC object when the XR/PCC object is output to the HUD, at least a part of the XR/PCC object may be output to overlap the actual object facing the occupant's gaze.
  • the XR/PCC object when the XR/PCC object is output on a display provided inside the autonomous vehicle 2320, at least a part of the XR/PCC object may be output to overlap the object in the screen.
  • the autonomous vehicle 2320 may output XR/PCC objects corresponding to objects such as lanes, other vehicles, traffic lights, traffic signs, motorcycles, pedestrians, and buildings.
  • VR Virtual Reality
  • AR Augmented Reality
  • MR Magnetic Reality
  • PCC Point Cloud Compression
  • VR technology is a display technology that provides objects or backgrounds in the real world only as CG images.
  • AR technology refers to a technology that shows a virtually created CG image on a real object image.
  • MR technology is similar to the AR technology described above in that virtual objects are mixed and combined in the real world.
  • real objects and virtual objects made from CG images are clear, and virtual objects are used in a form that complements the real objects, whereas in MR technology, the virtual objects are regarded as having the same characteristics as the real objects. It is distinct from technology. More specifically, for example, it is a hologram service to which the aforementioned MR technology is applied.
  • VR, AR, and MR technologies are sometimes referred to as XR (extended reality) technology rather than clearly distinguishing between them. Therefore, embodiments of the present invention are applicable to all of VR, AR, MR, and XR technologies.
  • One such technology can be applied to encoding/decoding based on PCC, V-PCC, and G-PCC technologies.
  • the PCC method/device according to the embodiments may be applied to an autonomous vehicle 2320 that provides an autonomous driving service.
  • the autonomous vehicle 2320 providing an autonomous driving service is connected to a PCC device to enable wired/wireless communication.
  • Point cloud compressed data (PCC) transmission and reception device when connected to enable wired/wireless communication with the autonomous vehicle 2320, AR/VR/PCC service related content data that can be provided together with the autonomous driving service May be received/processed and transmitted to the autonomous vehicle 2320.
  • the point cloud data transmission/reception device when the point cloud data transmission/reception device is mounted on the autonomous vehicle 2320, the point cloud transmission/reception device receives/processes AR/VR/PCC service-related content data according to a user input signal input through the user interface device. Can be provided to.
  • the vehicle or user interface device may receive a user input signal.
  • the user input signal according to the embodiments may include a signal indicating an autonomous driving service.
  • the point cloud encoder includes 3D point cloud content (or point cloud). Data) can be mapped onto a two-dimensional plane.
  • a patch according to embodiments is a mapping unit used when mapping 3D point cloud content to a 2D plane.
  • the point cloud encoder may generate one or more patches and pack the generated patches (eg, patch packing 40001). Since the 3D point cloud content is divided into patches and the patches are mapped to the 2D plane, the 2D image created by mapping contains an artificial boundary surface and has discontinuous attribute (e.g., color) values than a general x-dimensional image. . Therefore, it may cause a bug in the operation of the point cloud encoder and reduce the compression efficiency.
  • the point cloud encoder may pack a patch based on a material ID of the patch in order to improve compression efficiency (for example, the patch generation 40000 and patch packing described in FIG. 40001)).
  • the material ID indicates the material type of one or more points corresponding to the patch.
  • the material type according to the embodiments may be used as an indicator for identifying a characteristic of a point or an object of a point cloud.
  • points corresponding to one or more patches may have the same or similar attributes.
  • the point cloud encoder may be arranged by adjusting the spacing of patches. Therefore, efficient data compression is possible when patches having the same material ID are placed in the same area of the image plane.
  • the point cloud encoder may pack a patch, encode point cloud data including geometry, an ocupancy map, attributes, and information related to the patch (eg, patch data), and transmit it through a bitstream. Therefore, the point cloud decoder (for example, the point cloud decoder 1008) according to the embodiments may decode point cloud data included in the received bitstream. The point cloud decoder may restore 3D point cloud data based on information related to geometry, ocupancy maps, attributes, and patches included in the point cloud data.
  • the method of packing a patch based on the patch packing area is to divide a two-dimensional plane (for example, an ocupancy map) into one or more areas for packing patches having the same material ID, and Shows how to pack them.
  • the point cloud encoder (for example, the point cloud encoder 10002) according to the embodiments creates a two-dimensional plane (for example, an ocupancy map), sets an area to pack patches having the same material ID, and Patches with the same material ID are placed together in the same area.
  • the point cloud encoder places patches with a material ID value of 1 in the first area 2410, and places patches with a material ID value of 2 in the second area 2420, and has a material ID value of 3 Phosphorus patches may be disposed in the third area 2430.
  • the first area 2410 and the second area 2420 according to the exemplary embodiments are adjacent areas or different areas.
  • the second area 2420 and the third area 3430 according to the embodiments are adjacent areas or different areas.
  • An example 2400 of FIG. 24 shows an example in which a point cloud encoder divides a 2D plane into two vertical lines and sets three regions 2410, 2420, and 2430.
  • a method of setting one or more areas for arranging one or more patches having the same material ID is not limited to this example. Accordingly, according to embodiments, the point cloud encoder may set one or more areas by dividing the 2D plane into one or more horizontal lines or one or more horizontal lines and vertical lines perpendicular to each other.
  • the point cloud encoder determines the size of the corresponding area based on the areas of patches to be disposed in the same area.
  • the total area of patches for each material ID is expressed as follows.
  • the parameter size U of Equation 1 represents the horizontal width of the patch disposed on the two-dimensional plane (for example, the horizontal width of the patch described in FIG. 7 ), and the parameter Size V is It represents the height in the vertical direction (for example, the height in the vertical direction of the patch described in FIG. 7 ).
  • a unit representing the value of the width and height of the patch according to the embodiments is the packing block size of the ocupancy map.
  • the point cloud encoder according to embodiments arranges patches having the same material ID in a set area according to a raster scan order. Therefore, the point cloud encoder sequentially arranges patches in the corresponding area from the top left to the bottom right.
  • Areas in which one or more patches having the same material ID according to the embodiments are arranged are tiles in video coding. Mapped to (tile) or slice (slice). Therefore, the point cloud encoder can perform efficient encoding according to the material characteristics by placing and encoding one or more patches with the same material ID on a tile or slice, and enables random access in a material unit. have.
  • the example 2500 of the patch packing method of FIG. 25 is similar to the example 2400 of the patch packing method of FIG. 24, but differs in that patches are arranged by adjusting the patch packing order.
  • the point cloud encoder (for example, the point cloud encoder 10002) according to the embodiments generates a two-dimensional plane (for example, an ocupancy map) and converts one or more packets having the same material ID into the two-dimensional plane. Packed in a 2D plane in raster scan order from top left to bottom right.
  • a line 2510 shown in FIG. 25 represents a raster scan sequence.
  • the point cloud encoder may sequentially pack one or more patches 2520 having a material ID value of 1 in the 2D plane from the top left of the 2D plane to the right.
  • the point cloud encoder packs one or more patches 2530 having a material ID value of 2.
  • the point cloud encoder packs the remaining patches with the material ID value of 2 in the area corresponding to the next row according to the raster scan order.
  • the point cloud encoder packs all patches with a material ID of 2
  • it packs the patches with a material ID of 3.
  • the point cloud encoder may pack patches having the same material characteristics adjacent to each other in a two-dimensional plane, and pack the patches having different material characteristics so as not to overlap each other.
  • the point cloud encoder may set a safeguard that is an interval between at least two patches and pack the patches.
  • the safeguard according to the embodiments means the minimum interval that must exist between the packed patches, and the value may be expressed in units of blocks of the ocupancy map.
  • the resolution may be determined according to the size of the block, and the size of the block may be changed.
  • the patch packing method based on the safeguard according to the embodiments is a sequential operation of a point cloud encoder (or a program stored in one or more memories (for example, memory 17060) or an algorithm executed by a program) Is performed according to.
  • the point cloud encoder may change the spacing between patches having the same material characteristic (for example, by setting it to be narrower) to arrange the patches. Therefore, the point cloud encoder can reduce the amount of data required and perform efficient encoding by reducing the resolution of an ocupancy map, geometry image, and attribute image.
  • patches with the same material ID are placed without a safeguard, and patches with different material IDs are placed by setting a safeguard.
  • the information value indicating the safeguard inserted between patches is 1, and if the material ID is the same, the information value indicating the safeguard inserted between the patches is 0. Can be set.
  • a safe guard that is set between patches with different material characteristics may be referred to as material safeguard.
  • 26 is an example of a safeguard insertion method according to embodiments.
  • FIG. 26 shows an example 2600 of a method of inserting a safeguard between the patch packing areas described in FIG. 24.
  • the point cloud encoder (for example, the point cloud encoder 10002) according to embodiments sets an area to pack a patch for each of the same material ID in a two-dimensional plane, and places patches having the same material ID in the same area. .
  • a first area 2610 in which patches having a material ID value of 1 are arranged (for example, the first area 2410 in FIG. 24), and patches having a material ID value of 2 are included.
  • the disposed second area 2620 (for example, the second area 2420 in FIG.
  • a third area 2630 in which patches having a material ID value of 3 are disposed (for example, the third area in FIG. An area 2430) may be included.
  • the size, shape, and/or location of the area in which the patches are packed are not limited to this example.
  • the point cloud encoder sets the area in which patches are packed and the safeguards 2615 and 26245 together.
  • the safeguard according to the embodiments is located between areas where patches are packed.
  • 2 6 is a first safe guard 2615 located between the first area 2610 and the second area 2620, and a second safe guard 2625 located between the second area 2620 and the third area 2630. ).
  • Each of the first safeguard 2615 and the second safeguard 2625 according to the exemplary embodiments corresponds to one block when occupied.
  • the data values of the first safeguard 2615 and the second safeguard 2625 according to the embodiments are set to 1.
  • the point cloud encoder according to embodiments may pack patches having the same material ID value for each region.
  • Safeguard-based patch packing method is performed according to a sequential operation of a point cloud encoder (or a program stored in one or more memories (for example, memory 17060) or an algorithm executed by a program) do.
  • occupancySizeU represents the width of the Accupancy map, and the unit is the occupancy packing block size.
  • the width of the second area 2620 is expressed as occupancySizeU * m2/(m1+m2+m3), and the width of the third area 2630 is expressed as occupancySizeU * m3/(m1+m2+m3).
  • the patch is placed so that the upper left end of the patch corresponds to an arbitrary point (u,v) existing in the map plane during Okyufan.
  • Arbitrary points (u,v) exist in the horizontal range (offsetW, offsetW+occupancySizeU-patchSizeU) and the vertical range ([offsetW, offsetW+occupancySizeV-patchSizeV0) in the occupancy map.
  • FIG. 27 shows an example 2600 of a method of packing patches and inserting a safeguard based on the patch packing order adjustment described in FIG. 25.
  • the point cloud encoder (for example, the point cloud encoder 10002) according to the embodiments is a raster scan sequence of one or more packets having the same material ID from the upper left to the lower right of the 2D plane. order) on the 2D plane. Therefore, the point cloud encoder sequentially processes one or more patches 2710 (for example, one or more patches 2520 in FIG. 25) with a material ID value of 1 in a direction from the upper left to the right of the 2D plane. It can be packed on a two-dimensional plane.
  • the point cloud encoder When one or more patches 2710 having a material ID value of 1 are packed, the point cloud encoder replaces the safeguard 2730 corresponding to one occupancy block in a patch packing area (for example, a material ID value of 1). Is inserted under the area where one or more patches 2710 are disposed). The data value of the inserted safeguard 2730 is set to 1. Thereafter, the point cloud encoder packs one or more patches 2720 (eg, one or more patches 2530 in FIG. 25) having a material ID value of 2. The point cloud encoder may pack patches having the same material characteristics adjacent to each other in a two-dimensional plane, and may pack patches having different material characteristics so as not to overlap each other.
  • Safeguard-based patch packing method is performed according to a sequential operation of a point cloud encoder (or a program stored in one or more memories (for example, memory 17060) or an algorithm executed by a program) do.
  • the patch is placed so that the upper left end of the patch corresponds to an arbitrary point (u,v) existing in the map plane during Okyufan.
  • Arbitrary points (u,v) exist in the horizontal range (0, occupancySizeU-patchSizeU0) and vertical range (0, occupancySizeV-patchSizeV0) in the occupancy map.
  • the transmission device includes one or more components (for example, patch data or patch including information related to patch packing described in FIGS. 24 to 27).
  • Information for example, the ascetic patch information described in FIG. 16), geometry, attributes, and occupancy maps
  • the receiving device or the point cloud decoder can decode components in the bitstream and restore the point cloud content.
  • the bitstream of FIG. 28 is an example 2800 of a V-PCC bitstream.
  • the bitstream is a sequence of bits forming a representation of related data and coded point cloud frames forming coded point cloud sequences.
  • the bitstream 2810 according to the embodiments includes one or more units (eg, V-PCC unit).
  • the unit (for example, V-PCC unit) 2820 includes a syntax structure including a header (for example, V-PCC Unit Header) and a payload (for example, V-PCC Unit payload). structure).
  • the header according to the embodiments includes information indicating the type of the unit. That is, the information indicating the type of the unit indicates the type of information transmitted through the payload.
  • Payload according to embodiments is a syntax structure including bytes including sub-bitstream data. The sub-bitstream corresponds to each component (eg geometry, attribute, occupancy map or patch data).
  • the payload type 2830 according to the unit type is a sequence parameter set, patch sequence data, Occupancy Video data, geometry video data, and attribute video. Includes attribute video data.
  • the patch sequence data unit 2840 includes a sequence parameter set, a frame parameter set, a geometry parameter set, an attribute parameter set, a geometry patch parameter set, an attribute patch parameter set, and patch data F0, .., patch data Fn).
  • Patch data includes patch data or patch information including information related to patch packing described with reference to FIGS. 24 to 27 (eg, acyl patch information described with reference to FIG. 16 ).
  • 29 is a syntax of patch data unit information according to embodiments.
  • the syntax of the patch data unit information may include information related to patch packing.
  • Information related to patch packing included in the syntax of the patch data unit information is as follows.
  • material_id [ frmIdx ][ patchIndex ] is the material ID of the patch indicated by the current patch data unit. Patches with the same material properties have the same material ID.
  • material_packing_method [ frmIdx ][ patchIndex ] is information indicating a packing method for a patch indicated by the current patch data unit.
  • the packing method is a method of packing one or more patches (including the patch indicated by the current patch data unit) based on the patch packing area (for example, the patch packing method described in FIG. 24 ). It represents an example of (2400)).
  • the packing method is a method of packing one or more patches (including the patch indicated by the current patch data unit) by adjusting the patch packing order (for example, an example of the patch packing method described in FIG. 25 ( 2500)).
  • material_safeguard_type [ frmIdx ][ patchIndex ] indicates how to insert a material safeguard for the patch indicated by the current patch data unit.
  • the material safeguard insertion method shows a method of inserting a material safeguard between the patch packing areas (for example, an example of the safeguard insertion method in FIG. 26 (2600)).
  • the material safeguard insertion method is a method of packing patches and inserting a material safeguard based on patch packing order adjustment (for example, an example (2700) of the safeguard insertion method in FIG. Show.
  • Information related to patch packing may be inserted into information of a patch data unit, a frame, or a sequence. That is, the information related to patch packing may indicate a packing method according to material characteristics of a patch data unit, a frame, or a sequence, a safeguard insertion method, and the like. Accordingly, the frame parameter set or sequence parameter set according to the embodiments may include information related to patch packing.
  • FIG. 30 is a flow diagram of a method for receiving point cloud data according to embodiments.
  • FIG. 30 is a flow diagram 3000 of a method for receiving point cloud data by a receiver or a point cloud decoder (for example, the V-PCC decoder described in FIG. 16) as described with reference to FIGS. 24 to 29.
  • a point cloud decoder for example, the V-PCC decoder described in FIG. 16
  • the receiving device receives a bitstream including point cloud data (3010). Details of the bitstream are the same as those described with reference to FIGS. 1 to 29, and thus detailed descriptions are omitted.
  • the receiving device decodes the point cloud data (3020).
  • Point cloud data according to embodiments includes geometry, ocupancy map, attribute, and patch data. Since the point cloud data is the same as or similar to the point cloud data described in FIGS. 1 to 29, a detailed description will be omitted.
  • the patch data according to embodiments includes information related to a patch, which is a mapping unit for mapping point cloud content to a 2D image. Since the patch data is the same as or similar to the patch data described in FIGS. 24 to 29, a detailed description will be omitted.
  • Patch data according to embodiments includes a material ID of the patch (for example, material_id described in FIG. 29). The material ID according to the embodiments indicates a material type of one or more points corresponding to the patch.
  • the patch data includes information indicating a patch packing method (for example, material_packing_method described in FIG. 29).
  • the information indicating the patch packing method according to the embodiments indicates at least one of a method of packing one or more patches based on the patch packing area and a method of packing one or more patches by adjusting a patch packing order.
  • the patch data according to the embodiments includes information indicating a method of inserting a material safeguard for a patch (for example, material_safeguard_type described in FIG. 29).
  • the material safeguard insertion method includes a method of inserting a material safeguard between the patch packing areas (for example, an example of the safeguard insertion method in Fig.
  • At least one of the patch packing method and the safeguard insertion method is a sequential operation of a point cloud encoder or a program or program stored in one or more memories (for example, memory 17060). Can be performed by an algorithm executed by The point cloud decoder according to the embodiments may perform an operation corresponding to the reverse process of the operation of the point cloud encoder.
  • the operation of the point cloud decoder is the same as or similar to the operation of the point cloud decoder described in FIGS.
  • the point cloud decoder renders the decoded point cloud data (3030).
  • 31 is a flow diagram of a method for processing point cloud data according to embodiments.
  • a flow diagram 3100 of FIG. 31 is an embodiment of the flow diagram 3000 described with reference to FIG. 30 and shows a method of processing point cloud data by a receiving device or a point cloud decoder.
  • a point cloud decoder (or a demultiplexer (for example, a demultiplexer, 16000 described in FIG. 16)) according to embodiments demultiplexes a bitstream including point cloud data to output one or more sub-bitstreams.
  • the one or more sub-bitstreams according to the embodiments are a first sub-bitstream corresponding to a geometry (for example, the compressed geometry image described in FIG. 16), and a second sub-bitstream corresponding to an attribute (for example, Corresponds to the compressed texture image described in FIG. 16), a third sub-bitstream corresponding to the ocupancy map (for example, the compressed ocupancy map described in FIG. 16), and one or more patches It includes a fourth sub-bitstream (for example, compressed acillary patch information).
  • the point cloud decoder decompresses one or more sub-bitstreams and outputs geometry data, attribute data, ocupancy map data, and patch data corresponding to one or more patches (3120).
  • the patch data includes information related to a patch, which is a mapping unit for mapping point cloud content to a 2D image. Since the patch data is the same as or similar to the patch data described in FIGS. 24 to 29, a detailed description will be omitted.
  • Patch data according to embodiments includes a material ID of the patch (for example, material_id described in FIG. 29 ). The material ID according to the embodiments indicates a material type of one or more points corresponding to the patch.
  • the patch data includes information indicating a patch packing method (for example, material_packing_method described in FIG. 29).
  • the information indicating the patch packing method according to the embodiments indicates at least one of a method of packing one or more patches based on the patch packing area and a method of packing one or more patches by adjusting a patch packing order.
  • the patch data according to the embodiments includes information indicating a method of inserting a material safeguard for a patch (for example, material_safeguard_type described in FIG. 29 ).
  • the material safeguard insertion method includes a method of inserting a material safeguard between the patch packing areas (for example, an example of the safeguard insertion method in Fig. 26 (2600)) and packing the patches based on the patch packing order adjustment and It corresponds to at least one of the methods of inserting the safeguard (for example, an example 2700 of the safeguard insertion method of FIG. 27).
  • At least one of the patch packing method and the safeguard insertion method is a sequential operation of a point cloud encoder or a program or program stored in one or more memories (for example, memory 17060). It can be performed by an algorithm executed by The point cloud decoder according to the embodiments may perform an operation corresponding to the reverse process of the operation of the point cloud encoder.
  • the point cloud decoder reconstructs point cloud data based on geometry data, attribute data, occupancy map data, and patch data (3120). Since the reconstruction method and/or process according to the embodiments is the same as or similar to the reconstruction method and/or operation described in FIG. 22, a detailed description will be omitted.
  • the point cloud decoder is a demultiplexer that outputs one or more sub-bitstreams by demultiplexing a bitstream including point cloud data, one or more processors, and one or more memories (for example, A memory 17060) may be included.
  • One or more processors according to embodiments execute one or more programs stored in one or more memories.
  • One or more programs according to embodiments include instructions instructing to process point cloud data.
  • Instructions according to embodiments output geometry data, attribute data, ocupancy map data, and patch data corresponding to the one or more patches by decompressing one or more sub-bitstreams, and geometry data, attribute data , Instructs to reconstruct the point cloud data based on the map data and the patch data during occupancy. Since the instructions according to the embodiments are the same or similar to the instructions instructing to process the point cloud according to the operation of the point cloud decoder described in FIGS. 1 to 29, detailed descriptions will be omitted.
  • the method/apparatus for receiving point cloud data according to the embodiments may be combined with all/some of the above-described embodiments to provide point cloud content.
  • Each of the above-described parts, modules or units may be software, processor, or hardware parts that execute successive processes stored in a memory (or storage unit). Each of the steps described in the above-described embodiment may be performed by processor, software, and hardware parts. Each module/block/unit described in the above-described embodiment may operate as a processor, software, or hardware. In addition, methods suggested by the embodiments may be executed as code. This code can be written to a storage medium that can be read by the processor, and thus can be read by a processor provided by the apparatus.
  • Various components of the apparatus of the embodiments may be implemented by hardware, software, firmware, or a combination thereof.
  • Various components of the embodiments may be implemented as one chip, for example, one hardware circuit.
  • the components according to the embodiments may be implemented as separate chips.
  • at least one or more of the components of the device according to the embodiments may be composed of one or more processors capable of executing one or more programs, and one or more programs may be implemented. It may include instructions for performing or performing any one or more of the operations/methods according to the examples.
  • Executable instructions for performing the method/operations of the apparatus may be stored in a non-transitory CRM or other computer program products configured to be executed by one or more processors, or may be stored in one or more It may be stored in a temporary CRM or other computer program products configured for execution by the processors.
  • the memory according to the embodiments may be used as a concept including not only volatile memory (eg, RAM, etc.) but also non-volatile memory, flash memory, PROM, and the like.
  • it may be implemented in the form of a carrier wave such as transmission through the Internet.
  • the processor-readable recording medium is distributed over a computer system connected through a network, so that the processor-readable code can be stored and executed in a distributed manner.
  • first and second may be used to describe various elements of the embodiments. However, the interpretation of various components according to the embodiments should not be limited by the above terms. These terms are only used to distinguish one component from another. It's just a For example, a first user input signal may be referred to as a second user input signal. Similarly, the second user input signal may be referred to as a first user input signal. The use of these terms should be construed as not departing from the scope of various embodiments.
  • the first user input signal and the second user input signal are both user input signals, but do not mean the same user input signals unless clearly indicated in context.
  • Conditional expressions such as when, when, and when used to describe the embodiments are not limited to an optional case. When a specific condition is satisfied, it is intended to perform a related operation in response to a specific condition or to interpret the related definition.
  • the embodiments may be applied wholly or partially to the point cloud data transmission/reception apparatus and system.
  • Embodiments may include changes/modifications, and changes/modifications do not depart from the scope of the claims and the same.

Abstract

Un procédé de réception de données de nuage de points, selon des modes de réalisation, permet de recevoir et de décoder des données de nuage de points. Un procédé de traitement de données de nuage de points, selon des modes de réalisation, permet de traiter des données de nuage de points.
PCT/KR2020/003892 2019-03-20 2020-03-20 Dispositif de réception de données de nuage de points, procédé de réception de données de nuage de points, dispositif de traitement de données de nuage de points, et procédé de traitement de données de nuage de points WO2020190097A1 (fr)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112666569A (zh) * 2020-12-01 2021-04-16 天津优控智行科技有限公司 一种无人驾驶系统激光雷达连续点云的压缩方法
CN114581621A (zh) * 2022-03-07 2022-06-03 北京百度网讯科技有限公司 地图数据处理方法、装置、电子设备和介质
WO2022166968A1 (fr) * 2021-02-08 2022-08-11 荣耀终端有限公司 Procédé et dispositif de codage/décodage de nuage de points basés sur une projection plane régularisée bidimensionnelle

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180268570A1 (en) * 2017-03-16 2018-09-20 Samsung Electronics Co., Ltd. Point cloud and mesh compression using image/video codecs
KR20180107192A (ko) * 2016-01-29 2018-10-01 매직 립, 인코포레이티드 3차원 메쉬들의 직교-투사-기반 텍스처 아틀라스 패킹
KR20180122947A (ko) * 2017-05-04 2018-11-14 톰슨 라이센싱 2차원 포인트 클라우드들을 인코딩 및 디코딩하기 위한 방법 및 장치
WO2019012067A1 (fr) * 2017-07-13 2019-01-17 Thomson Licensing Procédés, dispositifs et flux d'encodage et de décodage de vidéo volumétrique

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20180107192A (ko) * 2016-01-29 2018-10-01 매직 립, 인코포레이티드 3차원 메쉬들의 직교-투사-기반 텍스처 아틀라스 패킹
US20180268570A1 (en) * 2017-03-16 2018-09-20 Samsung Electronics Co., Ltd. Point cloud and mesh compression using image/video codecs
KR20180122947A (ko) * 2017-05-04 2018-11-14 톰슨 라이센싱 2차원 포인트 클라우드들을 인코딩 및 디코딩하기 위한 방법 및 장치
WO2019012067A1 (fr) * 2017-07-13 2019-01-17 Thomson Licensing Procédés, dispositifs et flux d'encodage et de décodage de vidéo volumétrique

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SCHWARZ SEBASTIAN; PREDA MARIUS; BARONCINI VITTORIO; BUDAGAVI MADHUKAR; CESAR PABLO; CHOU PHILIP A; COHEN ROBERT A; KRIVOKUCA MAJA: "Emerging MPEG Standards for Point Cloud Compression", IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, vol. 9, no. 1, 30 March 2019 (2019-03-30), pages 133 - 148, XP011714044 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112666569A (zh) * 2020-12-01 2021-04-16 天津优控智行科技有限公司 一种无人驾驶系统激光雷达连续点云的压缩方法
CN112666569B (zh) * 2020-12-01 2023-03-24 天津优控智行科技有限公司 一种无人驾驶系统激光雷达连续点云的压缩方法
WO2022166968A1 (fr) * 2021-02-08 2022-08-11 荣耀终端有限公司 Procédé et dispositif de codage/décodage de nuage de points basés sur une projection plane régularisée bidimensionnelle
CN114581621A (zh) * 2022-03-07 2022-06-03 北京百度网讯科技有限公司 地图数据处理方法、装置、电子设备和介质

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