Patent Publication Number: US-2022230360-A1

Title: Point cloud data transmission device, point cloud data transmission method, point cloud data reception device, and point cloud data reception method

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Application No. 63/134,555, filed on Jan. 6, 2021, which is hereby incorporated by reference as if fully set forth herein. 
    
    
     TECHNICAL FIELD 
     Embodiments relate to a method and device for processing point cloud content. 
     BACKGROUND 
     Point cloud content is content represented by a point cloud, which is a set of points belonging to a coordinate system representing a three-dimensional space. The point cloud content may express media configured in three dimensions, and is used to provide various services such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and self-driving services. However, tens of thousands to hundreds of thousands of point data are required to represent point cloud content. Therefore, there is a need for a method for efficiently processing a large amount of point data. 
     SUMMARY 
     Embodiments provide a device and method for efficiently processing point cloud data. Embodiments provide a point cloud data processing method and device for addressing latency and encoding/decoding complexity. 
     The technical scope of the embodiments is not limited to the aforementioned technical objects, and may be extended to other technical objects that may be inferred by those skilled in the art based on the entire contents disclosed herein. 
     To achieve these objects and other advantages and in accordance with the purpose of the disclosure, as embodied and broadly described herein, a method for transmitting point cloud data may include encoding point cloud data, and transmitting a bitstream including the point cloud data. In another aspect of the present disclosure, a method for receiving point cloud data may include receiving a bitstream including point cloud data, and decoding the point cloud data. 
     Devices and methods according to embodiments may process point cloud data with high efficiency. 
     The devices and methods according to the embodiments may provide a high-quality point cloud service. 
     The devices and methods according to the embodiments may provide point cloud content for providing general-purpose services such as a VR service and a self-driving service. 
     It is to be understood that both the foregoing general description and the following detailed description of the present disclosure are exemplary and explanatory and are intended to provide further explanation of the disclosure as claimed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the disclosure and together with the description serve to explain the principle of the disclosure. For a better understanding of various embodiments described below, reference should be made to the description of the following embodiments in connection with the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts. In the drawings: 
         FIG. 1  shows an exemplary point cloud content providing system according to embodiments; 
         FIG. 2  is a block diagram illustrating a point cloud content providing operation according to embodiments; 
         FIG. 3  illustrates an exemplary process of capturing a point cloud video according to embodiments; 
         FIG. 4  illustrates an exemplary point cloud encoder according to embodiments; 
         FIG. 5  shows an example of voxels according to embodiments; 
         FIG. 6  shows an example of an octree and occupancy code according to embodiments; 
         FIG. 7  shows an example of a neighbor node pattern according to embodiments; 
         FIG. 8  illustrates an example of point configuration in each LOD according to embodiments; 
         FIG. 9  illustrates an example of point configuration in each LOD according to embodiments; 
         FIG. 10  illustrates a point cloud decoder according to embodiments; 
         FIG. 11  illustrates a point cloud decoder according to embodiments; 
         FIG. 12  illustrates a transmission device according to embodiments; 
         FIG. 13  illustrates a reception device according to embodiments; 
         FIG. 14  illustrates an exemplary structure operable in connection with point cloud data transmission/reception methods/devices according to embodiments; 
         FIG. 15  illustrates a process of encoding, transmission, and decoding point cloud data according to embodiments; 
         FIG. 16  shows a layer-based point cloud data configuration and a structure of geometry and attribute bitstreams according to embodiments; 
         FIG. 17  shows a bitstream configuration according to embodiments; 
         FIGS. 18A and 18B  illustrate a bitstream sorting method according to embodiments; 
         FIG. 19  illustrates a method of selecting geometry data and attribute data according to embodiments; 
         FIGS. 20A to 20C  illustrates a method of configuring a slice including point cloud data according to embodiments; 
         FIG. 21  shows a bitstream configuration according to embodiments; 
         FIG. 22  shows the syntax of a sequence parameter set and a geometry parameter set according to embodiments; 
         FIG. 23  shows the syntax of an attribute parameter set according to embodiments; 
         FIG. 24  shows the syntax of a geometry data unit header according to embodiments; 
         FIG. 25  shows the syntax of an attribute data unit header according to embodiments; 
         FIGS. 26A and 26B  show a single slice-based geometry tree structure and a segmented slice-based geometry tree structure according to embodiments; 
         FIGS. 27A and 27B  show a layer group structure of a geometry coding tree and an aligned layer group structure of an attribute coding tree according to embodiments; 
         FIGS. 28A and 28B  show a layer group of a geometry tree and an independent layer group structure of an attribute coding tree according to embodiments; 
         FIG. 29  shows syntax of parameter sets according to embodiments; 
         FIG. 30  shows a geometry data unit header according to embodiments; 
         FIG. 31  illustrates an example of combining a tree coding mode and a direct coding mode according to embodiments; 
         FIG. 32  shows an overview of an inferred direct coding mode (IDCM) according to embodiments; 
         FIG. 33  illustrates an example of an arithmetic entropy coded (AEC) bitstream and a direct coded (DC) bitstream according to embodiments; 
         FIG. 34  shows an example of a geometry tree structure and slice segments and an example of multiple AEC slices and one DC slice according to embodiments; 
         FIG. 35  shows an example of a geometry tree structure and slice segments and an example of AEC slices and DC slices according to embodiments; 
         FIG. 36  shows an example of a geometry tree structure and slice segments and an example of AEC slices and DC slices according to embodiments; 
         FIG. 37  shows a sequence parameter set (SPS) (seq_parameter_set( )) and a geometry parameter set according to embodiments; 
         FIG. 38  shows a syntax structure of a geometry data unit header (or referred to as a geometry slice header) according to embodiments; 
         FIG. 39  shows a structure of a point cloud data transmission device according to embodiments; 
         FIG. 40  shows a point cloud data reception device according to embodiments; 
         FIG. 41  is a flowchart of a point cloud data reception device according to embodiments; 
         FIG. 42  illustrates an example of efficient processing of a main region of point cloud data by a point cloud data transmission/reception device according to embodiments; 
         FIG. 43  shows a layer group structure and a subgroup bounding box according to embodiments; 
         FIG. 44  shows a geometry parameter set according to embodiments; 
         FIG. 45  shows an attribute parameter set according to embodiments; 
         FIG. 46  shows a geometry data unit header and an attribute data unit header according to embodiments; 
         FIG. 47  illustrates a method for transmitting and receiving point cloud data according to embodiments; 
         FIG. 48  illustrates a method for transmitting and receiving point cloud data according to embodiments; 
         FIG. 49  illustrates a method for transmitting point cloud data according to embodiments; 
       and 
         FIG. 50  illustrates a method for receiving point cloud data according to embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     Reference will now be made in detail to the preferred embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings. The detailed description, which will be given below with reference to the accompanying drawings, is intended to explain exemplary embodiments of the present disclosure, rather than to show the only embodiments that may be implemented according to the present disclosure. The following detailed description includes specific details in order to provide a thorough understanding of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be practiced without such specific details. 
     Although most terms used in the present disclosure have been selected from general ones widely used in the art, some terms have been arbitrarily selected by the applicant and their meanings are explained in detail in the following description as needed. Thus, the present disclosure should be understood based upon the intended meanings of the terms rather than their simple names or meanings. 
       FIG. 1  shows an exemplary point cloud content providing system according to embodiments. 
     The point cloud content providing system illustrated in  FIG. 1  may include a transmission device  10000  and a reception device  10004 . The transmission device  10000  and the reception device  10004  are capable of wired or wireless communication to transmit and receive point cloud data. 
     The point cloud data transmission device  10000  according to the embodiments may secure and process point cloud video (or point cloud content) and transmit the same. According to embodiments, the transmission device  10000  may include 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. According to embodiments, the transmission device  10000  may include a device, a robot, a vehicle, an AR/VR/XR device, a portable device, a home appliance, an Internet of Thing (IoT) device, and an AI device/server which are configured to perform communication with a base station and/or other wireless devices using a radio access technology (e.g., 5G New RAT (NR), Long Term Evolution (LTE)). 
     The transmission device  10000  according to the embodiments includes a point cloud video acquirer  10001 , a point cloud video encoder  10002 , and/or a transmitter (or communication module)  10003 . 
     The point cloud video acquirer  10001  according to the embodiments acquires a point cloud video through a processing process such as capture, synthesis, or generation. The point cloud video is point cloud content represented by a point cloud, which is a set of points positioned in a 3D space, and may be referred to as point cloud video data. The point cloud video according to the embodiments may include one or more frames. One frame represents a still image/picture. Therefore, the point cloud video may include a point cloud image/frame/picture, and may be referred to as a point cloud image, frame, or picture. 
     The point cloud video encoder  10002  according to the embodiments encodes the acquired point cloud video data. The point cloud video encoder  10002  may encode the point cloud video data based on point cloud compression coding. The point cloud compression coding according to the embodiments may include geometry-based point cloud compression (G-PCC) coding and/or video-based point cloud compression (V-PCC) coding or next-generation coding. The point cloud compression coding according to the embodiments is not limited to the above-described embodiment. The point cloud video encoder  10002  may output a bitstream containing the encoded point cloud video data. The bitstream may contain not only the encoded point cloud video data, but also signaling information related to encoding of the point cloud video data. 
     The transmitter  10003  according to the embodiments transmits the bitstream containing the encoded point cloud video data. The bitstream according to the embodiments is encapsulated in a file or segment (for example, a streaming segment), and is transmitted over various networks such as a broadcasting network and/or a broadband network. Although not shown in the figure, the transmission device  10000  may include an encapsulator (or an encapsulation module) configured to perform an encapsulation operation. According to embodiments, the encapsulator may be included in the transmitter  10003 . According to embodiments, the file or segment may be transmitted to the reception device  10004  over a network, or stored in a digital storage medium (e.g., USB, SD, CD, DVD, Blu-ray, HDD, SSD, etc.). The transmitter  10003  according to the embodiments is capable of wired/wireless communication with the reception device  10004  (or the receiver  10005 ) over a network of 4G, 5G, 6G, etc. In addition, the transmitter may perform a necessary data processing operation according to the network system (e.g., a 4G, 5G or 6G communication network system). The transmission device  10000  may transmit the encapsulated data in an on-demand manner. 
     The reception device  10004  according to the embodiments includes a receiver  10005 , a point cloud video decoder  10006 , and/or a renderer  10007 . According to embodiments, the reception device  10004  may include a device, a robot, a vehicle, an AR/VR/XR device, a portable device, a home appliance, an Internet of Things (IoT) device, and an AI device/server which are configured to perform communication with a base station and/or other wireless devices using a radio access technology (e.g., 5G New RAT (NR), Long Term Evolution (LTE)). 
     The receiver  10005  according to the embodiments receives the bitstream containing the point cloud video data or the file/segment in which the bitstream is encapsulated from the network or storage medium. The receiver  10005  may perform necessary data processing according to the network system (for example, a communication network system of 4G, 5G, 6G, etc.). The receiver  10005  according to the embodiments may decapsulate the received file/segment and output a bitstream. According to embodiments, the receiver  10005  may include a decapsulator (or a decapsulation module) configured to perform a decapsulation operation. The decapsulator may be implemented as an element (or component) separate from the receiver  10005 . 
     The point cloud video decoder  10006  decodes the bitstream containing the point cloud video data. The point cloud video decoder  10006  may decode the point cloud video data according to the method by which the point cloud video data is encoded (for example, in a reverse process of the operation of the point cloud video encoder  10002 ). Accordingly, the point cloud video decoder  10006  may decode the point cloud video data by performing point cloud decompression coding, which is the inverse process of the point cloud compression. The point cloud decompression coding includes G-PCC coding. 
     The renderer  10007  renders the decoded point cloud video data. The renderer  10007  may output point cloud content by rendering not only the point cloud video data but also audio data. According to embodiments, the renderer  10007  may include a display configured to display the point cloud content. According to embodiments, the display may be implemented as a separate device or component rather than being included in the renderer  10007 . 
     The arrows indicated by dotted lines in the drawing represent a transmission path of feedback information acquired by the reception device  10004 . The feedback information is information for reflecting interactivity with a user who consumes the point cloud content, and includes information about the user (e.g., head orientation information, viewport information, and the like). In particular, when the point cloud content is content for a service (e.g., self-driving service, etc.) that requires interaction with the user, the feedback information may be provided to the content transmitting side (e.g., the transmission device  10000 ) and/or the service provider. According to embodiments, the feedback information may be used in the reception device  10004  as well as the transmission device  10000 , or may not be provided. 
     The head orientation information according to embodiments is information about the user&#39;s head position, orientation, angle, motion, and the like. The reception device  10004  according to the embodiments may calculate the viewport information based on the head orientation information. The viewport information may be information about a region of a point cloud video that the user is viewing. A viewpoint is a point through which the user is viewing the point cloud video, and may refer to a center point of the viewport region. That is, the viewport is a region centered on the viewpoint, and the size and shape of the region may be determined by a field of view (FOV). Accordingly, the reception device  10004  may extract the viewport information based on a vertical or horizontal FOV supported by the device in addition to the head orientation information. Also, the reception device  10004  performs gaze analysis or the like to check the way the user consumes a point cloud, a region that the user gazes at in the point cloud video, a gaze time, and the like. According to embodiments, the reception device  10004  may transmit feedback information including the result of the gaze analysis to the transmission device  10000 . The feedback information according to the embodiments may be acquired in the rendering and/or display process. The feedback information according to the embodiments may be secured by one or more sensors included in the reception device  10004 . According to embodiments, the feedback information may be secured by the renderer  10007  or a separate external element (or device, component, or the like). The dotted lines in  FIG. 1  represent a process of transmitting the feedback information secured by the renderer  10007 . The point cloud content providing system may process (encode/decode) point cloud data based on the feedback information. Accordingly, the point cloud video data decoder  10006  may perform a decoding operation based on the feedback information. The reception device  10004  may transmit the feedback information to the transmission device  10000 . The transmission device  10000  (or the point cloud video data encoder  10002 ) may perform an encoding operation based on the feedback information. Accordingly, the point cloud content providing system may efficiently process necessary data (e.g., point cloud data corresponding to the user&#39;s head position) based on the feedback information rather than processing (encoding/decoding) the entire point cloud data, and provide point cloud content to the user. 
     According to embodiments, the transmission device  10000  may be called an encoder, a transmission device, a transmitter, or the like, and the reception device  10004  may be called a decoder, a receiving device, a receiver, or the like. 
     The point cloud data processed in the point cloud content providing system of  FIG. 1  according to embodiments (through a series of processes of acquisition/encoding/transmission/decoding/rendering) may be referred to as point cloud content data or point cloud video data. According to embodiments, the point cloud content data may be used as a concept covering metadata or signaling information related to the point cloud data. 
     The elements of the point cloud content providing system illustrated in  FIG. 1  may be implemented by hardware, software, a processor, and/or a combination thereof. 
       FIG. 2  is a block diagram illustrating a point cloud content providing operation according to embodiments. 
     The block diagram of  FIG. 2  shows the operation of the point cloud content providing system described in  FIG. 1 . As described above, the point cloud content providing system may process point cloud data based on point cloud compression coding (e.g., G-PCC). 
     The point cloud content providing system according to the embodiments (for example, the point cloud transmission device  10000  or the point cloud video acquirer  10001 ) may acquire a point cloud video ( 20000 ). The point cloud video is represented by a point cloud belonging to a coordinate system for expressing a 3D space. The point cloud video according to the embodiments may include a Ply (Polygon File format or the Stanford Triangle format) file. When the point cloud video has one or more frames, the acquired point cloud video may include one or more Ply files. The Ply files contain point cloud data, such as point geometry and/or attributes. The geometry includes positions of points. The position of each point may be represented by parameters (for example, values of the X, Y, and Z axes) representing a three-dimensional coordinate system (e.g., a coordinate system composed of X, Y and Z axes). The attributes include attributes of points (e.g., information about texture, color (in YCbCr or RGB), reflectance r, transparency, etc. of each point). A point has one or more attributes. For example, a point may have an attribute that is a color, or two attributes that are color and reflectance. According to embodiments, the geometry may be called positions, geometry information, geometry data, or the like, and the attribute may be called attributes, attribute information, attribute data, or the like. The point cloud content providing system (for example, the point cloud transmission device  10000  or the point cloud video acquirer  10001 ) may secure point cloud data from information (e.g., depth information, color information, etc.) related to the acquisition process of the point cloud video. 
     The point cloud content providing system (for example, the transmission device  10000  or the point cloud video encoder  10002 ) according to the embodiments may encode the point cloud data ( 20001 ). The point cloud content providing system may encode the point cloud data based on point cloud compression coding. As described above, the point cloud data may include the geometry and attributes of a point. Accordingly, the point cloud content providing system may perform geometry encoding of encoding the geometry and output a geometry bitstream. The point cloud content providing system may perform attribute encoding of encoding attributes and output an attribute bitstream. According to embodiments, the point cloud content providing system may perform the attribute encoding based on the geometry encoding. The geometry bitstream and the attribute bitstream according to the embodiments may be multiplexed and output as one bitstream. The bitstream according to the embodiments may further contain signaling information related to the geometry encoding and attribute encoding. 
     The point cloud content providing system (for example, the transmission device  10000  or the transmitter  10003 ) according to the embodiments may transmit the encoded point cloud data ( 20002 ). As illustrated in  FIG. 1 , the encoded point cloud data may be represented by a geometry bitstream and an attribute bitstream. In addition, the encoded point cloud data may be transmitted in the form of a bitstream together with signaling information related to encoding of the point cloud data (for example, signaling information related to the geometry encoding and the attribute encoding). The point cloud content providing system may encapsulate a bitstream that carries the encoded point cloud data and transmit the same in the form of a file or segment. 
     The point cloud content providing system (for example, the reception device  10004  or the receiver  10005 ) according to the embodiments may receive the bitstream containing the encoded point cloud data. In addition, the point cloud content providing system (for example, the reception device  10004  or the receiver  10005 ) may demultiplex the bitstream. 
     The point cloud content providing system (e.g., the reception device  10004  or the point cloud video decoder  10005 ) may decode the encoded point cloud data (e.g., the geometry bitstream, the attribute bitstream) transmitted in the bitstream. The point cloud content providing system (for example, the reception device  10004  or the point cloud video decoder  10005 ) may decode the point cloud video data based on the signaling information related to encoding of the point cloud video data contained in the bitstream. The point cloud content providing system (for example, the reception device  10004  or the point cloud video decoder  10005 ) may decode the geometry bitstream to reconstruct the positions (geometry) of points. The point cloud content providing system may reconstruct the attributes of the points by decoding the attribute bitstream based on the reconstructed geometry. The point cloud content providing system (for example, the reception device  10004  or the point cloud video decoder  10005 ) may reconstruct the point cloud video based on the positions according to the reconstructed geometry and the decoded attributes. 
     The point cloud content providing system according to the embodiments (for example, the reception device  10004  or the renderer  10007 ) may render the decoded point cloud data ( 20004 ). The point cloud content providing system (for example, the reception device  10004  or the renderer  10007 ) may render the geometry and attributes decoded through the decoding process, using various rendering methods. Points in the point cloud content may be rendered to a vertex having a certain thickness, a cube having a specific minimum size centered on the corresponding vertex position, or a circle centered on the corresponding vertex position. All or part of the rendered point cloud content is provided to the user through a display (e.g., a VR/AR display, a general display, etc.). 
     The point cloud content providing system (for example, the reception device  10004 ) according to the embodiments may secure feedback information ( 20005 ). The point cloud content providing system may encode and/or decode point cloud data based on the feedback information. The feedback information and the operation of the point cloud content providing system according to the embodiments are the same as the feedback information and the operation described with reference to  FIG. 1 , and thus detailed description thereof is omitted. 
       FIG. 3  illustrates an exemplary process of capturing a point cloud video according to embodiments. 
       FIG. 3  illustrates an exemplary point cloud video capture process of the point cloud content providing system described with reference to  FIGS. 1 to 2 . 
     Point cloud content includes a point cloud video (images and/or videos) representing an object and/or environment located in various 3D spaces (e.g., a 3D space representing a real environment, a 3D space representing a virtual environment, etc.). Accordingly, the point cloud content providing system according to the embodiments may capture a point cloud video using one or more cameras (e.g., an infrared camera capable of securing depth information, an RGB camera capable of extracting color information corresponding to the depth information, etc.), a projector (e.g., an infrared pattern projector to secure depth information), a LiDAR, or the like. The point cloud content providing system according to the embodiments may extract the shape of geometry composed of points in a 3D space from the depth information and extract the attributes of each point from the color information to secure point cloud data. An image and/or video according to the embodiments may be captured based on at least one of the inward-facing technique and the outward-facing technique. 
     The left part of  FIG. 3  illustrates the inward-facing technique. The inward-facing technique refers to a technique of capturing images a central object with one or more cameras (or camera sensors) positioned around the central object. The inward-facing technique may be used to generate point cloud content providing a 360-degree image of a key object to the user (e.g., VR/AR content providing a 360-degree image of an object (e.g., a key object such as a character, player, object, or actor) to the user). 
     The right part of  FIG. 3  illustrates the outward-facing technique. The outward-facing technique refers to a technique of capturing images an environment of a central object rather than the central object with one or more cameras (or camera sensors) positioned around the central object. The outward-facing technique may be used to generate point cloud content for providing a surrounding environment that appears from the user&#39;s point of view (e.g., content representing an external environment that may be provided to a user of a self-driving vehicle). 
     As shown in the figure, the point cloud content may be generated based on the capturing operation of one or more cameras. In this case, the coordinate system may differ among the cameras, and accordingly the point cloud content providing system may calibrate one or more cameras to set a global coordinate system before the capturing operation. In addition, the point cloud content providing system may generate point cloud content by synthesizing an arbitrary image and/or video with an image and/or video captured by the above-described capture technique. The point cloud content providing system may not perform the capturing operation described in  FIG. 3  when it generates point cloud content representing a virtual space. The point cloud content providing system according to the embodiments may perform post-processing on the captured image and/or video. In other words, the point cloud content providing system may remove an unwanted area (for example, a background), recognize a space to which the captured images and/or videos are connected, and, when there is a spatial hole, perform an operation of filling the spatial hole. 
     The point cloud content providing system may generate one piece of point cloud content by performing coordinate transformation on points of the point cloud video secured from each camera. The point cloud content providing system may perform coordinate transformation on the points based on the coordinates of the position of each camera. Accordingly, the point cloud content providing system may generate content representing one wide range, or may generate point cloud content having a high density of points. 
       FIG. 4  illustrates an exemplary point cloud encoder according to embodiments. 
       FIG. 4  shows an example of the point cloud video encoder  10002  of  FIG. 1 . The point cloud encoder reconstructs and encodes point cloud data (e.g., positions and/or attributes of the points) to adjust the quality of the point cloud content (to, for example, lossless, lossy, or near-lossless) according to the network condition or applications. When the overall size of the point cloud content is large (e.g., point cloud content of 60 Gbps is given for 30 fps), the point cloud content providing system may fail to stream the content in real time. Accordingly, the point cloud content providing system may reconstruct the point cloud content based on the maximum target bitrate to provide the same in accordance with the network environment or the like. 
     As described with reference to  FIGS. 1 to 2 , the point cloud encoder may perform geometry encoding and attribute encoding. The geometry encoding is performed before the attribute encoding. 
     The point cloud encoder according to the embodiments includes a coordinate transformer (Transform coordinates)  40000 , a quantizer (Quantize and remove points (voxelize))  40001 , an octree analyzer (Analyze octree)  40002 , and a surface approximation analyzer (Analyze surface approximation)  40003 , an arithmetic encoder (Arithmetic encode)  40004 , a geometric reconstructor (Reconstruct geometry)  40005 , a color transformer (Transform colors)  40006 , an attribute transformer (Transform attributes)  40007 , a RAHT transformer (RAHT)  40008 , an LOD generator (Generate LOD)  40009 , a lifting transformer (Lifting)  40010 , a coefficient quantizer (Quantize coefficients)  40011 , and/or an arithmetic encoder (Arithmetic encode)  40012 . 
     The coordinate transformer  40000 , the quantizer  40001 , the octree analyzer  40002 , the surface approximation analyzer  40003 , the arithmetic encoder  40004 , and the geometry reconstructor  40005  may perform geometry encoding. The geometry encoding according to the embodiments may include octree geometry coding, direct coding, trisoup geometry encoding, and entropy encoding. The direct coding and trisoup geometry encoding are applied selectively or in combination. The geometry encoding is not limited to the above-described example. 
     As shown in the figure, the coordinate transformer  40000  according to the embodiments receives positions and transforms the same into coordinates. For example, the positions may be transformed into position information in a three-dimensional space (for example, a three-dimensional space represented by an XYZ coordinate system). The position information in the three-dimensional space according to the embodiments may be referred to as geometry information. 
     The quantizer  40001  according to the embodiments quantizes the geometry. For example, the quantizer  40001  may quantize the points based on a minimum position value of all points (for example, a minimum value on each of the X, Y, and Z axes). The quantizer  40001  performs a quantization operation of multiplying the difference between the minimum position value and the position value of each point by a preset quantization scale value and then finding the nearest integer value by rounding the value obtained through the multiplication. Thus, one or more points may have the same quantized position (or position value). The quantizer  40001  according to the embodiments performs voxelization based on the quantized positions to reconstruct quantized points. As in the case of a pixel, which is the minimum unit containing 2D image/video information, points of point cloud content (or 3D point cloud video) according to the embodiments may be included in one or more voxels. The term voxel, which is a compound of volume and pixel, refers to a 3D cubic space generated when a 3D space is divided into units (unit=1.0) based on the axes representing the 3D space (e.g., X-axis, Y-axis, and Z-axis). The quantizer  40001  may match groups of points in the 3D space with voxels. According to embodiments, one voxel may include only one point. According to embodiments, one voxel may include one or more points. In order to express one voxel as one point, the position of the center of a voxel may be set based on the positions of one or more points included in the voxel. In this case, attributes of all positions included in one voxel may be combined and assigned to the voxel. 
     The octree analyzer  40002  according to the embodiments performs octree geometry coding (or octree coding) to present voxels in an octree structure. The octree structure represents points matched with voxels, based on the octal tree structure. 
     The surface approximation analyzer  40003  according to the embodiments may analyze and approximate the octree. The octree analysis and approximation according to the embodiments is a process of analyzing a region containing a plurality of points to efficiently provide octree and voxelization. 
     The arithmetic encoder  40004  according to the embodiments performs entropy encoding on the octree and/or the approximated octree. For example, the encoding scheme includes arithmetic encoding. As a result of the encoding, a geometry bitstream is generated. 
     The color transformer  40006 , the attribute transformer  40007 , the RAHT transformer  40008 , the LOD generator  40009 , the lifting transformer  40010 , the coefficient quantizer  40011 , and/or the arithmetic encoder  40012  perform attribute encoding. As described above, one point may have one or more attributes. The attribute encoding according to the embodiments is equally applied to the attributes that one point has. However, when an attribute (e.g., color) includes one or more elements, attribute encoding is independently applied to each element. The attribute encoding according to the embodiments includes color transform coding, attribute transform coding, region adaptive hierarchical transform (RAHT) coding, interpolation-based hierarchical nearest-neighbor prediction (prediction transform) coding, and interpolation-based hierarchical nearest-neighbor prediction with an update/lifting step (lifting transform) coding. Depending on the point cloud content, the RAHT coding, the prediction transform coding and the lifting transform coding described above may be selectively used, or a combination of one or more of the coding schemes may be used. The attribute encoding according to the embodiments is not limited to the above-described example. 
     The color transformer  40006  according to the embodiments performs color transform coding of transforming color values (or textures) included in the attributes. For example, the color transformer  40006  may transform the format of color information (for example, from RGB to YCbCr). The operation of the color transformer  40006  according to embodiments may be optionally applied according to the color values included in the attributes. 
     The geometry reconstructor  40005  according to the embodiments reconstructs (decompresses) the octree and/or the approximated octree. The geometry reconstructor  40005  reconstructs the octree/voxels based on the result of analyzing the distribution of points. The reconstructed octree/voxels may be referred to as reconstructed geometry (restored geometry). 
     The attribute transformer  40007  according to the embodiments performs attribute transformation to transform the attributes based on the reconstructed geometry and/or the positions on which geometry encoding is not performed. As described above, since the attributes are dependent on the geometry, the attribute transformer  40007  may transform the attributes based on the reconstructed geometry information. For example, based on the position value of a point included in a voxel, the attribute transformer  40007  may transform the attribute of the point at the position. As described above, when the position of the center of a voxel is set based on the positions of one or more points included in the voxel, the attribute transformer  40007  transforms the attributes of the one or more points. When the trisoup geometry encoding is performed, the attribute transformer  40007  may transform the attributes based on the trisoup geometry encoding. 
     The attribute transformer  40007  may perform the attribute transformation by calculating the average of attributes or attribute values of neighboring points (e.g., color or reflectance of each point) within a specific position/radius from the position (or position value) of the center of each voxel. The attribute transformer  40007  may apply a weight according to the distance from the center to each point in calculating the average. Accordingly, each voxel has a position and a calculated attribute (or attribute value). 
     The attribute transformer  40007  may search for neighboring points existing within a specific position/radius from the position of the center of each voxel based on the K-D tree or the Morton code. The K-D tree is a binary search tree and supports a data structure capable of managing points based on the positions such that nearest neighbor search (NNS) can be performed quickly. The Morton code is generated by presenting coordinates (e.g., (x, y, z)) representing 3D positions of all points as bit values and mixing the bits. For example, when the coordinates representing the position of a point are (5, 9, 1), the bit values for the coordinates are (0101, 1001, 0001). Mixing the bit values according to the bit index in order of z, y, and x yields 010001000111. This value is expressed as a decimal number of 1095. That is, the Morton code value of the point having coordinates (5, 9, 1) is 1095. The attribute transformer  40007  may order the points based on the Morton code values and perform NNS through a depth-first traversal process. After the attribute transformation operation, the K-D tree or the Morton code is used when the NNS is needed in another transformation process for attribute coding. 
     As shown in the figure, the transformed attributes are input to the RAHT transformer  40008  and/or the LOD generator  40009 . 
     The RAHT transformer  40008  according to the embodiments performs RAHT coding for predicting attribute information based on the reconstructed geometry information. For example, the RAHT transformer  40008  may predict attribute information of a node at a higher level in the octree based on the attribute information associated with a node at a lower level in the octree. 
     The LOD generator  40009  according to the embodiments generates a level of detail (LOD) to perform prediction transform coding. The LOD according to the embodiments is a degree of detail of point cloud content. As the LOD value decrease, it indicates that the detail of the point cloud content is degraded. As the LOD value increases, it indicates that the detail of the point cloud content is enhanced. Points may be classified by the LOD. 
     The lifting transformer  40010  according to the embodiments performs lifting transform coding of transforming the attributes a point cloud based on weights. As described above, lifting transform coding may be optionally applied. 
     The coefficient quantizer  40011  according to the embodiments quantizes the attribute-coded attributes based on coefficients. 
     The arithmetic encoder  40012  according to the embodiments encodes the quantized attributes based on arithmetic coding. 
     Although not shown in the figure, the elements of the point cloud encoder of  FIG. 4  may be implemented by hardware including one or more processors or integrated circuits configured to communicate with one or more memories included in the point cloud providing device, software, firmware, or a combination thereof. The one or more processors may perform at least one of the operations and/or functions of the elements of the point cloud encoder of  FIG. 4  described above. Additionally, the one or more processors may operate or execute a set of software programs and/or instructions for performing the operations and/or functions of the elements of the point cloud encoder of  FIG. 4 . The one or more memories according to the embodiments may include a high speed random access memory, or include a non-volatile memory (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices). 
       FIG. 5  shows an example of voxels according to embodiments. 
       FIG. 5  shows voxels positioned in a 3D space represented by a coordinate system composed of three axes, which are the X-axis, the Y-axis, and the Z-axis. As described with reference to  FIG. 4 , the point cloud encoder (e.g., the quantizer  40001 ) may perform voxelization. Voxel refers to a 3D cubic space generated when a 3D space is divided into units (unit=1.0) based on the axes representing the 3D space (e.g., X-axis, Y-axis, and Z-axis).  FIG. 5  shows an example of voxels generated through an octree structure in which a cubical axis-aligned bounding box defined by two poles (0, 0, 0) and (2d, 2d, 2d) is recursively subdivided. One voxel includes at least one point. The spatial coordinates of a voxel may be estimated from the positional relationship with a voxel group. As described above, a voxel has an attribute (such as color or reflectance) like pixels of a 2D image/video. The details of the voxel are the same as those described with reference to  FIG. 4 , and therefore a description thereof is omitted. 
       FIG. 6  shows an example of an octree and occupancy code according to embodiments. 
     As described with reference to  FIGS. 1 to 4 , the point cloud content providing system (point cloud video encoder  10002 ) or the point cloud encoder (for example, the octree analyzer  40002 ) performs octree geometry coding (or octree coding) based on an octree structure to efficiently manage the region and/or position of the voxel. 
     The upper part of  FIG. 6  shows an octree structure. The 3D space of the point cloud content according to the embodiments is represented by axes (e.g., X-axis, Y-axis, and Z-axis) of the coordinate system. The octree structure is created by recursive subdividing of a cubical axis-aligned bounding box defined by two poles (0, 0, 0) and (2 d , 2 d , 2 d ). Here, 2 d  may be set to a value constituting the smallest bounding box surrounding all points of the point cloud content (or point cloud video). Here, d denotes the depth of the octree. The value of d is determined in the following equation. In the following equation, (x int   n , y int   n , z int   n ) denotes the positions (or position values) of quantized points. 
         d =Ceil(Log 2(Max( x   n   int   ,y   n   int   ,z   n   int   ,n= 1, . . . ,  N )+1)) 
     As shown in the middle of the upper part of  FIG. 6 , the entire 3D space may be divided into eight spaces according to partition. Each divided space is represented by a cube with six faces. As shown in the upper right of  FIG. 6 , each of the eight spaces is divided again based on the axes of the coordinate system (e.g., X-axis, Y-axis, and Z-axis). Accordingly, each space is divided into eight smaller spaces. The divided smaller space is also represented by a cube with six faces. This partitioning scheme is applied until the leaf node of the octree becomes a voxel. 
     The lower part of  FIG. 6  shows an octree occupancy code. The occupancy code of the octree is generated to indicate whether each of the eight divided spaces generated by dividing one space contains at least one point. Accordingly, a single occupancy code is represented by eight child nodes. Each child node represents the occupancy of a divided space, and the child node has a value in 1 bit. Accordingly, the occupancy code is represented as an 8-bit code. That is, when at least one point is contained in the space corresponding to a child node, the node is assigned a value of 1. When no point is contained in the space corresponding to the child node (the space is empty), the node is assigned a value of 0. Since the occupancy code shown in  FIG. 6  is 00100001, it indicates that the spaces corresponding to the third child node and the eighth child node among the eight child nodes each contain at least one point. As shown in the figure, each of the third child node and the eighth child node has eight child nodes, and the child nodes are represented by an 8-bit occupancy code. The figure shows that the occupancy code of the third child node is 10000111, and the occupancy code of the eighth child node is 01001111. The point cloud encoder (for example, the arithmetic encoder  40004 ) according to the embodiments may perform entropy encoding on the occupancy codes. In order to increase the compression efficiency, the point cloud encoder may perform intra/inter-coding on the occupancy codes. The reception device (for example, the reception device  10004  or the point cloud video decoder  10006 ) according to the embodiments reconstructs the octree based on the occupancy codes. 
     The point cloud encoder (for example, the point cloud encoder of  FIG. 4  or the octree analyzer  40002 ) according to the embodiments may perform voxelization and octree coding to store the positions of points. However, points are not always evenly distributed in the 3D space, and accordingly there may be a specific region in which fewer points are present. Accordingly, it is inefficient to perform voxelization for the entire 3D space. For example, when a specific region contains few points, voxelization does not need to be performed in the specific region. 
     Accordingly, for the above-described specific region (or a node other than the leaf node of the octree), the point cloud encoder according to the embodiments may skip voxelization and perform direct coding to directly code the positions of points included in the specific region. The coordinates of a direct coding point according to the embodiments are referred to as direct coding mode (DCM). The point cloud encoder according to the embodiments may also perform trisoup geometry encoding, which is to reconstruct the positions of the points in the specific region (or node) based on voxels, based on a surface model. The trisoup geometry encoding is geometry encoding that represents an object as a series of triangular meshes. Accordingly, the point cloud decoder may generate a point cloud from the mesh surface. The direct coding and trisoup geometry encoding according to the embodiments may be selectively performed. In addition, the direct coding and trisoup geometry encoding according to the embodiments may be performed in combination with octree geometry coding (or octree coding). 
     To perform direct coding, the option to use the direct mode for applying direct coding should be activated. A node to which direct coding is to be applied is not a leaf node, and points less than a threshold should be present within a specific node. In addition, the total number of points to which direct coding is to be applied should not exceed a preset threshold. When the conditions above are satisfied, the point cloud encoder (or the arithmetic encoder  40004 ) according to the embodiments may perform entropy coding on the positions (or position values) of the points. 
     The point cloud encoder (for example, the surface approximation analyzer  40003 ) according to the embodiments may determine a specific level of the octree (a level less than the depth d of the octree), and the surface model may be used staring with that level to perform trisoup geometry encoding to reconstruct the positions of points in the region of the node based on voxels (Trisoup mode). The point cloud encoder according to the embodiments may specify a level at which trisoup geometry encoding is to be applied. For example, when the specific level is equal to the depth of the octree, the point cloud encoder does not operate in the trisoup mode. In other words, the point cloud encoder according to the embodiments may operate in the trisoup mode only when the specified level is less than the value of depth of the octree. The 3D cube region of the nodes at the specified level according to the embodiments is called a block. One block may include one or more voxels. The block or voxel may correspond to a brick. Geometry is represented as a surface within each block. The surface according to embodiments may intersect with each edge of a block at most once. 
     One block has 12 edges, and accordingly there are at least 12 intersections in one block. Each intersection is called a vertex (or apex). A vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge. The occupied voxel according to the embodiments refers to a voxel containing a point. The position of the vertex detected along the edge is the average position along the edge of all voxels adjacent to the edge among all blocks sharing the edge. 
     Once the vertex is detected, the point cloud encoder according to the embodiments may perform entropy encoding on the starting point (x, y, z) of the edge, the direction vector (Δx, Δy, Δz) of the edge, and the vertex position value (relative position value within the edge). When the trisoup geometry encoding is applied, the point cloud encoder according to the embodiments (for example, the geometry reconstructor  40005 ) may generate restored geometry (reconstructed geometry) by performing the triangle reconstruction, up-sampling, and voxelization processes. 
     The vertices positioned at the edge of the block determine a surface that passes through the block. The surface according to the embodiments is a non-planar polygon. In the triangle reconstruction process, a surface represented by a triangle is reconstructed based on the starting point of the edge, the direction vector of the edge, and the position values of the vertices. The triangle reconstruction process is performed by: i) calculating the centroid value of each vertex, ii) subtracting the center value from each vertex value, and iii) estimating the sum of the squares of the values obtained by the subtraction. 
     
       
         
           
             
               
                 
                   
                     
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     The minimum value of the sum is estimated, and the projection process is performed according to the axis with the minimum value. For example, when the element x is the minimum, each vertex is projected on the x-axis with respect to the center of the block, and projected on the (y, z) plane. When the values obtained through projection on the (y, z) plane are (ai, bi), the value of θ is estimated through atan 2(bi, ai), and the vertices are ordered based on the value of θ. The table below shows a combination of vertices for creating a triangle according to the number of the vertices. The vertices are ordered from 1 to n. The table below shows that for four vertices, two triangles may be constructed according to combinations of vertices. The first triangle may consist of vertices  1 ,  2 , and  3  among the ordered vertices, and the second triangle may consist of vertices  3 ,  4 , and  1  among the ordered vertices. 
     
       
         
           
               
             
               
                 TABLE 2-1 
               
             
            
               
                   
               
               
                 Triangles formed from vertices ordered 1, . . . , n 
               
            
           
           
               
               
            
               
                 n 
                 triangles 
               
               
                   
               
            
           
           
               
               
            
               
                 3 
                 (1, 2, 3) 
               
               
                 4 
                 (1, 2, 3), (3, 4, 1) 
               
               
                 5 
                 (1, 2, 3), (3, 4, 5), (5, 1, 3) 
               
               
                 6 
                 (1, 2, 3), (3, 4, 5), (5, 6, 1), (1, 3, 5) 
               
               
                 7 
                 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 1, 3), (3, 5, 7) 
               
               
                 8 
                 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 1), (1, 3, 5), (5, 7, 1) 
               
               
                 9 
                 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 9), (9, 1, 3), (3, 5, 7),  
               
               
                   
                 (7, 9, 3) 
               
               
                 10 
                 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 9), (9, 10, 1), (1, 3, 5),  
               
               
                   
                 (5, 7, 9), (9, 1, 5) 
               
               
                 11 
                 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 9), (9, 10, 11), (11, 1, 3),  
               
               
                   
                 (3, 5, 7), (7, 9, 11), (11, 3, 7) 
               
               
                 12 
                 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 9), (9, 10, 11), (11, 12, 1),  
               
               
                   
                 (1, 3, 5), (5, 7, 9), (9, 11, 1), (1, 5, 9) 
               
               
                   
               
            
           
         
       
     
     The upsampling process is performed to add points in the middle along the edge of the triangle and perform voxelization. The added points are generated based on the upsampling factor and the width of the block. The added points are called refined vertices. The point cloud encoder according to the embodiments may voxelize the refined vertices. In addition, the point cloud encoder may perform attribute encoding based on the voxelized positions (or position values). 
       FIG. 7  shows an example of a neighbor node pattern according to embodiments. 
     In order to increase the compression efficiency of the point cloud video, the point cloud encoder according to the embodiments may perform entropy coding based on context adaptive arithmetic coding. 
     As described with reference to  FIGS. 1 to 6 , the point cloud content providing system or the point cloud encoder (for example, the point cloud video encoder  10002 , the point cloud encoder or arithmetic encoder  40004  of  FIG. 4 ) may perform entropy coding on the occupancy code immediately. In addition, the point cloud content providing system or the point cloud encoder may perform entropy encoding (intra encoding) based on the occupancy code of the current node and the occupancy of neighboring nodes, or perform entropy encoding (inter encoding) based on the occupancy code of the previous frame. A frame according to embodiments represents a set of point cloud videos generated at the same time. The compression efficiency of intra encoding/inter encoding according to the embodiments may depend on the number of neighboring nodes that are referenced. When the bits increase, the operation becomes complicated, but the encoding may be biased to one side, which may increase the compression efficiency. For example, when a 3-bit context is given, coding needs to be performed using 23=8 methods. The part divided for coding affects the complexity of implementation. Accordingly, it is necessary to meet an appropriate level of compression efficiency and complexity. 
       FIG. 7  illustrates a process of obtaining an occupancy pattern based on the occupancy of neighbor nodes. The point cloud encoder according to the embodiments determines occupancy of neighbor nodes of each node of the octree and obtains a value of a neighbor pattern. The neighbor node pattern is used to infer the occupancy pattern of the node. The left part of  FIG. 7  shows a cube corresponding to a node (a cube positioned in the middle) and six cubes (neighbor nodes) sharing at least one face with the cube. The nodes shown in the figure are nodes of the same depth. The numbers shown in the figure represent weights (1, 2, 4, 8, 16, and 32) associated with the six nodes, respectively. The weights are assigned sequentially according to the positions of neighboring nodes. 
     The right part of  FIG. 7  shows neighbor node pattern values. A neighbor node pattern value is the sum of values multiplied by the weight of an occupied neighbor node (a neighbor node having a point). Accordingly, the neighbor node pattern values are 0 to 63. When the neighbor node pattern value is 0, it indicates that there is no node having a point (no occupied node) among the neighbor nodes of the node. When the neighbor node pattern value is 63, it indicates that all neighbor nodes are occupied nodes. As shown in the figure, since neighbor nodes to which weights 1, 2, 4, and 8 are assigned are occupied nodes, the neighbor node pattern value is 15, the sum of 1, 2, 4, and 8. The point cloud encoder may perform coding according to the neighbor node pattern value (for example, when the neighbor node pattern value is 63, 64 kinds of coding may be performed). According to embodiments, the point cloud encoder may reduce coding complexity by changing a neighbor node pattern value (for example, based on a table by which 64 is changed to 10 or 6). 
       FIG. 8  illustrates an example of point configuration in each LOD according to embodiments. 
     As described with reference to  FIGS. 1 to 7 , encoded geometry is reconstructed (decompressed) before attribute encoding is performed. When direct coding is applied, the geometry reconstruction operation may include changing the placement of direct coded points (e.g., placing the direct coded points in front of the point cloud data). When trisoup geometry encoding is applied, the geometry reconstruction process is performed through triangle reconstruction, up-sampling, and voxelization. Since the attribute depends on the geometry, attribute encoding is performed based on the reconstructed geometry. 
     The point cloud encoder (for example, the LOD generator  40009 ) may classify (reorganize) points by LOD. The figure shows the point cloud content corresponding to LODs. The leftmost picture in the figure represents original point cloud content. The second picture from the left of the figure represents distribution of the points in the lowest LOD, and the rightmost picture in the figure represents distribution of the points in the highest LOD. That is, the points in the lowest LOD are sparsely distributed, and the points in the highest LOD are densely distributed. That is, as the LOD rises in the direction pointed by the arrow indicated at the bottom of the figure, the space (or distance) between points is narrowed. 
       FIG. 9  illustrates an example of point configuration for each LOD according to embodiments. 
     As described with reference to  FIGS. 1 to 8 , the point cloud content providing system, or the point cloud encoder (for example, the point cloud video encoder  10002 , the point cloud encoder of  FIG. 4 , or the LOD generator  40009 ) may generates an LOD. The LOD is generated by reorganizing the points into a set of refinement levels according to a set LOD distance value (or a set of Euclidean distances). The LOD generation process is performed not only by the point cloud encoder, but also by the point cloud decoder. 
     The upper part of  FIG. 9  shows examples (P 0  to P 9 ) of points of the point cloud content distributed in a 3D space. In  FIG. 9 , the original order represents the order of points P 0  to P 9  before LOD generation. In  FIG. 9 , the LOD based order represents the order of points according to the LOD generation. Points are reorganized by LOD. Also, a high LOD contains the points belonging to lower LODs. As shown in  FIG. 9 , LOD 0  contains P 0 , P 5 , P 4  and P 2 . LOD 1  contains the points of LOD 0 , P 1 , P 6  and P 3 . LOD 2  contains the points of LOD 0 , the points of LOD 1 , P 9 , P 8  and P 7 . 
     As described with reference to  FIG. 4 , the point cloud encoder according to the embodiments may perform prediction transform coding, lifting transform coding, and RAHT transform coding selectively or in combination. 
     The point cloud encoder according to the embodiments may generate a predictor for points to perform prediction transform coding for setting a predicted attribute (or predicted attribute value) of each point. That is, N predictors may be generated for N points. The predictor according to the embodiments may calculate a weight (=1/distance) based on the LOD value of each point, indexing information about neighboring points present within a set distance for each LOD, and a distance to the neighboring points. 
     The predicted attribute (or attribute value) according to the embodiments is set to the average of values obtained by multiplying the attributes (or attribute values) (e.g., color, reflectance, etc.) of neighbor points set in the predictor of each point by a weight (or weight value) calculated based on the distance to each neighbor point. The point cloud encoder according to the embodiments (for example, the coefficient quantizer  40011 ) may quantize and inversely quantize the residuals (which may be called residual attributes, residual attribute values, or attribute prediction residuals) obtained by subtracting a predicted attribute (attribute value) from the attribute (attribute value) of each point. The quantization process is configured as shown in the following table. 
     
       
         
           
               
             
               
                 TABLE 
               
               
                   
               
               
                 Attribute prediction residuals quantization pseudo code 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
               
            
               
                   
                   
                 int PCCQuantization(int value, int quantStep) { 
               
               
                   
                   
                  if( value &gt;=0) { 
               
               
                   
                   
                   return floor(value / quantStep + 1.0 / 3.0); 
               
               
                   
                   
                  } else { 
               
               
                   
                   
                   return −floor(−value / quantStep + 1.0 / 3.0); 
               
               
                   
                   
                  } 
               
               
                   
                   
                 } 
               
               
                   
                   
                 int PCCInverseQuantization(int value, int quantStep) { 
               
               
                   
                   
                  if( quantStep ==0) { 
               
               
                   
                   
                   return value; 
               
               
                   
                   
                  } else { 
               
               
                   
                   
                   return value * quantStep; 
               
               
                   
                   
                  } 
               
               
                   
                   
                 } 
               
               
                   
                   
               
            
           
         
       
     
     When the predictor of each point has neighbor points, the point cloud encoder (e.g., the arithmetic encoder  40012 ) according to the embodiments may perform entropy coding on the quantized and inversely quantized residual values as described above. When the predictor of each point has no neighbor point, the point cloud encoder according to the embodiments (for example, the arithmetic encoder  40012 ) may perform entropy coding on the attributes of the corresponding point without performing the above-described operation. 
     The point cloud encoder according to the embodiments (for example, the lifting transformer  40010 ) may generate a predictor of each point, set the calculated LOD and register neighbor points in the predictor, and set weights according to the distances to neighbor points to perform lifting transform coding. The lifting transform coding according to the embodiments is similar to the above-described prediction transform coding, but differs therefrom in that weights are cumulatively applied to attribute values. The process of cumulatively applying weights to the attribute values according to embodiments is configured as follows. 
     1) Create an array Quantization Weight (QW) for storing the weight value of each point. The initial value of all elements of QW is 1.0. Multiply the QW values of the predictor indexes of the neighbor nodes registered in the predictor by the weight of the predictor of the current point, and add the values obtained by the multiplication. 
     2) Lift prediction process: Subtract the value obtained by multiplying the attribute value of the point by the weight from the existing attribute value to calculate a predicted attribute value. 
     3) Create temporary arrays called updateweight and update and initialize the temporary arrays to zero. 
     4) Cumulatively add the weights calculated by multiplying the weights calculated for all predictors by a weight stored in the QW corresponding to a predictor index to the updateweight array as indexes of neighbor nodes. Cumulatively add, to the update array, a value obtained by multiplying the attribute value of the index of a neighbor node by the calculated weight. 
     5) Lift update process: Divide the attribute values of the update array for all predictors by the weight value of the updateweight array of the predictor index, and add the existing attribute value to the values obtained by the division. 
     6) Calculate predicted attributes by multiplying the attribute values updated through the lift update process by the weight updated through the lift prediction process (stored in the QW) for all predictors. The point cloud encoder (e.g., coefficient quantizer  40011 ) according to the embodiments quantizes the predicted attribute values. In addition, the point cloud encoder (e.g., the arithmetic encoder  40012 ) performs entropy coding on the quantized attribute values. 
     The point cloud encoder (for example, the RAHT transformer  40008 ) according to the embodiments may perform RAHT transform coding in which attributes of nodes of a higher level are predicted using the attributes associated with nodes of a lower level in the octree. RAHT transform coding is an example of attribute intra coding through an octree backward scan. The point cloud encoder according to the embodiments scans the entire region from the voxel and repeats the merging process of merging the voxels into a larger block at each step until the root node is reached. The merging process according to the embodiments is performed only on the occupied nodes. The merging process is not performed on the empty node. The merging process is performed on an upper node immediately above the empty node. 
     The equation below represents a RAHT transformation matrix. In the equation, g l     x,y,z    denotes the average attribute value of voxels at level l. g l     x,y,z    may be calculated based on g l+1     2x,y,z    and g l+1     2x+1,y,z   . The weights for g l     2x,y,z    and g l     2x+1,y,z    are w 1 =w l     2x,y,z    and w 2 =w l     2x+1,y,z   . 
     
       
         
           
             
               
                 ⌈ 
                 
                   
                     
                       
                         g 
                         
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     Here, g l−1     x,y,z    is a low-pass value and is used in the merging process at the next higher level. h l−1     x,y,z    denotes high-pass coefficients. The high-pass coefficients at each step are quantized and subjected to entropy coding (for example, encoding by the arithmetic encoder  400012 ). The weights are calculated as w l     −1x,y,z   =w l     2x,y,z   +w l     2x+1,y,z   . The root node is created through the g 1     0,0,0    and g 1     0,0,1    as follows. 
     
       
         
           
             
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     The value of gDC is also quantized and subjected to entropy coding like the high-pass coefficients. 
       FIG. 10  illustrates a point cloud decoder according to embodiments. 
     The point cloud decoder illustrated in  FIG. 10  is an example of the point cloud video decoder  10006  described in  FIG. 1 , and may perform the same or similar operations as the operations of the point cloud video decoder  10006  illustrated in  FIG. 1 . As shown in the figure, the point cloud decoder may receive a geometry bitstream and an attribute bitstream contained in one or more bitstreams. The point cloud decoder includes a geometry decoder and an attribute decoder. The geometry decoder performs geometry decoding on the geometry bitstream and outputs decoded geometry. The attribute decoder performs attribute decoding based on the decoded geometry and the attribute bitstream, and outputs decoded attributes. The decoded geometry and decoded attributes are used to reconstruct point cloud content (a decoded point cloud). 
       FIG. 11  illustrates a point cloud decoder according to embodiments. 
     The point cloud decoder illustrated in  FIG. 11  is an example of the point cloud decoder illustrated in  FIG. 10 , and may perform a decoding operation, which is an inverse process of the encoding operation of the point cloud encoder illustrated in  FIGS. 1 to 9 . 
     As described with reference to  FIGS. 1 and 10 , the point cloud decoder may perform geometry decoding and attribute decoding. The geometry decoding is performed before the attribute decoding. 
     The point cloud decoder according to the embodiments includes an arithmetic decoder (Arithmetic decode)  11000 , an octree synthesizer (Synthesize octree)  11001 , a surface approximation synthesizer (Synthesize surface approximation)  11002 , and a geometry reconstructor (Reconstruct geometry)  11003 , a coordinate inverse transformer (Inverse transform coordinates)  11004 , an arithmetic decoder (Arithmetic decode)  11005 , an inverse quantizer (Inverse quantize)  11006 , a RAHT transformer  11007 , an LOD generator (Generate LOD)  11008 , an inverse lifter (inverse lifting)  11009 , and/or a color inverse transformer (Inverse transform colors)  11010 . 
     The arithmetic decoder  11000 , the octree synthesizer  11001 , the surface approximation synthesizer  11002 , and the geometry reconstructor  11003 , and the coordinate inverse transformer  11004  may perform geometry decoding. The geometry decoding according to the embodiments may include direct coding and trisoup geometry decoding. The direct coding and trisoup geometry decoding are selectively applied. The geometry decoding is not limited to the above-described example, and is performed as an inverse process of the geometry encoding described with reference to  FIGS. 1 to 9 . 
     The arithmetic decoder  11000  according to the embodiments decodes the received geometry bitstream based on the arithmetic coding. The operation of the arithmetic decoder  11000  corresponds to the inverse process of the arithmetic encoder  40004 . 
     The octree synthesizer  11001  according to the embodiments may generate an octree by acquiring an occupancy code from the decoded geometry bitstream (or information on the geometry secured as a result of decoding). The occupancy code is configured as described in detail with reference to  FIGS. 1 to 9 . 
     When the trisoup geometry encoding is applied, the surface approximation synthesizer  11002  according to the embodiments may synthesize a surface based on the decoded geometry and/or the generated octree. 
     The geometry reconstructor  11003  according to the embodiments may regenerate geometry based on the surface and/or the decoded geometry. As described with reference to  FIGS. 1 to 9 , direct coding and trisoup geometry encoding are selectively applied. Accordingly, the geometry reconstructor  11003  directly imports and adds position information about the points to which direct coding is applied. When the trisoup geometry encoding is applied, the geometry reconstructor  11003  may reconstruct the geometry by performing the reconstruction operations of the geometry reconstructor  40005 , for example, triangle reconstruction, up-sampling, and voxelization. Details are the same as those described with reference to  FIG. 6 , and thus description thereof is omitted. The reconstructed geometry may include a point cloud picture or frame that does not contain attributes. 
     The coordinate inverse transformer  11004  according to the embodiments may acquire positions of the points by transforming the coordinates based on the reconstructed geometry. 
     The arithmetic decoder  11005 , the inverse quantizer  11006 , the RAHT transformer  11007 , the LOD generator  11008 , the inverse lifter  11009 , and/or the color inverse transformer  11010  may perform the attribute decoding described with reference to  FIG. 10 . The attribute decoding according to the embodiments includes region adaptive hierarchical transform (RAHT) decoding, interpolation-based hierarchical nearest-neighbor prediction (prediction transform) decoding, and interpolation-based hierarchical nearest-neighbor prediction with an update/lifting step (lifting transform) decoding. The three decoding schemes described above may be used selectively, or a combination of one or more decoding schemes may be used. The attribute decoding according to the embodiments is not limited to the above-described example. 
     The arithmetic decoder  11005  according to the embodiments decodes the attribute bitstream by arithmetic coding. 
     The inverse quantizer  11006  according to the embodiments inversely quantizes the information about the decoded attribute bitstream or attributes secured as a result of the decoding, and outputs the inversely quantized attributes (or attribute values). The inverse quantization may be selectively applied based on the attribute encoding of the point cloud encoder. 
     According to embodiments, the RAHT transformer  11007 , the LOD generator  11008 , and/or the inverse lifter  11009  may process the reconstructed geometry and the inversely quantized attributes. As described above, the RAHT transformer  11007 , the LOD generator  11008 , and/or the inverse lifter  11009  may selectively perform a decoding operation corresponding to the encoding of the point cloud encoder. 
     The color inverse transformer  11010  according to the embodiments performs inverse transform coding to inversely transform a color value (or texture) included in the decoded attributes. The operation of the color inverse transformer  11010  may be selectively performed based on the operation of the color transformer  40006  of the point cloud encoder. 
     Although not shown in the figure, the elements of the point cloud decoder of  FIG. 11  may be implemented by hardware including one or more processors or integrated circuits configured to communicate with one or more memories included in the point cloud providing device, software, firmware, or a combination thereof. The one or more processors may perform at least one or more of the operations and/or functions of the elements of the point cloud decoder of  FIG. 11  described above. Additionally, the one or more processors may operate or execute a set of software programs and/or instructions for performing the operations and/or functions of the elements of the point cloud decoder of  FIG. 11 . 
       FIG. 12  illustrates a transmission device according to embodiments. 
     The transmission device shown in  FIG. 12  is an example of the transmission device  10000  of  FIG. 1  (or the point cloud encoder of  FIG. 4 ). The transmission device illustrated in  FIG. 12  may perform one or more of the operations and methods the same as or similar to those of the point cloud encoder described with reference to  FIGS. 1 to 9 . The transmission device according to the embodiments may include a data input unit  12000 , a quantization processor  12001 , a voxelization processor  12002 , an octree occupancy code generator  12003 , a surface model processor  12004 , an intra/inter-coding processor  12005 , an arithmetic coder  12006 , a metadata processor  12007 , a color transform processor  12008 , an attribute transform processor  12009 , a prediction/lifting/RAHT transform processor  12010 , an arithmetic coder  12011  and/or a transmission processor  12012 . 
     The data input unit  12000  according to the embodiments receives or acquires point cloud data. The data input unit  12000  may perform an operation and/or acquisition method the same as or similar to the operation and/or acquisition method of the point cloud video acquirer  10001  (or the acquisition process  20000  described with reference to  FIG. 2 ). 
     The data input unit  12000 , the quantization processor  12001 , the voxelization processor  12002 , the octree occupancy code generator  12003 , the surface model processor  12004 , the intra/inter-coding processor  12005 , and the arithmetic coder  12006  perform geometry encoding. The geometry encoding according to the embodiments is the same as or similar to the geometry encoding described with reference to  FIGS. 1 to 9 , and thus a detailed description thereof is omitted. 
     The quantization processor  12001  according to the embodiments quantizes geometry (e.g., position values of points). The operation and/or quantization of the quantization processor  12001  is the same as or similar to the operation and/or quantization of the quantizer  40001  described with reference to  FIG. 4 . Details are the same as those described with reference to  FIGS. 1 to 9 . 
     The voxelization processor  12002  according to the embodiments voxelizes the quantized position values of the points. The voxelization processor  120002  may perform an operation and/or process the same or similar to the operation and/or the voxelization process of the quantizer  40001  described with reference to  FIG. 4 . Details are the same as those described with reference to  FIGS. 1 to 9 . 
     The octree occupancy code generator  12003  according to the embodiments performs octree coding on the voxelized positions of the points based on an octree structure. The octree occupancy code generator  12003  may generate an occupancy code. The octree occupancy code generator  12003  may perform an operation and/or method the same as or similar to the operation and/or method of the point cloud encoder (or the octree analyzer  40002 ) described with reference to  FIGS. 4 and 6 . Details are the same as those described with reference to  FIGS. 1 to 9 . 
     The surface model processor  12004  according to the embodiments may perform trigsoup geometry encoding based on a surface model to reconstruct the positions of points in a specific region (or node) on a voxel basis. The surface model processor  12004  may perform an operation and/or method the same as or similar to the operation and/or method of the point cloud encoder (for example, the surface approximation analyzer  40003 ) described with reference to  FIG. 4 . Details are the same as those described with reference to  FIGS. 1 to 9 . 
     The intra/inter-coding processor  12005  according to the embodiments may perform intra/inter-coding on point cloud data. The intra/inter-coding processor  12005  may perform coding the same as or similar to the intra/inter-coding described with reference to  FIG. 7 . Details are the same as those described with reference to  FIG. 7 . According to embodiments, the intra/inter-coding processor  12005  may be included in the arithmetic coder  12006 . 
     The arithmetic coder  12006  according to the embodiments performs entropy encoding on an octree of the point cloud data and/or an approximated octree. For example, the encoding scheme includes arithmetic encoding. The arithmetic coder  12006  performs an operation and/or method the same as or similar to the operation and/or method of the arithmetic encoder  40004 . 
     The metadata processor  12007  according to the embodiments processes metadata about the point cloud data, for example, a set value, and provides the same to a necessary processing process such as geometry encoding and/or attribute encoding. Also, the metadata processor  12007  according to the embodiments may generate and/or process signaling information related to the geometry encoding and/or the attribute encoding. The signaling information according to the embodiments may be encoded separately from the geometry encoding and/or the attribute encoding. The signaling information according to the embodiments may be interleaved. 
     The color transform processor  12008 , the attribute transform processor  12009 , the prediction/lifting/RAHT transform processor  12010 , and the arithmetic coder  12011  perform the attribute encoding. The attribute encoding according to the embodiments is the same as or similar to the attribute encoding described with reference to  FIGS. 1 to 9 , and thus a detailed description thereof is omitted. 
     The color transform processor  12008  according to the embodiments performs color transform coding to transform color values included in attributes. The color transform processor  12008  may perform color transform coding based on the reconstructed geometry. The reconstructed geometry is the same as described with reference to  FIGS. 1 to 9 . Also, it performs an operation and/or method the same as or similar to the operation and/or method of the color transformer  40006  described with reference to  FIG. 4  is performed. The detailed description thereof is omitted. 
     The attribute transform processor  12009  according to the embodiments performs attribute transformation to transform the attributes based on the reconstructed geometry and/or the positions on which geometry encoding is not performed. The attribute transform processor  12009  performs an operation and/or method the same as or similar to the operation and/or method of the attribute transformer  40007  described with reference to  FIG. 4 . The detailed description thereof is omitted. The prediction/lifting/RAHT transform processor  12010  according to the embodiments may code the transformed attributes by any one or a combination of RAHT coding, prediction transform coding, and lifting transform coding. The prediction/lifting/RAHT transform processor  12010  performs at least one of the operations the same as or similar to the operations of the RAHT transformer  40008 , the LOD generator  40009 , and the lifting transformer  40010  described with reference to  FIG. 4 . In addition, the prediction transform coding, the lifting transform coding, and the RAHT transform coding are the same as those described with reference to  FIGS. 1 to 9 , and thus a detailed description thereof is omitted. 
     The arithmetic coder  12011  according to the embodiments may encode the coded attributes based on the arithmetic coding. The arithmetic coder  12011  performs an operation and/or method the same as or similar to the operation and/or method of the arithmetic encoder  400012 . 
     The transmission processor  12012  according to the embodiments may transmit each bitstream containing encoded geometry and/or encoded attributes and metadata information, or transmit one bitstream configured with the encoded geometry and/or the encoded attributes and the metadata information. When the encoded geometry and/or the encoded attributes and the metadata information according to the embodiments are configured into one bitstream, the bitstream may include one or more sub-bitstreams. The bitstream according to the embodiments may contain signaling information including a sequence parameter set (SPS) for signaling of a sequence level, a geometry parameter set (GPS) for signaling of geometry information coding, an attribute parameter set (APS) for signaling of attribute information coding, and a tile parameter set (TPS) for signaling of a tile level, and slice data. The slice data may include information about one or more slices. One slice according to embodiments may include one geometry bitstream Geom 0   0  and one or more attribute bitstreams Attr 0   0  and Attr 1   0 . 
     A slice refers to a series of syntax elements representing the entirety or part of a coded point cloud frame. 
     The TPS according to the embodiments may include information about each tile (for example, coordinate information and height/size information about a bounding box) for one or more tiles. The geometry bitstream may contain a header and a payload. The header of the geometry bitstream according to the embodiments may contain a parameter_set_identifier (geom_parameter_set_id), a tile identifier (geom_tile_id) and a slice identifier (geom_slice_id) included in the GPS, and information about the data contained in the payload. As described above, the metadata processor  12007  according to the embodiments may generate and/or process the signaling information and transmit the same to the transmission processor  12012 . According to embodiments, the elements to perform geometry encoding and the elements to perform attribute encoding may share data/information with each other as indicated by dotted lines. The transmission processor  12012  according to the embodiments may perform an operation and/or transmission method the same as or similar to the operation and/or transmission method of the transmitter  10003 . Details are the same as those described with reference to  FIGS. 1 and 2 , and thus a description thereof is omitted. 
       FIG. 13  illustrates a reception device according to embodiments. 
     The reception device illustrated in  FIG. 13  is an example of the reception device  10004  of  FIG. 1  (or the point cloud decoder of  FIGS. 10 and 11 ). The reception device illustrated in  FIG. 13  may perform one or more of the operations and methods the same as or similar to those of the point cloud decoder described with reference to  FIGS. 1 to 11 . 
     The reception device according to the embodiment includes a receiver  13000 , a reception processor  13001 , an arithmetic decoder  13002 , an occupancy code-based octree reconstruction processor  13003 , a surface model processor (triangle reconstruction, up-sampling, voxelization)  13004 , an inverse quantization processor  13005 , a metadata parser  13006 , an arithmetic decoder  13007 , an inverse quantization processor  13008 , a prediction/lifting/RAHT inverse transform processor  13009 , a color inverse transform processor  13010 , and/or a renderer  13011 . Each element for decoding according to the embodiments may perform an inverse process of the operation of a corresponding element for encoding according to the embodiments. 
     The receiver  13000  according to the embodiments receives point cloud data. The receiver  13000  may perform an operation and/or reception method the same as or similar to the operation and/or reception method of the receiver  10005  of  FIG. 1 . The detailed description thereof is omitted. 
     The reception processor  13001  according to the embodiments may acquire a geometry bitstream and/or an attribute bitstream from the received data. The reception processor  13001  may be included in the receiver  13000 . 
     The arithmetic decoder  13002 , the occupancy code-based octree reconstruction processor  13003 , the surface model processor  13004 , and the inverse quantization processor  1305  may perform geometry decoding. The geometry decoding according to embodiments is the same as or similar to the geometry decoding described with reference to  FIGS. 1 to 10 , and thus a detailed description thereof is omitted. 
     The arithmetic decoder  13002  according to the embodiments may decode the geometry bitstream based on arithmetic coding. The arithmetic decoder  13002  performs an operation and/or coding the same as or similar to the operation and/or coding of the arithmetic decoder  11000 . 
     The occupancy code-based octree reconstruction processor  13003  according to the embodiments may reconstruct an octree by acquiring an occupancy code from the decoded geometry bitstream (or information about the geometry secured as a result of decoding). The occupancy code-based octree reconstruction processor  13003  performs an operation and/or method the same as or similar to the operation and/or octree generation method of the octree synthesizer  11001 . When the trisoup geometry encoding is applied, the surface model processor  1302  according to the embodiments may perform trisoup geometry decoding and related geometry reconstruction (for example, triangle reconstruction, up-sampling, voxelization) based on the surface model method. The surface model processor  1302  performs an operation the same as or similar to that of the surface approximation synthesizer  11002  and/or the geometry reconstructor  11003 . 
     The inverse quantization processor  1305  according to the embodiments may inversely quantize the decoded geometry. 
     The metadata parser  1306  according to the embodiments may parse metadata contained in the received point cloud data, for example, a set value. The metadata parser  1306  may pass the metadata to geometry decoding and/or attribute decoding. The metadata is the same as that described with reference to  FIG. 12 , and thus a detailed description thereof is omitted. 
     The arithmetic decoder  13007 , the inverse quantization processor  13008 , the prediction/lifting/RAHT inverse transform processor  13009  and the color inverse transform processor  13010  perform attribute decoding. The attribute decoding is the same as or similar to the attribute decoding described with reference to  FIGS. 1 to 10 , and thus a detailed description thereof is omitted. 
     The arithmetic decoder  13007  according to the embodiments may decode the attribute bitstream by arithmetic coding. The arithmetic decoder  13007  may decode the attribute bitstream based on the reconstructed geometry. The arithmetic decoder  13007  performs an operation and/or coding the same as or similar to the operation and/or coding of the arithmetic decoder  11005 . 
     The inverse quantization processor  13008  according to the embodiments may inversely quantize the decoded attribute bitstream. The inverse quantization processor  13008  performs an operation and/or method the same as or similar to the operation and/or inverse quantization method of the inverse quantizer  11006 . 
     The prediction/lifting/RAHT inverse transformer  13009  according to the embodiments may process the reconstructed geometry and the inversely quantized attributes. The prediction/lifting/RAHT inverse transform processor  1301  performs one or more of operations and/or decoding the same as or similar to the operations and/or decoding of the RAHT transformer  11007 , the LOD generator  11008 , and/or the inverse lifter  11009 . The color inverse transform processor  13010  according to the embodiments performs inverse transform coding to inversely transform color values (or textures) included in the decoded attributes. The color inverse transform processor  13010  performs an operation and/or inverse transform coding the same as or similar to the operation and/or inverse transform coding of the color inverse transformer  11010 . The renderer  13011  according to the embodiments may render the point cloud data. 
       FIG. 14  illustrates an exemplary structure operable in connection with point cloud data transmission/reception methods/devices according to embodiments. 
     The structure of  FIG. 14  represents a configuration in which at least one of a server  1460 , a robot  1410 , a self-driving vehicle  1420 , an XR device  1430 , a smartphone  1440 , a home appliance  1450 , and/or a head-mount display (HMD)  1470  is connected to the cloud network  1400 . The robot  1410 , the self-driving vehicle  1420 , the XR device  1430 , the smartphone  1440 , or the home appliance  1450  is called a device. Further, the XR device  1430  may correspond to a point cloud data (PCC) device according to embodiments or may be operatively connected to the PCC device. 
     The cloud network  1400  may represent a network that constitutes part of the cloud computing infrastructure or is present in the cloud computing infrastructure. Here, the cloud network  1400  may be configured using a 3G network, 4G or Long Term Evolution (LTE) network, or a 5G network. 
     The server  1460  may be connected to at least one of the robot  1410 , the self-driving vehicle  1420 , the XR device  1430 , the smartphone  1440 , the home appliance  1450 , and/or the HMD  1470  over the cloud network  1400  and may assist in at least a part of the processing of the connected devices  1410  to  1470 . 
     The HMD  1470  represents one of the implementation types of the XR device and/or the PCC device according to the embodiments. The HMD type device according to the embodiments includes a communication unit, a control unit, a memory, an I/O unit, a sensor unit, and a power supply unit. 
     Hereinafter, various embodiments of the devices  1410  to  1450  to which the above-described technology is applied will be described. The devices  1410  to  1450  illustrated in  FIG. 14  may be operatively connected/coupled to a point cloud data transmission device and reception according to the above-described embodiments. 
     &lt;PCC+XR&gt; 
     The XR/PCC device  1430  may employ PCC technology and/or XR (AR+VR) technology, and may be implemented as an HMD, a head-up display (HUD) provided in a vehicle, a television, a mobile phone, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a stationary robot, or a mobile robot. 
     The XR/PCC device  1430  may analyze 3D point cloud data or image data acquired through various sensors or from an external device and generate position data and attribute data about 3D points. Thereby, the XR/PCC device  1430  may acquire information about the surrounding space or a real object, and render and output an XR object. For example, the XR/PCC device  1430  may match an XR object including auxiliary information about a recognized object with the recognized object and output the matched XR object. 
     &lt;PCC+XR+Mobile Phone&gt; 
     The XR/PCC device  1430  may be implemented as a mobile phone  1440  by applying PCC technology. 
     The mobile phone  1440  may decode and display point cloud content based on the PCC technology. 
     &lt;PCC+Self-Driving+XR&gt; 
     The self-driving vehicle  1420  may be implemented as a mobile robot, a vehicle, an unmanned aerial vehicle, or the like by applying the PCC technology and the XR technology. 
     The self-driving vehicle  1420  to which the XR/PCC technology is applied may represent a self-driving vehicle provided with means for providing an XR image, or a self-driving vehicle that is a target of control/interaction in the XR image. In particular, the self-driving vehicle  1420  which is a target of control/interaction in the XR image may be distinguished from the XR device  1430  and may be operatively connected thereto. 
     The self-driving vehicle  1420  having means for providing an XR/PCC image may acquire sensor information from sensors including a camera, and output the generated XR/PCC image based on the acquired sensor information. For example, the self-driving vehicle  1420  may have an HUD and output an XR/PCC image thereto, thereby providing an occupant with an XR/PCC object corresponding to a real object or an object present on the screen. 
     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 real object to which the occupant&#39;s eyes are directed. On the other hand, when the XR/PCC object is output on a display provided inside the self-driving vehicle, at least a part of the XR/PCC object may be output to overlap an object on the screen. For example, the self-driving vehicle  1220  may output XR/PCC objects corresponding to objects such as a road, another vehicle, a traffic light, a traffic sign, a two-wheeled vehicle, a pedestrian, and a building. 
     The virtual reality (VR) technology, the augmented reality (AR) technology, the mixed reality (MR) technology and/or the point cloud compression (PCC) technology according to the embodiments are applicable to various devices. 
     In other words, the VR technology is a display technology that provides only CG images of real-world objects, backgrounds, and the like. On the other hand, the AR technology refers to a technology that shows a virtually created CG image on the image of a real object. The MR technology is similar to the AR technology described above in that virtual objects to be shown are mixed and combined with the real world. However, the MR technology differs from the AR technology in that the AR technology makes a clear distinction between a real object and a virtual object created as a CG image and uses virtual objects as complementary objects for real objects, whereas the MR technology treats virtual objects as objects having equivalent characteristics as real objects. More specifically, an example of MR technology applications is a hologram service. 
     Recently, the VR, AR, and MR technologies are sometimes referred to as extended reality (XR) technology rather than being clearly distinguished from each other. Accordingly, embodiments of the present disclosure are applicable to any of the VR, AR, MR, and XR technologies. The encoding/decoding based on PCC, V-PCC, and G-PCC techniques is applicable to such technologies. 
     The PCC method/device according to the embodiments may be applied to a vehicle that provides a self-driving service. 
     A vehicle that provides the self-driving service is connected to a PCC device for wired/wireless communication. 
     When the point cloud data (PCC) transmission/reception device according to the embodiments is connected to a vehicle for wired/wireless communication, the device may receive/process content data related to an AR/VR/PCC service, which may be provided together with the self-driving service, and transmit the same to the vehicle. In the case where the PCC transmission/reception device is mounted on a vehicle, the PCC transmission/reception device may receive/process content data related to the AR/VR/PCC service according to a user input signal input through a user interface device and provide the same to the user. The vehicle or the user interface device according to the embodiments may receive a user input signal. The user input signal according to the embodiments may include a signal indicating the self-driving service. 
     A point cloud data transmission method/device according to embodiments is constructed as a term referring to the transmission device  10000  of  FIG. 1 , the point cloud video encoder  10002  of  FIG. 1 , the transmitter  10003  of  FIG. 1 , the acquisition  20000 /encoding  20001 /transmission  20002  of  FIG. 2 , the encoder of  FIG. 4 , the transmission device of  FIG. 12 , the device of  FIG. 14 , the encoder of  FIGS. 15, 39, 47, and 48 , the transmission method of  FIG. 39 , and the like. 
     A point cloud data reception method/device according to embodiments is construed as a term referring to the reception device  10004 , the receiver  10005  of  FIG. 1 , the point cloud video decoder  10006  of  FIG. 1 , the transmission  20002 /decoding  20003 /rendering  20004  of  FIG. 2 , the decoder of  FIGS. 10 and 11 , the reception device of  FIG. 13 , the device of  FIG. 14 , the decoder of  FIGS. 15, 40, 47, and 48 , the reception method of  FIG. 50 , and the like. 
     The method/device for transmitting or receiving point cloud data according to the embodiments may be referred to simply as a method/device. 
     According to embodiments, geometry data, geometry information, and position information constituting point cloud data are to be construed as having the same meaning. Attribute data, attribute information, and attribute information constituting the point cloud data are to be construed as having the same meaning. 
     The point cloud data transmission/reception method/device according to the embodiments proposes a method for segmentation and transmission/reception of point cloud data for local access (slice segmentation for spatial random access). 
     For example, when a direct compression mode is used for position compression, a method of configuring and transmitting/receiving slice segments, which are more suitable for a scalable PCC service, is proposed. 
     Referring to the point cloud data transmission/reception device (which may be referred to as an encoder/decoder) according to the embodiments shown in  FIGS. 4 and 11 , the point cloud data includes geometry (e.g., XYZ coordinates) and attributes (e.g., color, reflectance, intensity, grayscale, opacity, etc.) of each data. In point cloud compression (PCC), octree-based compression is performed to efficiently compress non-uniform distribution in a three-dimensional space, and attribute information is compressed based on the octree-based compression. The PCC transmission device and reception device shown in  FIGS. 4 and 11  may process operation(s) according to embodiments through each component device. 
       FIG. 15  illustrates a process of encoding, transmission, and decoding point cloud data according to embodiments. 
     Each component of  FIG. 15  may correspond to hardware, software, a processor, and/or a combination thereof. 
     A point cloud encoder  15000  is a transmission device carrying out a transmission method according to embodiments, and may scalably encode and transmit point cloud data. 
     A point cloud decoder  15010  is a reception device carrying out a reception method according to embodiments, and may scalably decode the point cloud data. 
     Source data received by the encoder  15000  may include geometry data and/or attribute data. 
     The encoder  15000  scalably encodes the point cloud data, but does not immediately generate a partial PCC bitstream. Instead, when it receives full geometry data and full attribute data, it stores the data in a storage connected to the encoder. Then, the encoder may perform transcoding for partial encoding, and generate and transmit a partial PCC bitstream. The decoder  15010  may receive and decode the partial PCC bitstream to reconstruct partial geometry and/or partial attributes. 
     Upon receiving the full geometry and full attributes, the encoder  15000  may store the data in the storage connected to the encoder, and transcode the point cloud data with a low quantization parameter (QP) to generate and transmit a complete PCC bitstream. The decoder  15010  may receive and decode the complete PCC bitstream to reconstruct full geometry and/or full attributes. The decoder  15010  may select a partial geometry and/or a partial attribute from the complete PCC bitstream through data selection. 
     The method/device according to the embodiment compresses and transmits the point cloud data by dividing the position information about data points and feature information such as color/brightness/reflectance, which are the point cloud data, into geometry information and attribute information. In this case, an octree structure having layers may be configured according to the degree of detail or PCC data may be configured according to levels of detail (LoDs). Then, scalable point cloud data coding and representation may be performed based the configured structure or data. In this case, only a part of the point cloud data may be decoded or represented due to the performance of the receiver or the transfer rate. 
     In this process, the method/device according to the embodiments may remove unnecessary data in advance. In other words, when only a part of the scalable PCC bitstream needs to be transmitted (i.e., only some layers are decoded in scalable decoding), there is no way to select and send only the necessary part. Therefore, 1) the necessary part needs to be re-encoded ( 15020 ) after decoding, or 2) the receiver must selectively apply an operation after the whole data is transferred thereto ( 15030 ). However, in case 1), delay may occur due to the time for decoding and re-encoding ( 15020 ). In case 2), bandwidth efficiency may be degraded due to transmission of unnecessary data. Further, when a fixed bandwidth is used, data quality may need to be lowered for transmission ( 15030 ). 
     Accordingly, the method/device according to the embodiments may define a slice segmentation structure of point cloud data, and signal a scalable layer and slice structure for scalable transmission. 
     In embodiments, to ensure efficient bitstream delivery and decoding, the bitstream may be divided into specific units to be processed. 
     For octree-based geometry compression, the method/device according to the embodiments may use entropy-based coding and direct coding together. In this case, a slice configuration for efficiently utilization of scalability is needed. 
     The unit according to the embodiments may be referred to as an LOD, a layer, a slice, or the like. LOD is the same term as LOD in attribute data coding, but may mean a data unit for a layered structure of a bitstream. It may be a concept corresponding to one depth or a bundle of two or more depths based on the hierarchical structure of point cloud data, for example, depths (levels) of an octree or multiple trees. Similarly, a layer is provided to generate a unit of a sub-bitstream, and is a concept that corresponds to one depth or a bundle of two or more depths, and may correspond to one LOD or two or more LODs. Also, a slice is a unit for configuring a unit of a sub-bitstream, and may correspond to one depth, a part of one depth, or two or more depths. Also, it may corresponds one LOD, a part of one LOD, or two or more LODs. According to embodiments, the LOD, the layer, and the slice may correspond to each other or one of the LOD, the layer, and the slice may be included in another one. Also, a unit according to embodiments may include an LOD, a layer, a slice, a layer group, or a subgroup, and may be referred to as complementary to each other. 
     In the method/device according to embodiments, a subdivision structure of slices for point cloud data is proposed. 
     In the method/device according to embodiments, signaling information on a scalable layer and slice structure for scalable transmission is proposed. 
     In the method/device according to embodiments, a definition of a layer group and/or a subgroup and slice segmentation is proposed. 
     In the method/device according to embodiments, an independent slice configuration method and signaling information for increasing scalability efficiency when direct coding is used are proposed. 
     In the method/device according to embodiments, layer-group-based slice configuration method and signaling for increasing scalability efficiency when direct coding is used are proposed. 
       FIG. 16  shows a layer-based point cloud data configuration and a structure of geometry and attribute bitstreams according to embodiments. 
     The transmission method/device according to the embodiments may configure layer-based point cloud data as shown in  FIG. 16  to encode and decode the point cloud data. 
     Layering of point cloud data may have a layer structure in terms of SNR, spatial resolution, color, temporal frequency, bit depth, or the like depending on the application field, and may construct layers in a direction in which data density increases based on the octree structure or LoD structure. 
     The method/device according to the embodiments may configure, encode, and decode a geometry bitstream and an attribute bitstream based on the layering as shown in  FIG. 16 . 
     A bitstream acquired through point cloud compression by the transmission device/encoder according to the embodiments may be divided into a geometry data bitstream and an attribute data bitstream according to the type of data and transmitted. 
     Each bitstream according to the embodiments may be composed of slices. Regardless of layer information or LoD information, the geometry data bitstream and the attribute data bitstream may each be configured as one slice and delivered. In this case, when only a part of the layer or LoD is to be used, operations of 1) decoding the bitstream, 2) selecting only a desired part and removing unnecessary parts, and 3) performing encoding again based on only the necessary information should be performed. 
       FIG. 17  shows a bitstream configuration according to embodiments. 
     The transmission method/device according to the embodiments may generate a bitstream as shown in  FIG. 17 , and the reception method/device according to the embodiments may decode point cloud data included in the bitstream as shown in  FIG. 17 . 
     Bitstream Configuration According to Embodiments 
     In embodiments, in order to avoid unnecessary intermediate processes, a bitstream may be divided into layers (or LoDs) and transmitted. 
     For example, in the LoD-based PCC structure, a lower LoD is included in a higher LoD. Information included in the current LoD but not included in the previous LoD, that is, information newly included in each LoD may be referred to as R (Rest). As shown in  FIG. 17 , the initial LoD information and the information R newly included in each LoD may be divided and transmitted in each independent unit. 
     The transmission method/device according to the embodiments may encode geometry data and generate a geometry bitstream. The geometry bitstream may be configured for each LOD or layer. The geometry bitstream may include a header (geometry header) for each LOD or layer. The header may include reference information for the next LOD or the next layer. The current LOD (layer) may further include information R (geometry data) not included in the previous LOD (layer). 
     The reception method/device according to the embodiments may encode attribute data and generate an attribute bitstream. The attribute bitstream may be configured for each LOD or layer, and the attribute bitstream may include a header (attribute header) for each LOD or layer. The header may include reference information for the next LOD or the next layer. The current LOD (layer) may further include information R (attribute data) not included in the previous LOD (layer). 
     The reception method/device according to the embodiments may receive a bitstream composed of LODs or layers and efficiently decode only necessary data without a complicated intermediate process. 
       FIGS. 18A and 18B  illustrate a bitstream sorting method according to embodiments. 
     The method/device according to the embodiments may sort the bitstreams of  FIG. 17  as shown in  FIGS. 18A and 18B . 
     Bitstream Sorting Method According to Embodiments 
     In transmitting a bitstream, the transmission method/device according to the embodiments may serially transmit geometry and attributes as shown in  FIGS. 18A and 18B . In this case, depending on the type of data, the whole geometry information (geometry data) may be transmitted first, and then the attribute information (attribute data) may be transmitted. In this case, the geometry information may be quickly reconstructed based on the transmitted bitstream information. 
     In  FIG. 18A , for example, layers (LODs) containing geometry data may be positioned first in the bitstream, and layers (LODs) containing attribute data may be positioned after the geometry layers. Since the attribute data is dependent on the geometry data, the geometry layer may be placed first. In addition, the positions may be changed differently according to embodiments. Reference may also be made between geometry headers and between an attribute header and a geometry header. 
     Referring to  FIG. 18B , bitstreams constituting the same layer including geometry data and attribute data may be collected and delivered. In this case, by using a compression technique capable of parallel decoding of geometry and attributes, the decoding execution time may be shortened. In this case, information that needs to be processed first (lower LoD, wherein geometry must precede attribute) may be placed first. 
     A first layer  1800  includes geometry data and attribute data corresponding to the lowest LOD  0  (layer  0 ) together with each header. A second layer  1810  includes LOD  0  (layer  0 ), and also includes the geometry data and attribute data of points for a new and more detailed layer  1  (LOD  1 ), which are not included in LOD  0  (layer  0 ), as information R 1 . A third layer  1820  may be subsequently placed in a similar manner. 
     The transmission/reception method/device according to the embodiments may efficiently select a layer (or LoD) desired in an application field at a bitstream level when a bitstream is transmitted and received. In the bitstream sorting method according to the embodiments, collecting and transmitting geometry information ( FIGS. 18A and 18B ) may produce an empty part in the middle after bitstream level selection. In this case, the bitstream may need to be rearranged. In the case where geometry and attributes are bundled and delivered according to each layer ( FIGS. 18A and 18B ), unnecessary information may be selectively removed according to the application field as follows. 
       FIG. 19  illustrates a method of selecting geometry data and attribute data according to embodiments. 
     Bitstream Selection According to Embodiments 
     When a bitstream needs to be selected as described above, the method/device according to the embodiments may select data at the bitstream level as shown in  FIG. 21 : 1) symmetric selection of geometry and attributes; 2) asymmetrical selection of geometry and attributes; or 3) A combination of the above two methods. 
     1) Symmetric Selection of Geometry and Attributes 
     Referring to  FIG. 19 , which illustrates a case where LoDs only up to LoD 1  (LOD  0 +R 1 ) are selected ( 19000 ) and transmitted or decoded, information corresponding to R 2  (new portion in LOD  2 ) corresponding to a upper layer is removed for transmission/decoding. 
     2) Asymmetric Selection of Geometry and Attributes 
     A method/device according to embodiments may transmit geometry and attributes asymmetrically. Only the attribute of the upper layer (Attribute R 2 ) is removed ( 19001 ), and the full geometry (from level  0  (root level) to level  7  (leaf level) in the triangular octree structure) may be selected and transmitted/decoded ( 19011 ). 
     Referring to  FIG. 16 , when point cloud data is represented in an octree structure and hierarchically divided into LODs (or layers), scalable encoding/decoding (scalability) may be supported. 
     The scalability function according to the embodiments may include slice level scalability and/or octree level scalability. 
     The LoD (level of detail) according to the embodiments may be used as a unit for representing a set of one or more octree layers. In addition, it may mean a bundle of octree layers to be configured as a slice. 
     In attribute encoding/decoding, the LOD according to the embodiments may be extended and used as a unit for dividing data in detail in a broader sense. 
     That is, spatial scalability by an actual octree layer (or scalable attribute layer) may be provided for each octree layer. However, when scalability is configured in slices before bitstream parsing, selection may be made in LoDs according to embodiments. 
     In the octree structure, LOD 0  may correspond to the root level to level  4 , LOD 1  may correspond to the root level to level  5 , and LOD 2  may correspond to the root level to level  7 , which is the leaf level. 
     That is, as shown in  FIG. 16 , when scalability is utilized in slices, as in the case of scalable transmission, the provided scalable step may correspond to three steps of LoD 0 , LoD 1 , and LoD 2 , and the scalable step that may be provided by the octree structure in the decoding operation may correspond to eight steps from the root to the leaf. 
     According to embodiments, for example, in  FIG. 16 , when LoD 0  to LoD 2  are configured as respective slices, a transcoder (the transcoder  15040  of  FIG. 15 ) of the receiver or the transmitter may select 1) LoD 0  only, select 2) LoD 0  and LoD 1 , or select 3) LoD 0 , LoD 1 , and LoD 2  for scalable processing. 
     Example 1: When only LoD 0  is selected, the maximum octree level may be 4, and one scalable layer may be selected from among octree layers  0  to  4  in the decoding process. In this case, the receiver may consider a node size obtainable through the maximum octree depth as a leaf node, and may transmit the node size through signaling information. 
     Example 2: When LoD 0  and LoD 1  are selected, layer  5  may be added. Thus, the maximum octree level may be 5, and one scalable layer may be selected from among octree layers  0  to  5  in the decoding process. In this case, the receiver may consider a node size obtainable through the maximum octree depth as a leaf node, and may transmit the node size through signaling information. 
     According to embodiments, an octree depth, an octree layer, and an octree level may be a unit in which data is divided in detail. 
     Example 3: When LoD 0 , LoD 1 , and LoD 2  are selected, layers  6  and  7  may be added. Thus, the maximum octree level may be 7, and one scalable layer may be selected from among octree layers  0  to  7  in the decoding process. In this case, the receiver may consider a node size obtainable through the maximum octree depth as a leaf node, and may transmit the node size through signaling information. 
       FIGS. 20A to 20C  illustrate a method of configuring a slice including point cloud data according to embodiments. 
     Slice Configuration According to Embodiments 
     The transmission method/device/encoder according to the embodiments may configure a G-PCC bitstream by segmenting the bitstream in a slice structure. A data unit for detailed data representation may be a slice. 
     For example, one or more octree layers may be matched to one slice. 
     The transmission method/device according to the embodiments, for example, the encoder, may configure a slice 2001-based bitstream by scanning a node (point) included in an octree in the direction of scan order  2000 . 
     In  FIG. 20A , some nodes in an octree layer may be included in one slice. 
     The octree layer (e.g., level  0  to level  4 ) may constitute one slice  2002 . 
     Partial data of an octree layer, for example, level  5  may constitute each slice  2003 ,  2004 ,  2005 . 
     Partial data of an octree layer, for example, level  6  may constitute each slice. 
     In  FIGS. 20B and 20C , when multiple octree layers are matched to one slice, only some nodes of each layer may be included. In this way, when multiple slices constitute one geometry/attribute frame, information necessary to configure a layer may be delivered for the receiver. The information may include information about layers included in each slice and information about nodes included in each layer. 
     In  FIG. 20B , octree layers, for example, level  0  to level  3  and partial data of level  4  may be configured as one slice. 
     Octree layers, for example, partial data of level  4  and partial data of level  5  may be configured as one slice. 
     Octree layers, for example, partial data of level  5  and partial data of level  6  may be configured as one slice. 
     An octree layer, for example, partial data of level  6  may be configured as one slice. 
     In  FIG. 20C , octree layers, for example, data of level  0  to level  4  may be configured as one slice. 
     Partial data from each of octree layer level  5 , level  6 , and level  7  may be configured as one slice. 
     The encoder and the device corresponding to the encoder according to the embodiments may encode the point cloud data, and may generate and transmit a bitstream including the encoded data and parameter information related to the point cloud data. 
     Furthermore, in generating the bitstream, the bitstream may be generated based on the bitstream structure according to embodiments (see, for example,  FIGS. 16 to 20C ). Accordingly, the reception device, the decoder, and a corresponding device according to the embodiments may receive and parse a bitstream configured to be suitable for selective partial data decoding, and partially decode and efficiently provide the point cloud data (see  FIG. 15 ). 
     Scalable Transmission According to Embodiments 
     The point cloud data transmission method/device according to the embodiments may scalably transmit a bitstream including point cloud data, and the point cloud data reception method/device according to the embodiments may scalably receive and decode the bitstream. 
     When the bitstream according to embodiments shown in  FIGS. 16 to 20C  is used for scalable transmission, information needed to select a slice required by the receiver may be transmitted to the receiver. Scalable transmission may mean transmitting or decoding only a part of a bitstream, rather than decoding the entire bitstream, and the result thereof may be low resolution point cloud data. 
     When scalable transmission is applied to the octree-based geometry bitstream, point cloud data may need to be configured with information ranging only up to a specific octree layer for the bitstream of each octree layer ( FIG. 16 ) from a root node to a leaf node. 
     To this end, the target octree layer should have no dependency on information about the lower octree layer. This may be a constraint applied to geometry coding and attribute coding in common. 
     In addition, in scalable transmission, a scalable structure used for the transmitter/receiver to select a scalable layer needs to be delivered. Considering the octree structure according to the embodiments, all octree layers may support the scalable transmission, or the scalable transmission may be allowed only for a specific octree layer or lower layers. When a slice includes some of the octree layers, a scalable layer in which the slice is included may be indicated. Thereby, it may be determined whether the slice is necessary/not necessary in the bitstream stage. In the example of  FIG. 20A , the yellow part starting from the root node constitutes one scalable layer without supporting scalable transmission. Following octree layers may be matched to scalable layers in a one-to-one correspondence. In general, scalability may be supported for a part corresponding to the leaf node. As shown in  FIG. 23 -( c ), when multiple octree layers are included in a slice, it may be defined that one scalable layer shall be configured for the layers. 
     In this case, scalable transmission and scalable decoding may be used separately according to the purpose. The scalable transmission may be used at the transmitting/receiving side for the purpose of selecting information up to a specific layer without involving a decoder. The scalable decoding is used to select a specific layer during coding. That is, the scalable transmission may support selection of necessary information without involving a decoder in a compressed state (in the bitstream stage), such that the information may be transmitted or determined by the receiver. On the other hand, the scalable decoding may support encoding/decoding data only up to a required part in the encoding/decoding process, and may thus be used in such a case as scalable representation. 
     In this case, the layer configuration for scalable transmission may be different from the layer configuration for scalable decoding. For example, the three bottom octree layers including leaf nodes may constitute one layer in terms of scalable transmission. However, when all layer information is included in terms of scalable decoding, scalable decoding may be performed for each of leaf node layer n, leaf node layer n−1, leaf node layer n−2. 
     Hereinafter, a slice structure for the layer configuration described above and a signaling method for scalable transmission will be described. 
       FIG. 21  shows a bitstream configuration according to embodiments. 
     The method/device according to the embodiments may generate a bitstream as shown in  FIG. 21 . The bitstream may include encoded geometry data and attribute data, and also include parameter information. 
     Syntax and semantics for the parameter information are described below. 
     According to embodiments, information on a separated slice may be defined in a parameter set of the bitstream and an SEI message as follows. 
     The bitstream may include a sequence parameter set (SPS), a geometry parameter set (GPS), an attribute parameter set (APS), a geometry slice header, and an attribute slice header. In this regard, depending on the application or system, the range and method to be applied may be defined in a corresponding or separate position and used differently. That is, a signal may have different meanings depending on the position where the signal is transmitted. If the signal is defined in the SPS, it may be equally applied to the entire sequence. If the signal is defined in the GPS, this may indicate that the signal is used for position reconstruction. If the signal is defined in the APS, this may indicate that the signal is applied to attribute reconstruction. If the signal is defined in the TPS, this may indicate that the signal is applied only to points within a tile. If the signal is delivered in a slice, this may indicate that the signal is applied only to the slice. In addition, the range and method to be applied may be defined in a corresponding position or a separate position depending on the application or system so as to be used differently. In addition, when the syntax elements defined below are applicable to multiple point cloud data streams as well as the current point cloud data stream, they may be carried in a superordinate parameter set. 
     Abbreviations used herein are: SPS: Sequence Parameter Set; GPS: Geometry Parameter Set; APS: Attribute Parameter Set; TPS: Tile Parameter Set; Geom: Geometry bitstream=geometry slice header+geometry slice data; Attr: Attribute bitstream=attribute slice header+attribute slice data. 
     While the embodiments define the information independently of the coding technique, the information may be defined in connection with the coding technique. In order to support regionally different scalability, the information may be defined in the tile parameter set of the bitstream. In addition, when syntax elements defined below are applicable not only to the current point cloud data stream but also to multiple point cloud data streams, they may be carried in a superordinate parameter set or the like. 
     Alternatively, a network abstract layer (NAL) unit may be defined for a bitstream and relevant information for selecting a layer, such as layer_id, may be delivered. Thereby, a bitstream may be selected at a system level. 
     Hereinafter, parameters (which may be referred to as metadata, signaling information, or the like) according to the embodiments may be generated in the process of the transmitter according to the embodiments, and transmitted to the receiver according to the embodiments so as to be used in the reconstruction process. 
     For example, the parameters may be generated by a metadata processor (or metadata generator) of the transmission device according to the embodiments, which will be described later, and may be acquired by a metadata parser of the reception device according to the embodiments. 
     Hereinafter, syntax/semantics of parameters included in a bitstream will be described with reference to  FIGS. 22 to 25 . 
       FIG. 22  shows the syntax of a sequence parameter set and a geometry parameter set according to embodiments. 
       FIG. 23  shows the syntax of an attribute parameter set according to embodiments. 
       FIG. 24  shows the syntax of a geometry data unit header according to embodiments. 
       FIG. 25  shows the syntax of an attribute data unit header according to embodiments. 
     scalable_transmission_enable_flag: When equal to 1, it may indicate that a bitstream is configured to be suitable for scalable transmission. That is, as the bitstream is composed of multiple slices, information may be selected at the bitstream stage. Scalable layer configuration information may be transmitted to indicate that slice selection is available in the transmitter or receiver, and the geometry and/or attributes are compressed to enable partial decoding. When scalable_transmission_enable_flag is 1, a transcoder of the receiver or transmitter may be used to determine whether geometry and/or attribute scalable transmission is allowed. The transcoder may be coupled to or included in the transmission device and the reception device. 
     geom_scalable_transmission_enable_flag and attr_scalable_transmission_enable_flag: When equal to 1, they may indicate that the geometry or attribute is compressed to enable scalable transmission. 
     For example, for geometry, the flag may indicate that the geometry is composed of octree-based layers or that slice partitioning (see  FIG. 23 ) is has been performed in consideration of scalable transmission. 
     When geom_scalable_transmission_enable_flag or attr_scalable_transmission_enable_flag is 1, the receiver may know that scalable transmission is available for the geometry or attributes. 
     For example, geom_scalable_transmission_enable_flag equal to 1 may indicate that octree-based geometry coding is used, and QTBT is disabled, or the geometry is coded in such a form as an octree by performing coding in order of BT-QT-OT. 
     attr_scalable_transmission_enable_flag to 1 may indicate that pred-Lifting coding is used by using scalable LOD generation or that scalable RAHT (e.g. Haar-based RAHT) is used. 
     num_scalable_layers may indicate the number of layers supporting scalable transmission. According to embodiments, a layer may mean an LOD. 
     scalable_layer_id specifies an indicator for a layer constituting scalable transmission. When a scalable_layer is composed of multiple slices, common information may be carried in a parameter set by scalable_layer_id, and different information may be carried in a data unit header according to slices. 
     num_octree_layers_in_scalable_layer may indicate the number of octree layers included in or corresponding to a layer constituting scalable transmission. When the scalable_layer is not configured based on the octree, it may refer to a corresponding layer. 
     tree_depth_start may indicate a starting octree depth (relatively closest to the root) among octree layers included in or corresponding to a layer constituting scalable transmission. 
     tree_depth_end may indicate the last octree depth (relatively closest to the leaf) among the octree layers included in or corresponding to a layer constituting scalable transmission. 
     node_size may indicate the node size of the output point cloud data when the scalable layer is reconstructed through scalable transmission. For example, when node_size equal to 1 may indicate the leaf node. Although the embodiments assume that the XYZ node size is constant, an arbitrary node size may be indicated by signaling the size in the XYZ directions or each direction in transformation coordinates such as (r(radius), phi, theta). 
     num_nodes may indicate the number of nodes included in the corresponding scalable layer. 
     num_slices_in_scalable_layer may indicate the number of slices belonging to the scalable layer. 
     slice_id specifies an indicator for distinguishing a slice or a data unit, and may deliver an indicator for a data unit belonging to the scalable layer. 
     aligned_slice_structure_enabled_flag: When equal to 1, it may indicate that the attribute scalable layer structure and/or slice configuration matches the geometry scalable layer structure and/or slice configuration. In this case, information on the attribute scalable layer structure and/or slice configuration may be identified through the information on the geometry scalable layer structure and/or slice configuration. That is, the geometry layer/slice structure is the same as the attribute layer/slice structure. 
     slice_id_offset may indicate an offset for obtaining an attribute slice or data unit based on the geometry slice id. According to embodiments, when aligned_slice_structure_enabled_flag is 1, that is, when the attribute slice structure matches the geometry slice structure, the attribute slice id may be obtained based on the geometry slice id as follows. 
       Slice_id (attr)=slice_id(geom)+slice_id_offset 
     In this case, the values provided in the geometry parameter set may be used for num_scalable_layers, scalable_layer_id tree_depth_start, tree_depth_end, node_size, num_nodes, and num_slices_in_scalable_layer, which are variables for configuring the attribute slice structure. 
     corresponding_geom_scalable_layer may indicate a geometry scalable layer corresponding to the attribute scalable layer structure. 
     num_tree_depth_in_data_unit may indicate a tree depth in which nodes belonging to a data unit are included. 
     tree_depth may indicate a tree depth. 
     num_nodes may indicate the number of nodes belonging to tree_depth among the nodes belonging to the data unit. 
     aligned_geom_data_unit_id may indicate a geometry data unit ID when the attribute data unit conforms to the scalable transmission layer structure/slice structure of the corresponding geometry data unit. 
     ref_slice_id may be used to refer to a slice that should precede the current slice for decoding (see, for example,  FIGS. 18A to 20C ). 
       FIGS. 26A and 26B  show a single slice-based geometry tree structure and a segmented slice-based geometry tree structure according to embodiments. 
     The method/device according to the embodiments may configure slices for transmitting point cloud data as shown in  FIGS. 26A and 26B . 
       FIGS. 26A and 26B  shows a geometry tree structure contained in different slice structures. According to G-PCC technology, the entire coded bitstream may be included in a single slice. For multiple slices, each slice may contain a sub-bitstream. The order of the slices may be the same as the order of the sub-bitstreams. The bitstreams may be accumulated in breadth-first order of the geometry tree, and each slice may be matched to a group of tree layers (see  FIGS. 26A and 26B ). The segmented slices may inherit the layering structure of the G-PCC bitstream. 
     Slices may not affect previous slices, just as a higher layer does not affect lower layers in the geometry tree. 
     The segmented slices according to the embodiments are effective in terms of error robustness, effective transmission, support of region of interest, and the like. 
     1) Error Resilience 
     Compared to a single slice structure, a segmented slice may be more resilient to errors. When a slice contains the entire bitstream of a frame, data loss may affect the entire frame data. On the other hand, when the bitstream is segmented into multiple slices, some slices that are not affected by the loss even may be decoded even when some other slices are lost. 
     2) Scalable Transmission 
     Multiple decoders having different capabilities may be supported. When coded data is in a single slice, the LOD of the coded point cloud may be determined prior to encoding. Accordingly, multiple pre-encoded bitstreams having different resolutions of the point cloud data may be independently transmitted. This may be inefficient in terms of large bandwidth or storage space. 
     When a PCC bitstream is generated and included in segmented slices, the single bitstream may support decoders of different levels. From the decoder perspective, the receiver may select target layers and may deliver the partially selected bitstream to the decoder. Similarly, by using a single PCC bitstream without partitioning the entire bitstream, a partial PCC bitstream may be efficiently generated at the transmitter side. 
     3) Region Based Spatial Scalability 
     Regarding the G-PCC requirement, region based spatial scalability may be defined as follows. A compressed bitstream may be configured to have one or more layers. A particular region of interest may have a high density with additional layers, and the layers may be predicted from lower layers. 
     To support this requirement, it is necessary to support different detailed representations of a region. For example, in a VR/AR application, a distant object may be represented with low accuracy and a nearby object may be represented with high accuracy. Alternatively, the decoder may increase the resolution of the region of interest according to a request. This operation may be implemented using the scalable structure of G-PCC, such as the geometry octree and scalable attribute coding scheme. Decoders should access the entire bitstream based on the current slice structure including the entire geometry or attributes. This may lead to inefficiency in terms of bandwidth, memory, and decoder. On the other hand, when the bitstream is segmented into multiple slices, and each slice includes sub-bitstreams according to scalable layers, the decoder according to the embodiments may select slices as needed before efficiently parsing the bitstream. 
       FIGS. 27A and 27B  show a layer group structure of a geometry coding tree and an aligned layer group structure of an attribute coding tree according to embodiments. 
     The method/device according to the embodiments may generate a slice layer group using the hierarchical structure of point cloud data as shown in  FIGS. 27A and 27B . 
     The method/device according to the embodiments may apply segmentation of geometry and attribute bitstreams included in different slices. In addition, from the perspective of tree depth, a coding tree structure of geometry and attribute coding and each slice included in the partial tree information may be used. 
       FIG. 27A  shows an example of a geometry tree structure and a proposed slice segments. 
     For example, 8 layers may be configured in an octree, and 5 slices may be used to contain sub-bitstreams of one or more layers. A group represents a group of geometry tree layers. For example, group  1  includes layers  0  to  4 , group  2  includes layer  5 , and group  3  includes layers  6  and  7 . Also, a group may be divided into three subgroups. Parent and child pairs exist in each subgroup. Groups  3 - 1  to  3 - 3  are subgroups of group  3 . When scalable attribute coding is used, the tree structure is identical to the geometry tree structure. The same octree-slice mapping may be used to create attribute slice segments ( FIG. 27B ). 
     A layer group represents a bundle of layer structure units generated in G-PCC coding, such as an octree layer and a LoD layer. 
     A subgroup may represent a set of neighboring nodes based on position information for one layer group. Alternatively, a set of neighbor nodes may be configured based on the lowest layer (which may be the layer closest to the root side, and may be layer  6  in the case of group  3  in  FIGS. 27A and 27B ) in the layer group, may be configured by Morton code order, may be configured based on distance, or may be configured according to coding order. Additionally, a rule may be defined such that nodes having a parent-child relationship are present in the same subgroup. 
     When a subgroup is defined, a boundary may be formed in the middle of a layer. Regarding whether continuity is maintained at the boundary, sps_entropy_continuation_enabled_flag, gsh_entropy_continuation_flag, and the like may be used to indicate whether entropy is used continuously, and ref_slice_id may be provided. Thereby, a continuation from the previous slice may be maintained. 
       FIGS. 28A and 28B  show a layer group of a geometry tree and an independent layer group structure of an attribute coding tree according to embodiments. 
     The method/device according to the embodiments may generate geometry-based slice layers and attribute-based slice layers as shown in  FIGS. 28A and 28B . 
     The attribute coding layer may have a structure different from that of the geometry coding tree. Referring to  FIG. 28B , groups may be defined independently of the geometry tree structure. 
     For efficient use of the layered structure of the G-PCC, segmentation of slices paired with the geometry and attribute layered structure may be provided. 
     For the geometry slice segments, each slice segment may contain coded data from a layer group. Here, the layer group is defined as a group of consecutive tree layers, the start and end depths of the tree layers may be a specific number in the tree depth, and the start depth is less than the end depth. 
     For the attribute slice segments, each slice segment may contain coded data from a layer group. Here, the layers may be tree depths or LODs according to an attribute coding scheme. 
     The order of the coded data in the slice segments may be the same as the order of the coded data in a single slice. 
     As parameter sets included in the bitstream, the following may be provided. 
     In the geometry parameter sets, a layer group structure corresponding to the geometry tree layers needs to be described by, for example, the number of groups, the group identifier, the number of tree depth(s) in the group, and the number of subgroup(s) in the group. 
     In the attribute parameter sets, indication information indicating whether the slice structure is aligned with the geometry slice structure is necessary. The number of groups, the group identifier, the number of tree depth(s), and the number of segment(s) are defined to describe the layer group structure. 
     The following elements are defined in the slice headers. 
     In the geometry slice header, a group identifier, a subgroup identifier, and the like may be defined to identify the group and subgroups of each slice. 
     In the attribute slice header, when the attribute layer structure is not aligned with the geometry group, it is necessary to identify the group and subgroups of each slice. 
       FIG. 29  shows syntax of parameter sets according to embodiments. 
     The syntax of  FIG. 29  may be included together with parameter information of  FIGS. 22 to 25  in the bitstream of  FIG. 21 . 
     num_layer_groups_minus1 plus 1 specifies the number of layer groups where the layer group represents a group of consecutive tree layers that are part of the geometry or attribute coding tree structure. 
     layer_group_id specifies the layer group identifier of the i-th layer group. 
     num_tree_depth_minus1 plus 1 specifies the number of tree depths contained in the i-th layer group. 
     num_subgroups_minus1 plus 1 specifies the number of subgroups in the i-th layer group. 
     aligned_layer_group_structure_flag equal to 1 specifies that the layer group and subgroup structure of the attribute slices is identical to the geometry layer group and subgroup structure. aligned_layer_group_structure_flag equal to 0 specifies that the layer group and subgroup structure of the attribute slices is not identical to the geometry layer group and subgroup structure. 
     geom_parameter_set_id specifies the geometry parameter set identifier that contains the layer group and subgroup structure information that is aligned with the attribute layer group structure. 
       FIG. 30  shows a geometry data unit header according to embodiments. 
     The header of  FIG. 30  may be included together with parameter information of  FIGS. 22 to 25  in the bitstream of  FIG. 21 . 
     subgroup_id specifies an indicator of a subgroup in a layer group indicated by layer_group_id. The range of subgroup_id may be 0 to num_subgroups minus1. 
     layer_group_id and subgroup_id may be used to indicate the order of slices, and may be used to sort the slices in bitstream order. 
     The transmission method/device and the encoder according to the embodiments may transmit the point cloud data by dividing the point cloud data into units for transmission. Through the bitstream generator, the data may be divided and packed into units ( FIGS. 33 to 35 ) suitable for selecting necessary information in a bitstream unit according to the layered structure information. 
     The reception method/device and decoder according to the embodiments may reconstruct geometry data and attribute data based on the bitstream layer ( FIGS. 33 to 35 ). 
     In this case, the sub-bitstream classifier may deliver appropriate data to the decoder based on the information in the bitstream header. Alternatively, in this process, a layer required by the receiver may be selected. 
     Based on the slice layering bitstream of  FIGS. 26A to 28B , a geometry slice and/or an attribute slice may be selected with reference to necessary parameter information, and then decoded and rendered. 
     Based on the embodiments of  FIGS. 26A to 28B , compressed data may be divided and transmitted according to layers, and only a necessary part of the pre-compressed data may be selectively transmitted in the bitstream stage without a separate transcoding process. This scheme may be efficient in terms of storage space as only one storage space per stream is required. It also enables efficient transmission in terms of (bitstream selector) bandwidth because only the necessary layers are selected before transmission. 
     In addition, the reception method/device according to the embodiments may receive the bitstream on a slice-by-slice basis, and the receiver may selectively transmit the bitstream to the decoder according to the density of point cloud data to be represented according to decoder performance or application field. In this case, since selection is made before decoding, decoder efficiency may be increased, and decoders of various performances may be supported. 
       FIG. 31  illustrates an example of combining a tree coding mode and a direct coding mode according to embodiments. 
     That is, when octree-based compression is performed, the positions of points present at similar positions may be represented in a bundle, and therefore the number of required bits may be reduced. However, as shown in  FIG. 31 , when there is no sibling node among the descendent nodes of an occupied node ( 31000 ), the octree-based compression may not have a significant effect. Accordingly, in this case, by performing direct coding of the node (i.e., point)  31000  in a direct mode, coding efficiency and compression speed may be improved. 
     That is, referring to the octree structure, a maximum of 8 descendent nodes may be provided based on the current point (node). The 8 descendent nodes may include an occupied node and/or unoccupied nodes. 
     If there are no descendent nodes and/or sibling nodes based on the current point, it is highly likely that similar neighbor points are not present. Accordingly, a residual value is generated by generating an expected value between nodes (points), the residual may become large, the accuracy may be lowered, or latency may occur. In this case, the position value of the point may be transmitted by direct coding of the point (e.g.,  31000  in  FIG. 31 ). 
     As a method to determine whether the direct coding is performed, the method/device according to the embodiments may determine use of the direct coding based on a relationship with neighbor nodes as follows. That is, the direct compression method may be operated when the following specific conditions are satisfied. 
     1) Condition for parent-based eligibility: Only the current node is an occupied child from the perspective of the parent node of the current node (point), and there is at most one occupied child (i.e., occupied sibling of the parent) (i.e., there are 2 occupied children) from the perspective of the parent (grand-parent) of the parent. 
     2) Condition for 6N eligibility: From the perspective of the parent node, only the current node is an occupied child, and 6 neighbors (nodes contacting face to face) are unoccupied. 
     For example, in this case, it may be determined that direct coding is available. In this case, only when the number of included points is less than or equal to a threshold, the inferred direct coding mode (IDCM) may be applied. When the IDCM is executed, information indicating that the IDCM is executed, the number of points, and information indicating the XYZ values of the point positions (that is, the portion corresponding to the remaining depths that are not octree-coded) may be included in at least one of the parameter sets and delivered to the reception device. 
       FIG. 32  shows an overview of the IDCM according to embodiments. 
     The direct compression operation according to the embodiments may be performed by one or more processors or integrated circuits configured to communicate with the transmission device  10000  of  FIG. 1 , the point cloud video encoder  10002  of  FIG. 1 , the encoding of  FIG. 2 , the point cloud video encoder of  FIG. 4 , the transmission device of  FIG. 12 , the device of  FIG. 14 , the point cloud data transmission device of  FIG. 39 , or one or more memories corresponding thereto. The one or more memories may store programs for processing/controlling the operations according to the embodiments. Each component of the point cloud transmission device/method according to the embodiments may be implemented in hardware, software, processor, and/or a combination thereof. The one or more processors may control various operations described herein. The processor may be referred to as a controller or the like. In some embodiments, operations may be performed by firmware, software, and/or a combination thereof. The firmware, software, and/or a combination thereof may be stored in a processor or a memory. 
     The direct decompression operation according to the embodiments may be performed by one or more processors or integrated circuits configured to communicate with the reception device  10004  of  FIG. 1 , the point cloud video decoder  10006  of  FIG. 1 , the decoding of  FIG. 2 , the decoder of  FIG. 10 , the decoder of  FIG. 11 , the reception device of  FIG. 13 , the device of  FIG. 14 , the point cloud data reception device of  FIG. 50 , or one or more memories corresponding thereto. The one or more memories may store programs for processing/controlling the operations according to the embodiments. Each component of the point cloud reception device/method according to the embodiments may be implemented by hardware, software, a processor, and/or a combination thereof. The one or more processors may control various operations described herein. The processor may be referred to as a controller or the like. In some embodiments, operations may be performed by firmware, software, and/or a combination thereof. The firmware, software, and/or a combination thereof may be stored in a processor or a memory. 
     Referring to  FIG. 32  as an example, a parent node  32000  may have up to 8 children according to the distribution of points, and a specific child  32001  may further have a child  32002 . 
     In this case, the child  32001  is the parent node of the child  32002 . In addition, it may be determined whether to additionally perform octree splitting and prediction coding or direct mode coding at the child  32002 . 
     When it is determined that direct mode coding is available ( 32003 ), it is checked whether the number of neighbor nodes (neighbor points) for the point  32002  is less than or equal to a threshold th. When the number of neighbor nodes (neighbor points) for the point  32002  is less than or equal to the threshold th, the direct mode may be enabled. In addition, x, y, and z coordinate information for position values may be directly coded for each of the one or more points. According to embodiments, the position values may be represented based on a sub-cube for the octree. 
     In another embodiment, when the number of neighbor nodes (neighbor points) for the point  32002  exceeds the threshold th, the compression efficiency of prediction coding may be higher than that of direct coding, and thus the direct mode is disabled and the node may be further split to generate an octree. That is, when it is determined that the direct mode coding is not available ( 32004 ), the octree may be additionally split into octree-based sub-cubes based on the point. 
     As described above, when direct compression is performed, the x, y, and z position information of the current depth or less is directly transmitted to the reception device. In this case, each independent position information is compressed, and therefore the compression efficiency may not be high even when arithmetic entropy compression is used. 
     Therefore, in this case, the transmission device/method may perform direct compression (or referred to as coding) on the x, y, and z values. In this case, the direct coded bitstream ( FIG. 33 ) may be transmitted independently of an arithmetic entropy coded bitstream ( FIG. 33 ). 
       FIG. 33  illustrates an example of an arithmetic entropy coded (AEC) bitstream and a direct coded (DC) bitstream according to embodiments. 
     When the geometry tree structure is divided into layer group(s) and/or subgroup(s) for scalable transmission, slices may be configured by dividing the AEC bitstream according to each layer group and/or subgroup. In one embodiment, when multiple slices are configured, each slice includes a part of the AEC bitstream, that is, an AEC sub-bitstream. In addition, a separate slice may be configured for the DC bitstream. In this case, the type of a bitstream included in each slice may be divided into an AEC bitstream and a DC bitstream. Accordingly, when geometry partial decoding is performed, the reception device may select a slice including a required AEC bitstream, and select information on a DC point of a required depth among slices including a DC bitstream. 
     In the present disclosure, for simplicity, a slice including an AEC bitstream will be referred to as an AEC slice, and a slice including a DC bitstream will be referred to as a DC slice. 
       FIG. 34  shows an example of a geometry tree structure and slice segments and an example of multiple AEC slices and one DC slice according to embodiments. 
     That is, the DC bitstream is carried in one slice. 
       FIG. 34  illustrates a case where position compression is performed based on 7 octree depths. In this case, the geometry tree structure (i.e., the octree structure) has 3 groups and is divided into a total of 5 layer groups (e.g., one of the 3 groups is again divided into 3 subgroups), and the AEC bitstreams of the 5 layer groups are included in 5 slices (e.g., slice  1  to slice  5 ), respectively. In this case, when direct compression is used, the DC bitstream may be transmitted in a separate slice (e.g., slice  6 ). According to embodiments, DC bitstreams included in slice  6  may be sequentially transmitted according to the octree depth. Referring to  FIG. 34 -( b ) as an example, a DC bitstream of depth  4 , a DC bitstream of depth  5 , a DC bitstream of depth  6 , and a DC bitstream of depth  7  are included slice  6  in this order. This example corresponds to a case where direct coding is performed starting at depth  4 . 
     When the reception device uses only information about depths up to octree depth  5  (i.e., group  2 ), the reception device may select slices  1  and  2  to reconstruct the AEC bitstream corresponding to octree depth  5  through the AEC decoder. Additionally, the reception device may select slice  6 , and reselect DC bitstreams corresponding to depths  4  and  5  in slice  6  to reconstruct the bitstreams through a DC decoder. That is, the reception device may independently reconstruct the positions of direct-compressed points through the DC decoder. 
     In this case, the DC decoder may select and use only required information for a corresponding layer from the x, y, and z position information. 
     In the example below, the octree depth A is an octree depth at which direct coding is performed, and the octree depth B is an octree depth after the octree depth A and may be a value obtained by subtracting the octree depth A from the full octree depth N. That is, when it is defined that octree depth B=octree depth (N−A), the position of the DC compressed leaf node may be defined as the DC position at the AEC occupied node position before DC as shown in Equation 5 below. That is, when direct coding is performed, if a preset condition is satisfied while performing coding toward the leaf node by octree coding, direct coding is performed. In the example of Equation 5, when the depth at which direct coding starts is depth B, the final node position is obtained by concatenating the position of the previous depth (e.g., depth A, octree-coded depth) with respect to depth B to the direct coded position. In other words, it is an expression to find the position when decoding is fully performed. 
       Leaf node position ( x  or  y  or  z )=occupied node position (from  AEC  bitstream of upper layer) at octree depth  A &lt;&lt;octree depth  B+DC  position after octree depth  A   Equation 5
 
     In Equation 5, “occupied node position at octree depth A&lt;&lt;octree depth B” means that the “occupied node position at octree depth A” should be bit-shifted to the left by “octree depth B.” 
     In addition, when octree depth C is an octree depth targeted in partial decoding (where octree depth C&lt;Full octree depth N, and octree depth C&gt;octree depth A), if partial geometry decoding is performed, the position of the point/node may be defined as in Equation 6 below. 
       Partially decoded node position ( x  or  y  or  z ) at octree depth  C =occupied node position (from  AEC ) at octree depth  A &lt;&lt;octree depth ( C−A )+ DC  position after octree depth  A &gt;&gt;octree depth ( B −( C−A ))  Equation 6
 
     Equation 6 is an application of Equation 5. That is, since the position changes when partial decoding is performed. The position changed at this time is obtained in this equation. 
     For example, a DC position is added after a position that is decoded with the octree. In this case, a node (or depth) lost by partial decoding is taken into consideration in this equation. Considering the depth lost due to partial decoding, the positions of depths excluding this part are shifted and concatenated. 
       FIG. 35  shows an example of a geometry tree structure and slice segments and an example of AEC slices and DC slices according to embodiments. 
     That is,  FIG. 35  illustrates another method for transmitting a DC bitstream. In this example, a DC bitstream is divided by octree depths and each divided DC bitstream is transmitted through each slice. That is, as many slices for DC as the number of divided DC bitstreams are segmented. 
     In this example, a DC bitstream is divided into three DC groups. The DC groups may be divided according to layer groups. For example, when the geometry tree structure is divided into three layer groups (group 1 , group 2 , and group 3 ), the DC bitstream is also divided into three DC groups (DC group 1 , DC group 2 , and DC group 3 ). Subgroups are not applied to the DC bitstream in this example. However, in an application field, subgroups may also be divided in the same manner. In this case, DC group  3  may be further divided into three DC groups, that is, DC group  3 - 1 , DC group  3 - 2 , and DC group  3 - 3  (i.e., three DC subgroups). According to embodiments, the DC bitstreams of the three DC groups (DC group 1 , DC group 2 , and DC group 3 ) are transmitted in three slices (slice  6  to slice  8 ), respectively. In this example, a DC bitstream of depth  4  (i.e., DC group  1 ) is included in slice  6 , a DC bitstream of depth  5  (i.e., DC group  2 ) is included in slice  7 , and a DC bitstream of depths  6  and  7  (i.e., DC group  3 ) is included in slice  8 . 
     Alternatively, the criterion for dividing the DC bitstream into groups and the criterion for dividing the AEC bitstream into groups may be separately applied according to the application field. 
     When the reception device decodes only information up to octree depth  5 , it may select slices  1  and  2 , and perform AEC decoding (i.e., reconstruction) on the AEC bitstreams included in slices  1  and  2  through the AEC decoder, and may perform DC decoding (i.e., reconstruction) on the DC bitstreams included in slice  6 ,  7  through the DC decoder. 
     In this case, to allow the reception device to select a DC slice according to the octree depth, layer-group or octree depth information of a bitstream included in each DC slice may be transmitted to the reception device. 
       FIG. 36  shows an example of a geometry tree structure and slice segments and an example of AEC slices and DC slices according to embodiments. 
     That is,  FIG. 36  illustrates another method for transmitting a DC bitstream. In the illustrated example, an AEC bitstream and a DC bitstream matched to each other according to an octree depth are transmitted together through the same slice. In this case, in an embodiment, the criterion for dividing the AEC bitstream is the same as the criterion for dividing the DC bitstream. For example, the same layer-group partitioning method is used to divide the AEC bitstream and the DC bitstream. 
     When the reception device uses only information up to octree depth  5 , slices  1  and  2  are selected. Slices  1  and  2  include an AEC bitstream and a DC bitstream belonging to group  1 . Therefore, when slices  1  and  2  are selected, the AEC bitstream included in slices  1  and  2  may be subjected to AEC decoding through the AEC decoder, and the DC bitstream may be subjected to DC decoding through the DC decoder. In other words, in the case where the reception device uses octree depths only up to octree depth  5 , slices  1  and  2  only need to be selected based on the layer-group information regardless of the AEC/DC bitstream type. Accordingly, the slice selection process may be operated more efficiently. 
     While a method of including different geometry coding bitstreams in one slice is described in the present disclosure, the same method may be applied to an application field where different attribute coding bitstreams are included in one slice, or a geometry coding bitstream and an attribute bitstream are included in one slice. In this case, different types of bitstreams may have different layer-groups. Alternatively, different types of bitstreams may have the same layer-group structure. In this case, they may be efficiently used in application fields such as scalable transmission and spatial scalability. 
       FIG. 21  shows an exemplary bitstream structure of point cloud data for transmission/reception according to embodiments. According to embodiments, the bitstream output from the point cloud video encoder of any one of  FIGS. 1, 2, 4, and 12  may take the form shown in  FIG. 21 . 
     According to embodiments, the bitstream of the point cloud data provides tiles or slices such that the point cloud data may be divided into regions and processed. The regions of the bitstream may have different importance levels. Accordingly, when the point cloud data is partitioned into tiles, different filters (encoding methods) or different filter units may be applied to the respective tiles. When the point cloud data is partitioned into slices, different filters or different filter units may be applied to the respective slices. 
     When the point cloud data is compressed by partitioning the data into regions, the transmission device and the reception device according to the embodiments may transmit and receive a bitstream in a high-level syntax structure for selective transmission of attribute information in the partitioned regions. 
     By transmitting the point cloud data according to the bitstream structure as shown in  FIG. 21 , the transmission device according to the embodiments may allow the encoding operation to be applied differently according to the importance level, and allow a good-quality encoding method to be used in an important region. In addition, it may support efficient encoding and transmission according to the characteristics of the point cloud data and provide attribute values according to user requirements. 
     As the the reception device according to the embodiments receives the point cloud data according to the bitstream structure as shown in  FIG. 34 , it may apply different filtering (decoding methods) to the respective regions (divided into tiles or slices) according to the processing capacity of the reception device, rather than using a complex decoding (filtering) method to the entire point cloud data. Thereby, a better image quality may be ensured for regions important to the user and appropriate latency may be ensured in the system. 
     When a geometry bitstream, an attribute bitstream, and/or a signaling bitstream (or signaling information) according to embodiments are configured in one bitstream (or G-PCC bitstream), the bitstream may include one or more sub-bitstreams. The bitstream according to the embodiments may include a sequence parameter set (SPS) for sequence-level signaling, a geometry parameter set (GPS) for signaling of geometry information coding, and one or more attribute parameter sets (APSs) (APS 0 , APS 1 ) for signaling of attribute information coding, a tile inventory (or referred to as TPS) for tile-level signaling, and one or more slices (slice  0  to slice n). That is, the bitstream of point cloud data according to the embodiments may include one or more tiles. Each tile may be a slice group including one or more slices (slice  0  to slice n). The tile inventory (i.e., TPS) according to the embodiments may include information about each of one or more tiles (e.g., coordinate value information and height/size information about a tile bounding box). Each slice may include one geometry bitstream (Geom 0 ) and/or one or more attribute bitstreams (Attr 0 , Attr 1 ). For example, slice  0  may include one geometry bitstream Geom 00  and one or more attribute bitstreams Attr 00  and Attr 10 . 
     The geometry bitstream in each slice may be composed of a geometry slice header (geom_slice_header) and geometry slice data (geom_slice_data). According to embodiments, the geometry bitstream in each slice may be referred to as a geometry data unit, the geometry slice header may be referred to as a geometry data unit header, and the geometry slice data may be referred to as geometry data unit data. 
     Each attribute bitstream in each slice may be composed of an attribute slice header (attr_slice_header) and attribute slice data (attr_slice_data). According to embodiments, the attribute bitstream in each slice may be referred to as an attribute data unit, the attribute slice header may be referred to as an attribute data unit header, and the attribute slice data may be referred to as attribute data unit data. 
     According to embodiments, parameters required for encoding and/or decoding of point cloud data may be newly defined in parameter sets (e.g., SPS, GPS, APS, and TPS (or referred to as a tile inventory), etc.) of the point cloud data and/or the header of the corresponding slice. For example, they may be added to the GPS in encoding and/or decoding of geometry information, and may be added to the tile and/or slice header in tile-based encoding and/or decoding. 
     According to embodiments, information on segmented (separated) slices and/or information related to direct coding may be signaled in at least one of the SPS, the GPS, the APS, the TPS, or an SEI message. Also, the information on segmented (separated) slices and/or information related to direct coding may be signaled in at least one of the geometry slice header (or called a geometry data unit header) or the attribute slice header (or called an attribute data unit header). 
     According to embodiments, the information on segmented (separated) slices and/or information related to direct coding may be defined in a corresponding position or a separate position depending on an application or system such that the range and method to be applied may be used differently. A field, which is a term used in syntaxes that will be described later in the present disclosure, may have the same meaning as a parameter or a syntax element. 
     That is, the signal (i.e., the information on segmented (separated) slices and/or information related to direct coding) may have different meanings depending on the position where the signal is transmitted. If the signal is defined in the SPS, it may be equally applied to the entire sequence. If the signal is defined in the GPS, this may indicate that the signal is used for position reconstruction. If the signal is defined in the APS, this may indicate that the signal is applied to attribute reconstruction. If the signal is defined in the TPS, this may indicate that the signal is applied only to points within a tile. If the signal is delivered in a slice, this may indicate that the signal is applied only to the slice. In addition, when the fields (or referred to as syntax elements) are applicable to multiple point cloud data streams as well as the current point cloud data stream, they may be carried in a superordinate parameter set. 
     According to embodiments, parameters (which may be referred to as metadata, signaling information, or the like) may be generated by the metadata processor (or metadata generator), signaling processor, or processor of the transmission device, and transmitted to the reception device so as to be used in the decoding/reconstruction process. For example, the parameters generated and transmitted by the transmission device may be acquired by the metadata parser of the reception device. 
     In this embodiment, it has been described that information is defined independently of the coding technique. However, in other embodiments, the information may be defined in connection with the coding technique. In order to support regionally different scalability, the information may be defined in the tile parameter set. Alternatively, a network abstract layer (NAL) unit may be defined and relevant information (e.g., information about segmented (separated) slices and/or information related to direct coding) for selecting a layer, such as layer_id, may be delivered, such that a bitstream may be selected even at a system level. 
       FIG. 37  shows a sequence parameter set (SPS) (seq_parameter_set( )) and a geometry parameter set according to embodiments. 
     The parameter sets may be included in the bitstream of  FIG. 21 , and may be generated by an encoder and decoded by a decoder according to embodiments. 
     The SPS according to the embodiments may include a main_profile_compatibility_flag field, a unique_point_positions_constraint_flag field, a level_idc field, an sps_seq_parameter_set_id field, an sps_bounding_box_present_flag field, an sps_source_scale_factor_numerator_minus 1  field, an sps_source_scale_factor_denominator_minus 1  field, an sps_num_attribute_sets field, log 2_max_frame_idx field, an axis_coding_order field, an sps_bypass_stream_enabled_flag field, and an sps_extension_flag field. 
     The main_profile_compatibility_flag field may indicate whether the bitstream conforms to the main profile. For example, main_profile_compatibility_flag equal to 1 may indicate that the bitstream conforms to the main profile. For example, main_profile_compatibility_flag equal to 0 may indicate that the bitstream conforms to a profile other than the main profile. 
     When unique_point_positions_constraint_flag is equal to 1, in each point cloud frame that is referred to by the current SPS, all output points may have unique positions. When unique_point_positions_constraint flag is equal to 0, in any point cloud frame that is referred to by the current SPS, two or more output points may have the same position. For example, even when all points are unique in the respective slices, slices in a frame and other points may overlap. In this case, unique_point_positions_constraint_flag is set to 0. 
     level_idc indicates a level to which the bitstream conforms. 
     sps_seq_parameter_set_id provides an identifier for the SPS for reference by other syntax elements. 
     The sps_bounding_box_present_flag field indicates whether a bounding box is present in the SPS. For example, sps_bounding_box_present_flag equal to 1 indicates that the bounding box is present in the SPS, and sps_bounding_box_present_flag equal to 0 indicates that the size of the bounding box is undefined. 
     According to embodiments, when sps_bounding_box_present_flag is equal to 1, the SPS may further include an sps_bounding_box_offset_x field, an sps_bounding_box_offset_y field, an sps_bounding_box_offset_z field, an sps_bounding_box_offset_log 2_scale field, an sps_bounding_box_size_width field, an sps_bounding_box_size_height field, and an sps_bounding_box_size_depth field. 
     sps_bounding_box_offset_x indicates the x offset of the source bounding box in Cartesian coordinates. When the x offset of the source bounding box is not present, the value of sps_bounding_box_offset_x is 0. 
     sps_bounding_box_offset_y indicates the y offset of the source bounding box in Cartesian coordinates. When the y offset of the source bounding box is not present, the value of sps_bounding_box_offset_y is 0. 
     sps_bounding_box_offset_z indicates the z offset of the source bounding box in Cartesian coordinates. When the z offset of the source bounding box is not present, the value of sps_bounding_box_offset_z is 0. 
     sps_bounding_box_offset_log 2_scale indicates a scale factor for scaling quantized x, y, and z source bounding box offsets. 
     sps_bounding_box_size_width indicates the width of the source bounding box in Cartesian coordinates. When the width of the source bounding box is not present, the value of sps_bounding_box_size_width may be 1. 
     sps_bounding_box_size_height indicates the height of the source bounding box in Cartesian coordinates. When the height of the source bounding box is not present, the value of sps_bounding_box_size_height may be 1. 
     sps_bounding_box_size_depth indicates the depth of the source bounding box in Cartesian coordinates. When the depth of the source bounding box is not present, the value of sps_bounding_box_size_depth may be 1. 
     sps_source_scale_factor_numerator_minus1 plus 1 indicates the scale factor numerator of the source point cloud. 
     sps_source_scale_factor_denominator_minus1 plus 1 indicates the scale factor denominator of the source point cloud. 
     sps_num_attribute_sets indicates the number of coded attributes in the bitstream. 
     The SPS according to the embodiments includes an iteration statement repeated as many times as the value of the sps_num_attribute_sets field. In an embodiment, i is initialized to 0, and is incremented by 1 each time the iteration statement is executed. The iteration statement is repeated until the value of i becomes equal to the value of the sps_num_attribute_sets field. The iteration statement may include an attribute_dimension_minus1[i] field and an attribute_instance_id[i] field. attribute_dimension_minus1[i] plus 1 indicates the number of components of the i-th attribute. 
     The attribute_instance_id[i] field specifies the instance ID of the i-th attribute. 
     According to embodiments, when the value of the attribute_dimension_minus1[i] field is greater than 1, the iteration statement may further include an attribute_secondary_bitdepth_minus1[i] field, an attribute_cicp_colour_primaries[i] field, an attribute_cicp_transfer_characteristics[i] field, an attribute_cicp_matrix_coeffs[i] field, and an attribute_cicp_video_full_range_flag[i] field. 
     attribute_secondary_bitdepth_minus1[i] plus 1 specifies the bitdepth for the secondary component of the i-th attribute signal(s). 
     attribute_cicp_colour_primaries[i] indicates the chromaticity coordinates of the color attribute source primaries of the i-th attribute. 
     attribute_cicp_transfer_characteristics[i] either indicates the reference opto-electronic transfer characteristic function of the color attribute as a function of a source input linear optical intensity with a nominal real-valued range of 0 to 1 or indicates the inverse of the reference electro-optical transfer characteristic function as a function of an output linear optical intensity 
     attribute_cicp_matrix_coeffs[i] describes the matrix coefficients used in deriving luma and chroma signals from the green, blue, and red, or Y, Z, and X primaries of the i-th attibute. 
     attribute_cicp_video_full_range_flag[i] specifies the black level and range of the luma and chroma signals as derived from E′Y, E′PB, and E′PR or E′R, E′G, and E′B real-valued component signals of the i-th attibute. 
     The known_attribute_label_flag[i] field indicates whether a know_attribute_label[i] field or an attribute_label_four_bytes[i] field is signaled for the i-th attribute. For example, when known_attribute_label_flag[i] equal to 0 indicates the known_attribute_label[i] field is signaled for the i-th attribute. known_attribute_label_flag[i] equal to 1 indicates that the attribute_label_four_bytes[i] field is signaled for the i-th attribute. 
     known_attribute_label[i] specifies the type of the i-th attribute. For example, known_attribute_label[i] equal to 0 may specify that the i-th attribute is color. known_attribute_label[i] equal to 1 may specify that the i-th attribute is reflectance. known_attribute_label[i] equal to 2 may specify that the i-th attribute is frame index. Also, known_attribute_label[i] equal to 4 specifies that the i-th attribute is transparency. known_attribute_label[i] equal to 5 specifies that the i-th attribute is normal. 
     attribute_label_four_bytes[i] indicates the known attribute type with a 4-byte code. 
     According to embodiments, attribute_label_four_bytes[i] equal to 0 may indicate that the i-th attribute is color. attribute_label_four_bytes[i] equal to 1 may indicate that the i-th attribute is reflectance. attribute_label_four_bytes[i] equal to 2 may indicate that the i-th attribute is a frame index. attribute_label_four_bytes[i] equal to 4 may indicate that the i-th attribute is transparency. attribute_label_four_bytes[i] equal to 5 may indicate that the i-th attribute is normals. 
     log 2_max_frame_idx indicates the number of bits used to signal a syntax variable frame_idx. 
     axis_coding_order specifies the correspondence between the X, Y, and Z output axis labels and the three position components in the reconstructed point cloud RecPic [pointidx] [axis] with and axis=0 . . . 2. 
     sps_bypass_stream_enabled_flag equal to 1 specifies that the bypass coding mode may be used in reading the bitstream. As another example, sps_bypass_stream_enabled_flag equal to 0 specifies that the bypass coding mode is not used in reading the bitstream. 
     sps_extension_flag indicates whether the sps_extension_data syntax structure is present in the SPS syntax structure. For example, sps_extension_present_flag equal to 1 indicates that the sps_extension_data syntax structure is present in the SPS syntax structure. sps_extension_present_flag equal to 0 indicates that this syntax structure is not present. 
     When the value of the sps_extension_flag field is 1, the SPS according to the embodiments may further include an sps_extension_data_flag field. 
     sps_extension_data_flag may have any value. 
       FIG. 37  shows another embodiment of a syntax structure of the SPS (sequency_parameter_set( )) according to embodiments. 
     The SPS of  FIG. 37  may further include a scalable_transmission_enable_flag field. scalable_transmission_enable_flag indicates whether a bitstream configuration is established to be suitable for scalable transmission. For example, scalable_transmission_enable_flag equal to 1 indicates that the bitstream configuration is established to be suitable for scalable transmission. That is, it may indicate that the geometry tree structure and/or attribute tree structure is composed of multiple slices, and thus information may be selected at the bitstream stage, indicate that information about segmented (separated) slices and/or information related to direct coding (e.g., scalable layer configuration information) is transmitted through the GPS, APS, TPS, slice header, SEI message, or the like to allow the transmission device or the reception device to perform slice selection, and indicate that geometry and/or attributes are compressed to enable partial decoding. That is, when the value of scalable_transmission_enable_flag is 1, the reception device or the transcoder of the reception device may identify that geometry and/or attribute scalable transmission is available, based on the value 
     According to embodiments, the scalable_transmission_enable_flag field of  FIG. 37  may be included in any position in the SPS of  FIG. 37 . 
       FIG. 37  shows an embodiment of a syntax structure of the GPS (geometry_parameter_set( )) according to the present disclosure. The GPS may include information on a method of encoding geometry information of point cloud data included in one or more slices. 
     According to embodiments, the GPS may include a gps_geom_parameter_set_id field, a gps_seq_parameter_set_id field, gps_box_present_flag field, a unique_geometry_points_flag field, a geometry_planar_mode_flag field, a geometry_angular_mode_flag field, a neighbour_context_restriction_flag field, a inferred_direct_coding_mode_enabled_flag field, a bitwise_occupancy_coding_flag field, an adjacent_child_contextualization_enabled_flag field, a log 2_neighbour_avail_boundary field, a log 2_intra_pred_max_node_size field, a log 2_trisoup_node_size field, a geom_scaling_enabled_flag field, a gps_implicit_geom_partition_flag field, and a gps_extension_flag field. 
     gps_geom_parameter_set_id provides an identifier for the GPS for reference by other syntax elements. 
     gps_seq_parameter_set_id specifies the value of sps_seq_parameter_set_id for the active SPS. 
     gps_box_present_flag indicates whether additional bounding box information is provided in a geometry slice header that references the current GPS. For example, gps_box_present_flag field equal to 1 may indicate that additional bounding box information is provided in the geometry slice header that references the current GPS. Accordingly, when the value of the gps_box_present_flag field is 1, the GPS may further include a gps_gsh_box_log 2_scale_present_flag field. 
     gps_gsh_box_log 2_scale_present_flag indicates whether gps_gsh_box_log 2_scale is signaled in each geometry slice header that references the current GPS. For example, gps_gsh_box_log 2_scale_present_flag equal to 1 may indicate that gps_gsh_box_log 2_scale is signaled in each geometry slice header that references the current GPS. As another example, gps_gsh_box_log 2_scale_present_flag equal to 0 may indicate that gps_gsh_box_log 2_scale is not signaled in each geometry slice header that references the current GPS, and that a common scale for all slices is signaled in the gps_gsh_box_log 2_scale field of the current GPS. 
     When the value of the gps_gsh_box_log 2_scale_present_flag field is 0, the GPS may further include a gps_gsh_box_log 2_scale field. 
     gps_gsh_box_log 2_scale indicates a common scale factor of the bounding box origin for all slices that references the current GPS. 
     unique_geometry_points_flag indicates whether all output points have unique positions in one slice in all slices currently referring to GPS. For example, unique_geometry_points_flag equal to 1 indicates that in all slices that refer to the current GPS, all output points have unique positions within a slice. unique_geometry_points_flag field equal to 0 indicates that in all slices that refer to the current GPS, the two or more of the output points may have same positions within a slice. 
     The geometry_planar_mode_flag field indicates whether the planar coding mode is activated. For example, geometry_planar_mode_flag equal to 1 indicates that the planar coding mode is active. geometry_planar_mode_flag equal to 0 indicates that the planar coding mode is not active. 
     When the value of the geometry_planar_mode_flag field is 1, that is, TRUE, the GPS may further include a geom_planar_mode_th_idcm field, a geom_planar_mode_th[1] field, and a geom_planar_mode_th[2] field. 
     The geom_planar_mode_th_idcm field may specify the value of the threshold of activation for the direct coding mode. 
     geom_planar_mode_th[i] specifies, for i in the range of 0 . . . 2, specifies the value of the threshold of activation for planar coding mode along the i-th most probable direction for the planar coding mode to be efficient. 
     geometry_angular_mode_flag indicates whether the angular coding mode is active. For example, geometry_angular_mode_flag field equal to 1 may indicate that the angular coding mode is active. geometry_angular_mode_flag field equal to 0 may indicate that the angular coding mode is not active. 
     When the value of the geometry_angular_mode_flag field is 1, that is, TRUE, the GPS may further include an lidar_head_position[0] field, a lidar_head_position[1] field, a lidar_head_position[2] field, a number_lasers field, a planar_buffer_disabled field, an implicit_qtbt_angular_max_node_min_dim_log 2_to_split_z field, and an implicit_qtbt_angular_max_diff_to_split_z field. 
     The lidar_head_position[0] field, lidar_head_position[1] field, and lidar_head_position[2] field may specify the (X, Y, Z) coordinates of the lidar head in the coordinate system with the internal axes. 
     number_lasers specifies the number of lasers used for the angular coding mode. 
     The GPS according to the embodiments includes an iteration statement that is repeated as many times as the value of the number_lasers field. In an embodiment, i is initialized to 0, and is incremented by 1 each time the iteration statement is executed. The iteration statement is repeated until the value of i becomes equal to the value of the number_lasers field. This iteration statement may include a laser_angle[i] field and a laser_correction[i] field. 
     laser_angle[i] specifies the tangent of the elevation angle of the i-th laser relative to the horizontal plane defined by the 0-th and the 1st internal axes. 
     laser_correction[i] specifies the correction, along the second internal axis, of the i-th laser position relative to the lidar_head_position[2]. 
     planar_buffer_disabled equal to 1 indicates that tracking the closest nodes using a buffer is not used in process of coding the planar mode flag and the plane position in the planar mode. planar_buffer_disabled equal to 0 indicates that tracking the closest nodes using a buffer is used. 
     implicit_qtbt_angular_max_node_min_dim_log 2_to_split_z specifies the log 2 value of a node size below which horizontal split of nodes is preferred over vertical split. 
     implicit_qtbt_angular_max_diff_to_split_z specifies the log 2 value of the maximum vertical over horizontal node size ratio allowed to a node. 
     neighbour_context_restriction_flag equal to 0 indicates that geometry node occupancy of the current node is coded with the contexts determined from neighboring nodes which is located inside the parent node of the current node. neighbour_context_restriction_flag equal to 1 indicates that geometry node occupancy of the current node is coded with the contexts determined from neighboring nodes which is located inside or outside the parent node of the current node. 
     inferred_direct_coding_mode_enabled_flag indicates whether direct_mode_flag is present in the geometry node syntax. For example, inferred_direct_coding_mode_enabled_flag equal to 1 indicates that direct_mode_flag is present in the geometry node syntax. For example, inferred_direct_coding_mode_enabled_flag equal to 0 indicates that direct_mode_flag is not present in the geometry node syntax. 
     bitwise_occupancy_coding_flag indicates whether geometry node occupancy is encoded using bitwise contextualization of the syntax element occupancy map. For example, bitwise_occupancy_coding_flag equal to 1 indicates that geometry node occupancy is encoded using bitwise contextualization of the syntax element ocupancy_map. For example, bitwise_occupancy_coding_flag equal to 0 indicates that geometry node occupancy is encoded using the directory encoded syntax element occypancy_byte. 
     adjacent_child_contextualization_enabled_flag indicates whether the adjacent children of neighboring octree nodes are used for bitwise occupancy contextualization. For example, adjacent_child_contextualization_enabled_flag equal to 1 indicates that the adjacent children of neighboring octree nodes are used for bitwise occupancy contextualization. For example, adjacent_child_contextualization_enabled_flag equal to 0 indicates that the children of neighboring octree nodes are is not used for the occupancy contextualization. 
     log 2_neighbour_avail_boundary specifies the value of NeighbAvailBoundary, a variable used in the decoding process. For example, when neighbour_context_restriction_flag is equal to 1, NeighbAvailabilityMask may be set to 1. For example, when neighbour_context_restriction_flag is equal to 0, NeighbAvailabilityMask may be set to 1&lt;&lt;log 2_neighbour_avail_boundary. 
     log 2_intra_pred_max_node_size specifies the octree nodesize eligible for occupancy intra prediction. 
     log 2_trisoup_node_size specifies the variable TrisoupNodeSize as the size of the triangle nodes. 
     geom_scaling_enabled_flag indicates specifies whether a scaling process for geometry positions is applied during the geometry slice decoding process. For example, geom_scaling_enabled_flag equal to 1 specifies that a scaling process for geometry positions is applied during the geometry slice decoding process. geom_scaling_enabled_flag equal to 0 specifies that geometry positions do not require scaling. 
     geom_base_qp indicates the base value of the geometry position quantization parameter. 
     gps_implicit_geom_partition_flag indicates whether the implicit geometry partition is enabled for the sequence or slice. For example, equal to 1 specifies that the implicit geometry partition is enabled for the sequence or slice. gps_implicit_geom_partition_flag equal to 0 specifies that the implicit geometry partition is disabled for the sequence or slice. When gps_implicit_geom_partition_flag is equal to 1, the following two fields, that is, a gps_max_num_implicit_qtbt_before_ot field and a gps_min_size_implicit_qtbt field, are signaled. 
     gps_max_num_implicit_qtbt_before_ot specifies the maximal number of implicit QT and BT partitions before OT partitions. Then, the variable K is initialized by gps_max_num_implicit_qtbt_before_ot as follows. 
       K=gps_max_num_implicit_qtbt_before_ot. 
     gps_min_size_implicit_qtbt specifies the minimal size of implicit QT and BT partitions. Then, the variable M is initialized by gps_min_size_implicit_qtbt as follows. 
       M=gps_min_size_implicit_qtbt 
     gps_extension_flag indicates whether a gps_extension_data syntax structure is present in the GPS syntax structure. For example, gps_extension_flag equal to 1 indicates that the gps_extension_data syntax structure is present in the GPS syntax. For example, gps_extension_flag equal to 0 indicates that the gps_extension_data syntax structure is not present in the GPS syntax. 
     When gps_extension_flag is equal to 1, the GPS according to the embodiments may further include a gps_extension_data flag field. 
     gps_extension_data_flag may have any value. Its presence and value do not affect decoder conformance to profiles 
     According to embodiments, the GPS may further include a geom_tree_type field. For example, geom_tree_type equal to 0 indicates that the position information (or geometry) is coded using an octree. geom_tree_type equal to 1 indicates that the position information (or geometry) is coded using a predictive tree. 
     According to embodiments, when the value of the scalable_transmission_enable_flag field included in the SPS is 1, the GPS may include a geom_scalable_transmission_enable_flag field. 
     In one embodiment, geom_scalable_transmission_enable_flag equal to 1 indicates that the geometry is compressed to enable scalable transmission. 
     For example, it may indicate that the geometry is composed of octree-based layers or that slice partitioning (see  FIG. 24 , etc.) is performed in consideration of scalable transmission. 
     For example, geom_scalable_transmission_enable_flag equal to 1 may indicate that octree-based geometry coding is used, and QTBT is disabled, or the geometry is coded in such a form as an octree by performing coding in order of BT (Binary-tree)-QT (Quad-tree)-OT (Octree). 
     When geom_scalable_transmission_enable_flag is equal to 1, the GPS may further include a num_scalable_layer field. 
     num_scalable_layers may indicate the number of layers supporting scalable transmission. A layer according to the embodiments may mean an LOD. 
     According to embodiments, the GPS includes an iteration statement repeated as many times as the value of the num_scalable_layers field. In an embodiment, i is initialized to 0, and is incremented by 1 each time the iteration statement is executed. The iteration statement is repeated until the value of i becomes equal to the value of the num_scalable_layers field. The iteration statement may include a scalable_layer_id[i] field and a num_slices_in_scalable_layer[i] field. 
     The scalable_layer_id[i] field may specify an identifier of the i-th scalable layer. That is, it specifies an indicator of a scalable layer constituting scalable transmission. According to embodiments, when a scalable layer is composed of multiple slices, common information may be transmitted through the scalable_layer_id field in a parameter set, and other individual information may be transmitted through a data unit header according to slices. 
     According to embodiments, when geom_tree_type is equal to 0, that is, when position information (i.e., geometry) is coded using an octree, the GPS may further include a num_octree_layers_in_scalable_layer[i] field, a tree_depth_start[i] field, a tree_depth_end[i] field, a node_size[i] field, and a num_nodes[i] field. 
     num_octree_layers_in_scalable_layer[i] may indicate the number of octree layers included in or corresponding to the i-th scalable layer constituting scalable transmission. When the scalable layer is not configured based on the octree, num_octree_layers_in_scalable_layer[i] may refer to a corresponding layer. 
     tree_depth_start[i] may indicate a starting octree depth (relatively closest to the root) among octree layers included in or corresponding to the i-th scalable layer constituting scalable transmission. 
     tree_depth_end[i] may indicate the last octree depth (relatively closest to the leaf) among the octree layers included in or corresponding to the i-th scalable layer constituting scalable transmission. 
     node_size[i] may indicate the node size of the output point cloud data when the i-th scalable layer is reconstructed through scalable transmission. For example, node_size[i] equal to 1 may indicate the leaf node. Although the embodiments assume that the XYZ node size is constant, an arbitrary node size may be indicated by signaling the size in the XYZ direction or each direction in transformation coordinates such as (r(radius), phi, theta). 
     num_slices_in_scalable_layer[i] may indicate the number of slices belonging to the i-th scalable layer. 
     According to embodiments, the GPS may include an iteration statement that is repeated as many times as the value of the num_slices_in_scalable_layer[i] field. In an embodiment, j is initialized to 0, and is incremented by 1 each time the iteration statement is executed. The iteration statement is repeated until the value of j becomes equal to the value of the num_slices_in_scalable_layer[i] field. This iteration statement may include a sub_group_id[i][j] field, a num_nodes_in_subgroup[i][j] field, a bitstream_type[i][j] field, and a slice_id[i][j] field. 
     The sub_group_id[i][j] field specifies an identifier of a subgroup included in the j-th slice belonging to the i-th scalable layer. That is, the sub_group_id[i][j] field specifies an indicator of a subgroup in the layer group indicated by the layer_group_id field. The range of subgroup_id is 0 to num_subgroups_minus1[layer_group_id], where subgroup_id indicates the order of slices in the same layer_group_id. 
     num_nodes_in_subgroup[i][j] indicates the number of nodes related to the j-th slice belonging to the i-th scalable layer. That is, num_nodes_in_subgroup[i][j] indicates the number of nodes included in the geometry data unit. According to embodiments, the sum of all num_nodes in a geometry data unit specifies the total number of nodes in the geometry data unit. 
     bitstream_type[i][j] indicates the type of a bitstream included in the j-th slice belonging to the i-th scalable layer. According to embodiments, bitstream_type may indicate the type of a bitstream included in a slice. bitstream_type equal to 0 may indicate that the bitstream is an arithmetic entropy coding (AEC) bitstream. bitstream_type equal to 1 may indicate that the bitstream is a direct coding (DC) bitstream. bitstream_type equal to 2 may indicate that an AEC bitstream and a DC bitstream are present together in the slice. 
     slice_id[i][j] specifies an identifier for identifying the j-th slice belonging to the i-th scalable layer. That is, slice_id[i][j] may specify an indicator for distinguishing a slice or a data unit, and may deliver an indicator for a data unit (or called a slice) belonging to a slice layer. 
     According to embodiments, the information on the segmented (separated) slices and/or information related to direct coding of  FIG. 38  may be included in any position in the GPS of  FIG. 37 . 
       FIG. 38  shows a syntax structure of a geometry data unit header (or referred to as a geometry slice header) according to embodiments. 
     The geometry data unit header according to the embodiments may include a slice_id field and a bitstream_type field. 
     slice_id specifies an identifier for identifying a data unit (i.e., a slice). That is, slice_id specifies an indicator for distinguishing a slice or a data unit, and may deliver an indicator for a data unit (or called a slice) belonging to a slice layer. 
     bitstream_type indicates the type of a bitstream included in a slice. According to embodiments, bitstream_type may indicate the type of a bitstream included in the slice. bitstream_type equal to 0 may indicate that the bitstream is an arithmetic entropy coding (AEC) bitstream. bitstream_type equal to 1 may indicate that the bitstream is a direct coding (DC) bitstream. bitstream_type equal to 2 may indicate that an AEC bitstream and a DC bitstream are present together in the slice. 
     According to embodiments, when the value of the geom_scalable_transmission_enable_flag field is 1, the geometry data unit header may further include a scalable_layer_id field, a num_tree_depth_in_data_unit field, and a bitstream_type field. 
     scalable_layer_id may specify an identifier of a scalable layer related to a data unit (i.e., slice). That is, it specifies an indicator for a scalable layer constituting scalable transmission. According to embodiments, when a scalable layer is composed of multiple slices, common information may be transmitted through the scalable_layer_id field in a parameter set, and other individual information may be transmitted through the data unit header of  FIG. 43  according to slices. 
     When multiple subgroups are present in the scalable layer corresponding to scalable_layer_id, the geometry data unit header may further include a sub_group_id field. 
     sub_group_id specifies an identifier of a subgroup belonging to the scalable layer specified by scalable_layer_id. That is, sub_group_id specifies an indicator of a subgroup in the layer group indicated by layer_group_id. The range of subgroup_id is 0 to num_subgroups_minus1[layer_group_id], where subgroup_id indicates the order of slices in the same layer_group_id. 
     num_tree_depth_in_data_unit may indicate the number of tree depths including nodes belonging to a data unit (i.e., a slice). 
     According to embodiments, the geometry data unit header includes an iteration statement repeated as many times as the value of num_tree_depth_in_data_unit. In an embodiment, i is initialized to 0, and is incremented by 1 each time the iteration statement is executed. The iteration statement is repeated until the value of i becomes equal to the value of num_tree_depth_in_data_unit. This iteration statement may include a tree_depth[i] field, a num_nodes[i] field, and a num_nodes_in_subgroup[i][sub_group_id] field. 
     tree_depth[i] may indicate the i-th tree depth. That is, tree_depth may indicate a tree depth. 
     num_nodes[i] may indicate the number of nodes included in the i-th tree depth. That is, num_nodes[i] may indicate the number of nodes belonging to the i-th tree depth (tree_depth) among the nodes belonging to a data unit. 
     num_nodes_in_subgroup[i][sub_group_id] indicates the number of nodes related to a data unit (i.e., a slice). That is, num_nodes_in_subgroup[i] indicates the number of nodes included in a subgroup indicated by sub_group_id. According to embodiments, the sum of all num_nodes in a geometry data unit specifies the total number of nodes in the geometry data unit. 
     num_points specifies that the number of points in an attribute data unit. The sum of all num_points in an attribute data unit specifies the total number of points in the attribute data unit. 
     According to embodiments, when bitstream_type is equal to 2, that is, an AEC bitstream and a DC bitstream are present together in the slice, the geometry data unit header may further include a dc_bitstream_offset field, a dc_bitstream_length field, and a dc_backward_enabled_flag field. 
     According to embodiments, dc_bitstream_offset and dc_bitstream_length may indicate the start/end positions of the DC bitstream and the total length of the DC bitstream in the slice. That is, when bitstream_type is equal to 2, an AEC bitstream and a DC bitstream may be present together in one slice. In this case, the start/end positions of the DC bitstream and the total length of the DC bitstream may be indicated. 
     dc_backward_enabled_flag equal to 1 may indicate that the DC bitstream is included in reverse order in the slice including both the AEC bitstream and the DC bitstream. In this case, the end of the bitstream of the slice may be the start of the DC bitstream, and dc_bitstream_offset may be the end of the DC bitstream. dc_backward_enabled_flag equal to 0 indicates that the DC bitstream is included in the same direction as the AEC bitstream in the slice including both the AEC bitstream and the DC bitstream. In this case, it may be seen that the DC bitstream starts from dc_bitstream_offset and the DC bitstream ends at the end of the entire bitstream (i.e., dc_bitstream_offset+dc_bitstream_length). 
     According to embodiments, the geometry data unit header may further include a ref_slice_id field. 
     The ref_slice_id field may be used to indicate a slice that must be preceded for decoding of the current slice (see, for example, the headers of  FIGS. 19-21 ). 
     According to embodiments, the information about the segmented (separated) slices and/or information related to direct coding of  FIG. 38  may be included in any position in the geometry slice header (i.e., the geometry data unit header). 
       FIG. 39  shows a structure of a point cloud data transmission device according to embodiments. 
     The transmission device of  FIG. 39  according to the embodiments corresponds to the transmission device  10000  of  FIG. 1 , the point cloud video encoder  10002  of  FIG. 1 , the transmitter  10003  of  FIG. 1 , the acquisition  20000 /encoding  20001 /transmission  20002  of  FIG. 2 , the encoder of  FIG. 4 , the transmission device of  FIG. 12 , the device of  FIG. 14 , the encoder of  FIGS. 18A and 18B , and the like. Each component of  FIG. 39  may correspond to hardware, software, a processor, and/or a combination thereof. 
     Operations of the encoder and the transmitter according to the embodiments are described below. 
     When point cloud data is input to the transmission device, a geometry encoder  60010  encodes position information (geometry data (e.g., XYZ coordinates, phi-theta coordinates, etc.)), and an attribute encoder  60020  encodes attribute data (e.g., color, reflectance, intensity, grayscale, opacity, medium, material, glossiness, etc.). 
     The compressed (encoded) data is divided into units for transmission. The data may be divided by a sub-bitstream generator  60040  into units suitable for selection of necessary information in the bitstream unit according to layered structure information and may then be packed. 
     According to embodiments, an octree coded geometry bitstream is input to an octree coded geometry bitstream segmentation part  60041 , and a direct coded geometry bitstream is input to a direct coded geometry bitstream segmentation part  60042 . 
     The octree coded geometry bitstream segmentation part  60041  divides the octree coded geometry bitstream into one or more groups and/or subgroups based on information about segmented (separated) slices and/or information related to direct coding generated by a layer-group structure generator  60030 . For details, see  FIGS. 15 to 33  described above. Detailed description thereof will be skipped. 
     In addition, the direct coded geometry bitstream segmentation part  60042  divides the direct code geometry bitstream into one or more groups and/or subgroups based on the information about the segmented (separated) slices and/or information related to direct coding generated by the layer-group structure generator  60030 . For details, see  FIGS. 15 to 33  described above. Detailed description thereof will be skipped. 
     An output of the octree coded geometry bitstream segmentation part  60041  and an output of the direct coded geometry bitstream segmentation part  60042  are input to a geometry bitstream bonding part  60043 . 
     The geometry bitstream bonding part  60043  performs a geometry bitstream bonding process based on the information about the segmented (separated) slices and/or information related to direct coding generated by the layer-group structure generator  60030 , and outputs sub-bitstreams to a segmented slice generator  60045  on a layer group-by-layer group basis. For example, the geometry bitstream bonding part  60043  performs a process of concatenating an AEC bitstream and a DC bitstream within a slice. Final slices are created by the geometry bitstream bonding part  60043 . 
     A coded attribute bitstream segmentation part  60044  divides the coded attribute bitstream into one or more groups and/or subgroups based on the information about the segmented (separated) slices and/or information related to direct coding generated by the layer-group structure generator  60030 . The one or more groups and/or subgroups of the attribute information may be linked with the one or more groups and/or subgroups for the geometry information, or may be independently generated. For details, see  FIGS. 15 to 33  described above. Detailed description thereof will be skipped. 
     The segmented slice generator  60045  segments one slice into multiple slices according to the inputs received from the geometry bitstream bonding part  60043  and/or the coded attribute bitstream segmentation part  60044  based on information about segmented (separated) slices and/or direct coding related information generated by a metadata generator  60050 . Each sub-bitstream is transmitted through each slice segment. In this case, the AEC bitstream and the DC bitstream may be transmitted through one slice or may be transmitted through different slices. 
     A multiplexer  60060  multiplexes the output of the segmented slice generator  60045  and the output of the metadata generator  60050  for each layer, and provides a multiplexed output to the transmitter  60070 . For the information about segmented (separated) slices and/or information related to direct coding generated by the layer-group structure generator  60030  and/or the metadata generator, refer to  FIGS. 34 to 48 . 
     That is, as proposed in the present disclosure, when different types of bitstreams (e.g., an AEC bitstream and a DC bitstream) are included in one slice, the bitstreams (e.g., the AEC bitstream and DC bitstream) generated by the geometry encoder  60010  may be separated according to the purposes. Then, respective slices or adjacent information may be included in one slice according to the information about the segmented (separated) slices and/or information related to direct coding (i.e., layer-group information) generated by the layer-group structure generator  60030  and/or the metadata generator. According to embodiments, the information about the segmented (separated) slices and/or information related to direct coding (e.g., information such as bitstream type, bitstream_offset, bitstream_length, and a bitstream direction in addition to layer-group information according to each slice id, layer information included in a layer-group, the number of nodes, layer depth information, and the number of nodes included in a subgroup) may be transmitted from the metadata generator  60050 . The information about the segmented (separated) slices and/or information related to direct coding (e.g., information such as bitstream type, bitstream_offset, bitstream_length, and a bitstream direction in addition to layer-group information according to each slice id, layer information included in a layer-group, the number of nodes, layer depth information, and the number of nodes included in a subgroup) may be signaled in the SPS, APS, GPS, geometry data unit header, attribute data unit header, or SEI message. For details of the information about the segmented (separated) slices and/or information related to direct coding (e.g., information such as bitstream type, bitstream_offset, bitstream_length, and a bitstream direction in addition to layer-group information according to each slice id, layer information included in a layer-group, the number of nodes, layer depth information, and the number of nodes included in a subgroup), see  FIGS. 34 to 48 . Detailed description thereof will be skipped. 
       FIG. 40  shows a point cloud data reception device according to embodiments. 
     An operation of each component of the reception device of  FIG. 40  may follow the operation of a corresponding component of the transmission device of  FIG. 39  or a reverse process thereof. 
       FIG. 41  is a flowchart of a point cloud data reception device according to embodiments. 
     That is,  FIG. 41  illustrates the operation of the sub-bitstream classifier shown in  FIG. 40  in more detail. In other words, it is assumed that the geometry data and the attribute data are scalably transmitted from the transmitter. 
     The reception device receives data on a slice-by-slice basis, and the metadata parser delivers parameter set information such as the SPS, GPS, APS, and TPS (e.g., information about segmented (separated) slices and/or information related to direct coding). Based on the delivered information, scalability may be determined. When the data is scalable, the slice structure for scalable transmission is identified as shown in  FIG. 41  ( 65011 ). First, the geometry slice structure may be identified based on information such as num_scalable_layers, scalable_layer_id, tree_depth_start, tree_depth_end, node_size, num_nodes, num_slices_in_scalable_layer, and slice_id carried in the GPS. 
     When aligned_slice_structure_enabled_flag is equal to 1 ( 65017 ), the attribute slice structure may also be identified in the same way (e.g., geometry is encoded based on an octree, attributes are encoded based on scalable LoD or scalable RAHT, and geometry/attribute slice pairs generated through the same slice partitioning have the same number of nodes for the same octree layer. 
     When the structures are identical, the range of geometry slice id is determined according to the target scalable layer, and the range of attribute slice id is determined by slice_id_offset. A geometry/attribute slice is selected according to the determined ranges ( 65012  to  65014 ,  65018 , and  65019 ). 
     When aligned_slice_structure_enabled_flag=0, the attribute slice structure may be separately identified based on the information such as num_scalable_layers, scalable_layer_id tree_depth_start, tree_depth_end, node_size, num_nodes, num_slices_in_scalable_layer, and slice_id delivered through the APS, and the range of the necessary attribute slice id may be limited according to the scalable operation. Based on the range, a required slice may be selected through each slice id before reconstruction ( 65019 ,  65020 , and  65021 ). The geometry/attribute slice selected through the above process is transmitted to the decoder as an input. 
     The decoding process according to the slice structure has been described above based on the scalable transmission or the scalable selection of the receiver. However, when scalable_transmission_enabled_flag is equal to 0, the operation of ranging geom/attr slice id may be skipped and the entire slices may be selected such that they may be used even in the non-scalable operation. Even in this case, information about a preceding slice (e.g., a slice belonging to a higher layer or a slice specified by ref_slice_id) may be used through the slice structure information delivered through a parameter set such as the SPS, GPS, APS, or TPS (e.g., information about the segmented (separated) slices and/or information related to direct coding). 
     As described above, the bitstream may be received based on the scalable transmission, and the scalable bitstream structure may be identified based on the parameter information included in the bitstream. A geometry scalable layer may be estimated. 
     A geometry slice may be identified based on geom_slice_id. 
     A geometry slice may be selected based on slice_id. 
     The decoder may decode the selected geometry slice. 
     When aligned_slice_structure_enabled_flag included in the bitstream is equal to 1, the attribute slice ID corresponding to the geometry slice may be checked. An attribute slice may be accessed based on slice_id_offset. 
     An attribute slice may be selected based on slice_id. 
     The decoder may decode the selected attribute slice. 
     When aligned_slice_structure_enabled_flag is not equal to 1, an attribute scalable layer may be estimated. An attribute slice may be identified based on the attribute slice id. 
     An attribute slice may be selected based on slice_id. 
     In the present disclosure, when different types of geometry bitstreams (e.g., an AEC bitstream and a DC bitstream) are present, all slices included in the range for the different bitstreams may be selected in the slice selection operation. When the different types of bitstreams are included in one slice, the bitstreams may be separated based on offset information and length information, and the separated bitstreams may be subjected to aa concatenation operation in which the bitstreams are concatenated into one bitstream for decoding according to layer-group order. This operation may be included as a process of processing bitstreams separated by layer-groups into contiguous bitstreams, and the bitstreams may be sorted in order based on layer-group information. Bitstream that may be processed in parallel may be processed in the decoder without the concatenation operation. 
     The transmission device according to the embodiments has the following effects. 
     For point cloud data, the transmission device may divide and transmit compressed data according to a specific criterion. When layered coding according to the embodiments is used, the compressed data may be divided and transmitted according to layers. Accordingly, the storage and transmission efficiency on the transmitting side may be increased. 
     Referring to  FIGS. 15 and 16 , the geometry and attributes of the point cloud data may be compressed and provided. In the PCC-based service, the compression rate or the amount of data may be adjusted according to the receiver performance or transmission environment. 
     In the case where point cloud data is configured in one slice, when the receiver performance or transmission environment changes, 1) a bitstream suitable for each environment may be transcoded and stored separately, and may be selected at the time of transmission, or 2) or the transcoding operation may be needed prior to transmission. In this case, if the number of receiver environments to be supported increases or the transmission environment frequently changes, issues related to the storage space or a delay resulting from transcoding may be raised. 
       FIG. 42  illustrates an example of efficient processing of a main region of point cloud data by a point cloud data transmission/reception device according to embodiments. 
     The transmission device  10002  of  FIG. 1 , the encoder  10002  of  FIG. 1 , the reception device of  FIG. 1 , the decoder  10006  of  FIG. 1 , the encoding and decoding of  FIG. 2 , the encoder of  FIG. 4 , the decoder of  FIG. 11 , the transmission device of  FIG. 12 , the reception device of  FIG. 13 , the XR device  1430  of  FIG. 14 , the encoder and decoder of  FIG. 15 , the encoder and decoder of  FIGS. 39 to 41 , and the like may support efficient encoding/decoding of a main region based on the ROI or encoding/decoding having different resolutions according to regions. As a method to support the same, a slice segment structure according to the embodiments may be used. Accordingly, the method/device according to the embodiments may provide effects such as spatial random access, ROI based region-wise data resolution, and increase in receiver efficiency. 
     For example, when the object that is the target of the point cloud data is a person, the head region of the person may be the region of interest, and the leg region may not be the region of interest. Data corresponding to the region of interest needs to have a high data resolution, and data not corresponding to the region of interest may have a low data resolution. Thereby, efficient data processing may be implemented. 
     The method/device according to the embodiments may support use cases requiring low latency or low complexity, such as live streaming or devices exhibiting low performance, through a layer-group structure and corresponding slice partitioning. For a device exhibiting low performance, decoding may be burdensome when the number of points or coding layers is large. In this case, a partial bitstream may be received and decoded using the scalable transmission enabled by slice partitioning. Thereby, required time and complexity may be reduced. However, the quality of the output point cloud data may be deteriorated because detailed layers are skipped. 
     In addition, if region-wise decoding can be performed by the decoder, complexity may be reduced while maintaining high quality in the region of interest (ROI). By changing the decoding depth according to the ROI, that is, by decoding the entire coding layers for the ROI and decoding fewer coding layers for the non-ROI, both low-performance and high-performance devices may effectively generate point cloud data. This may be a major use case for spatial random access applications that aim to provide direct access to the ROI in an efficient manner. Embodiments include a slice partitioning method for supporting layer-group structure-based spatial access. 
       FIG. 43  shows a layer group structure and a subgroup bounding box according to embodiments. 
     The transmission device  10002  of  FIG. 1 , the encoder  10002  of  FIG. 1 , the reception device of  FIG. 1 , the decoder  10006  of  FIG. 1 , the encoding and decoding of  FIG. 2 , the encoder of  FIG. 4 , the decoder of  FIG. 11 , the transmission device of  FIG. 12 , the reception device of  FIG. 13 , the XR device  1430  of  FIG. 14 , the encoder and decoder of  FIG. 15 , the encoder and decoder of  FIGS. 39 to 41 , and the like may apply slice partitioning in the layer-group structure as shown in  FIG. 43 . 
     In this example, 8 coding layers are provided, and coding of a lower layer depends on the coded information (i.e. occupancy) of the previous layer. In generating slice segments, the coding layers are grouped into three different layer groups, and a set of layer groups is the same as the set of coding layers. Also, the last two layer groups are divided into several subgroups. Layer group  2  has two subgroups and layer group  3  has four subgroups. The layer groups or subgroups are contained in 7 different slice segments, respectively. 
     Through such slice partitioning, the point cloud data reception device according to the embodiments may select a slice required for an application program, thereby improving decoding and rendering efficiency. For example, when an application requires only data of subgroup  3 - 3 , the receiver may select slice  6 , which contains data for subgroup  3 - 3 . In addition, considering the coding dependency between layers, preceding slices  1  and  3  for layer group  1  and subgroup  2 - 2  may be required. For the spatial access use case, it may be assumed that there is no dependency between subgroups of the same layer-group. Based on the slice partitioning, decoding complexity may be reduced due to fewer slices. 
     Subgroup bounding box according to embodiments: 
     Considering that the efficiency is obtained from slice selection before decoding, it is necessary to provide a description of the data of each slice in order to find a slice containing the target data. Embodiments propose that a signal be sent to a bounding box of data contained in a subgroup for the spatial access use case.  FIG. 43  shows a subgroup bounding box proposed in each layer group. Considering the node size of each coding layer, the boundary of all layer groups is the same as the bounding box of a sequence or frame. In addition, it is assumed that subgroup division is performed within the boundary of the preceding subgroup. Thus, the bounding boxes of subgroups  2 - 1  and  2 - 2  are in the bounding box of layer group  1 , and the bounding boxes of subgroups  3 - 1  and  3 - 2  and subgroups  3 - 3  and  3 - 4  may be in subgroups  2 - 1  and  2 - 2 . 
     A subgroup bounding box for layer-group  1  may correspond to a frame and/or a bounding box. 
     For the lower layer-group, the upper subgroup bounding box may be divided. That is, the set of lower subgroup bounding boxes is the subgroup bounding box of the upper layer-group. 
     When a bounding box (group) of subgroup  3 - 1  is required, only box (group)  3 - 1 , box (group)  2 - 1 , and box (group)  1  may be decoded. 
     When there is a subgroup bounding box of each subgroup, spatial access may be performed by comparing the bounding box of each slice with the ROI, selecting a slice whose subgroup bounding box is correlated with the ROI, and then decoding the selected slice. For example, suppose the ROI is in subgroup  3 - 3 . In this case, layer-group  1  and subgroups  2 - 2  and  3 - 3  may be selected by comparing the ROI with the subgroup bounding box. By decoding the corresponding slices  1 ,  3 , and  6 , efficient access to the ROI may be performed with high data resolution of subgroup  3 - 1  and low data resolution of other regions. For live streaming or low-latency usage, selection and decoding may be performed when receiving each slice segment. 
     The method/device according to the embodiments may signal subgroup bounding box information in a parameter set with a data unit header or layer group information to enable slice selection before decoding. Examples of the syntax of the above items are described below. 
     Information for slice selection according to embodiments may include not only a position range but also an attribute range, a normal vector range, and a type of attribute. 
     Signaling example according to embodiments: (Example of signaling information ( FIGS. 44 to 46 ) included in the bitstream of  FIG. 21 ) 
     According to an embodiment of the present disclosure, information on a separated slice may be defined in the parameter set as follows. It may be defined in a sequence parameter set, a geometry parameter set, an attribute parameter set, an SEI message, a geometry slice header, and an attribute slice header. Depending on the application and system, it may be defined in the corresponding or separate position to differently use the range and method to be applied. That is, a signal may have different meanings depending on the position where the signal is transmitted. If the signal is defined in the SPS, it may be equally applied to the entire sequence. If the signal is defined in the GPS, this may indicate that the signal is used for position reconstruction. If the signal is defined in the APS, this may indicate that the signal is applied to attribute reconstruction. If the signal is defined in the TPS, this may indicate that the signal is applied only to points within a tile. If the signal is delivered in a slice, this may indicate that the signal is applied only to the slice. In addition, the range and method to be applied may be defined in a corresponding position or a separate position depending on the application or system so as to be used differently. In addition, when the syntax elements defined below are applicable to multiple point cloud data streams as well as the current point cloud data stream, they may be carried in a superordinate parameter set. 
     While the embodiments define the information independently of the coding technique, the information may be defined in connection with the coding technique. In order to support regionally different scalability, the information may be defined in the tile parameter set. In addition, when syntax elements defined below are applicable not only to the current point cloud data stream but also to multiple point cloud data streams, they may be carried in a superordinate parameter set or the like. 
     Alternatively, a network abstract layer (NAL) unit may be defined and relevant information for selecting a layer, such as layer_id, may be delivered. Thereby, a bitstream may be selected at a system level. 
     Hereinafter, parameters (which may be referred to as metadata, signaling information, or the like) according to the embodiments may be generated in the process of the transmitter according to embodiments described below, and transmitted to the receiver according to the embodiments so as to be used in the reconstruction process. 
     For example, the parameters may be generated by a metadata processor (or metadata generator) of the transmission device according to the embodiments, which will be described later, and may be acquired by a metadata parser of the reception device according to the embodiments. 
     Consider slice segmentation with layer-group structure. In this example, there are 8 coding layers where the coding of the lower layers depends on the coded information (e.g., occupancy) of the previous layers. In creating slice segments, the coding layers are grouped into 3 different layer-groups, where the aggregation of the layer-groups is the same as the entire coding layers. In addition, the second and the third layer-groups are divided into multiple subgroups: the layer-group  2  is divided into 2 subgroups and the layer-group  3  is divided into 4 subgroups. Each layer-group or subgroup is contained in the different slices segments. Consider slice segmentation with layer-group structure. In this example, there are 8 coding layers where the coding of the lower layers depends on the coded information (e.g., occupancy) of the previous layers. In creating slice segments, the coding layers are grouped into 3 different layer-groups, where the aggregation of the layer-groups is the same as the entire coding layers. In addition, the second and the third layer-groups are divided into multiple subgroups: the layer-group  2  is divided into 2 subgroups and the layer-group  3  is divided into 4 subgroups. Each layer-group or subgroup is contained in the different slices segments. 
     With the slice segments with layer-group structure, receivers could produce region-wise different resolution by partial decoding. For example, consider one application that needs the data in the subgroup  3 - 3 . In this case, receivers could decode slice  6  but not slices  4 ,  5 , and  7 . Due to the coding dependency between layers, the preceding slices are also required. Based on the slice segmentation, decoding complexity is reduced due to fewer number of slices. 
     One of the important thing to use the slice segmentation for the spatial access use case is how the receiver finds the slices it needs for the ROI. In this document, we propose to use subgroup bounding box to describe the data distribution in the slice. In  FIG. 1( b ) , the proposed subgroup bounding boxes in each layer-group is illustrated. Considering the node size of each coding layer, the boundary of all layer-group is identical to the bounding box of the sequence or the frame. Also, it is assumed that the subgroup division is performed within the boundary of the preceding subgroups. Therefore, the bounding boxes of the subgroups  2 - 1  and  2 - 2  are within the bounding box of layer-group  1 . Also, the bounding boxes of the subgroups  3 - 1  and  3 - 2  and the subgroups  3 - 3  and  3 - 4  are within the boundaries of the subgroup  2 - 1  and  2 - 2 , respectively. 
     Given the subgroup bounding box, the spatial access could be performed through the process of comparing each slice&#39;s bounding box with the ROI, selecting the slices whose subgroup bounding box is correlated with ROI, and then decoding the selected slices. In our example, slices  1 ,  3 , and  6  will be selected as the ROI is within the subgroup bounding box of the layer-group  1 , subgroup  2 - 2 , and  3 - 3 , respectively. By decoding selected slices, the output point cloud showing high data resolution for ROI and low data resolution for the other regions is produced. Note that, it is assumed that there is no dependency between subgroups in the same layer-group for effective spatial access. In case of the live streaming or low latency use case, the selection and decoding could be performed at the time of receiving each slice segments which will increase time efficiency. 
       FIG. 44  shows a geometry parameter set according to embodiments. 
       FIG. 45  shows an attribute parameter set according to embodiments. 
     The parameters in  FIGS. 44 and 45  are generated and delivered in the bitstream of  FIG. 21  by the encoder according to the embodiments of  FIG. 1  and the like, and are parsed by the decoder according to the embodiments of  FIG. 1  and the like. 
     num_layer_groups_minus1 plus 1 specifies the number of layer groups where the layer group represents a group of consecutive tree layers that are part of the geometry (or attribute) coding tree structure. num_layer_groups_minus1 may be in the range of 0 to the number of coding tree layers. 
     layer_group_id specifies the layer group identifier of the i-th geometry or attribute layer group. 
     num_tree_depth_minus1 plus 1 specifies the number of tree depth contained in the i-th layer-group. The total number of tree depth may be derived by adding all (num_tree_depth_minus1[i]+1) for i equal to 0 to num layer groups minus1. 
     num_subgroups_minus1 plus 1 specifies the number of sub-groups in the i-th layer group. 
     subgroup_id specifies the indicator of the j-th subgroup of the i-th layer group indicated by layer_group_id. 
     subgroup_bbox_origin specifies the origin of the subgroup bounding box of the j-th subgroup of the i-th layer group. It may have a value close to the xyz origin among the 8 vertices of the bounding box. 
     subgroup_bbox_size specifies the size of the subgroup bounding box of the j-th subgroup of the i-th layer-group. It may have the distance from the bounding box origin to the maximum value along each axis. The unit indicating the origin and size may be represented based on the leaf node size. If another representation unit is used, it may be signaled. 
     aligned_layer_group_structure_flag equal to 1 specifies that the layer-group and subgroup structure of the attribute slices is identical to the geometry layer-group and subgroup structure. aligned_layer_group_structure flag equal to 0 specifies that the layer-group and subgroup structure of the attribute slices may not be identical to the geometry layer-group and subgroup structure. 
     geom_parameter_set_id specifies the geometry parameter set identifier that contains the layer-group and subgroup structure information that is aligned with the attribute layer-group structure. 
     Number of child subgroups (num_child_subgroups_minus1): Indicates the number of subgroups in the j-th subgroup of the i-th hierarchical group. 
     child_subgroup_id specifies the identifier for the child subgroup of the j-th subgroup of the i-th layer-group. 
       FIG. 46  shows a geometry data unit header and an attribute data unit header according to embodiments. 
       FIG. 46  shows parameter information included in the bitstream of  FIG. 21 . 
     For the parameters included in  FIG. 46 , refer to the description of  FIGS. 44 and 45 . 
     Referring to  FIG. 15 , the point cloud data transmission device according to the embodiments may provide the following effects. 
     For point cloud data, the transmission device may divide and transmit compressed data according to an criterion according to embodiments. For example, when layered coding is used, the compressed data may be divided and transmitted according to layers. In this case, the storage and transmission efficiency on the transmitting side may be increased. 
       FIG. 15  illustrates an embodiment in which the geometry and attributes of the point cloud data are compressed and provided. In the PCC-based service, the compression rate or the amount of data may be adjusted according to the receiver performance or transmission environment. In the case where point cloud data is bundled in one slice as in conventional cases, when the receiver performance or transmission environment changes, 1) a bitstream suitable for each environment may be transcoded and stored separately, and may be selected at the time of transmission, or 2) or the transcoding operation may be needed prior to transmission. In this case, if the number of receiver environments to be supported increases or the transmission environment frequently changes, issues related to the storage space or a delay resulting from transcoding may be raised. 
       FIG. 47  illustrates a method for transmitting and receiving point cloud data according to embodiments. 
     The transmission device  10002  of  FIG. 1 , the encoder  10002  of  FIG. 1 , the reception device of  FIG. 1 , the decoder  10006  of  FIG. 1 , the encoding and decoding of  FIG. 2 , the encoder of  FIG. 4 , the decoder of  FIG. 11 , the transmission device of  FIG. 12 , the reception device of  FIG. 13 , the XR device  1430  of  FIG. 14 , the encoder and decoder of  FIG. 15 , the encoder and decoder of  FIGS. 39 to 41 , and the like may transmit/receive the point cloud data by partitioning the data as shown in  FIG. 47 . Each component in  FIG. 47  may correspond to hardware, software, a processor, and/or a combination thereof. 
     When the compressed data is divided and transmitted according to layers according to the embodiments, only a necessary part of the pre-compressed data may be selectively transmitted in the bitstream stage without a separate transcoding process. This scheme may be efficient in terms of storage space as only one storage space per stream is required. It also enables efficient transmission in terms of (bitstream selector) bandwidth because only the necessary layers are selected before transmission. 
     The point cloud data reception method/device according to the embodiments may provide the following effects. 
       FIG. 48  illustrates a method for transmitting and receiving point cloud data according to embodiments. 
     The transmission device  10002  of  FIG. 1 , the encoder  10002  of  FIG. 1 , the reception device of  FIG. 1 , the decoder  10006  of  FIG. 1 , the encoding and decoding of  FIG. 2 , the encoder of  FIG. 4 , the decoder of  FIG. 11 , the transmission device of  FIG. 12 , the reception device of  FIG. 13 , the XR device  1430  of  FIG. 14 , the encoder and decoder of  FIG. 15 , the encoder and decoder of  FIGS. 39 to 41 , and the like may transmit/receive the point cloud data by partitioning the data as shown in  FIG. 48 . Each component in  FIG. 48  may correspond to hardware, software, a processor, and/or a combination thereof. 
     Embodiments include a method of dividing and transmitting compressed data according to a specific criterion for point cloud data. When layered coding is used, the compressed data may be divided and transmitted according to layers. In this case, the efficiency of the receiving side may be increased. 
       FIG. 48  illustrates the operations at the transmitting and receiving sides in the case of transmission of point cloud data composed of layers. In this case, when information for reconstructing the entire PCC data is delivered regardless of the receiver performance, the receiver needs to reconstruct the point cloud data through decoding and then select only data corresponding to a required layer (data selection or sub-sampling). In this case, since the transmitted bitstream is already decoded, a delay may occur in the receiver aiming at low latency or decoding may fail depending on the receiver performance. 
     According to embodiments, when a bitstream is divided into slices and delivered, the receiver may selectively deliver the bitstream to the decoder according to the density of point cloud data to be represented according to decoder performance or an application field. In this case, since selection is made before decoding, decoder efficiency may be increased, and decoders of various performances may be supported. 
     Accordingly, the method/device for transmitting and receiving point cloud data according to the embodiments may provide an efficient spatial random access to point cloud data based on the proposed operations and signaling schemes. 
     Various elements of the embodiments may be implemented by hardware, software, firmware, or a combination thereof. Various elements in the embodiments may be executed by a single chip such as a single hardware circuit. According to embodiments, the element may be selectively executed by separate chips, respectively. According to embodiments, at least one of the elements of the embodiments may be executed in one or more processors including instructions for performing operations according to the embodiments. 
     The operations according to the above-described embodiments may be performed by the transmission device and/or the reception device according to the embodiments. The transmission/reception device may include a transmitter/receiver configured to transmit and receive media data, a memory configured to store instructions (program code, algorithms, flowcharts and/or data) for the processes according to the embodiments, and a processor configured to control the operations of the transmission/reception device. 
     The processor may be referred to as a controller or the like, and may correspond to, for example, hardware, software, and/or a combination thereof. The operations according to the above-described embodiments may be performed by the processor. In addition, the processor may be implemented as an encoder/decoder for the operations of the above-described embodiments. 
       FIG. 49  illustrates a method for transmitting point cloud data according to embodiments. 
     S 4900 : The point cloud data transmission method according to the embodiments may include encoding point cloud data. 
     The encoding may include the operations of the point cloud video encoder  10002  of  FIG. 1 , the transmission device  10000  of  FIG. 1 , the encoding  20001  of  FIG. 2 , the encoder of  FIG. 4 , the transmission device of  FIG. 12 , the XR device  1430  of  FIG. 14 , the scalable encoder of  FIG. 15 , the bitstream generation of  FIG. 21 , the (sub-)bitstream generator of  FIG. 39 , the region-wise (layer-wise) encoding/transmission, and the like. 
     S 4910 : The point cloud data transmission method may further include transmitting a bitstream including the point cloud data. 
     The transmission may include the operations of the transmitter  10003  of  FIG. 1 , the transmission  20002  of  FIG. 2 , and the bitstream transmission of  FIGS. 21 to 25 . 
       FIG. 50  illustrates a method for receiving point cloud data according to embodiments. 
     S 5000 : The point cloud data reception method according to the embodiments may include receiving a bitstream including point cloud data. 
     The reception may include the operations of the reception device  10004  of  FIG. 1 , the receiver  10005 , of  FIG. 1 , the reception  20002  according to the transmission of  FIG. 2 , and the bitstream reception of  FIGS. 21 to 25 . 
     S 5010 : The point cloud data reception method may further include decoding the point cloud data. 
     The decoding may include the operations of the point cloud video decoder  10006  of  FIG. 1 , the decoding  20003  of  FIG. 2 , the decoder of  FIGS. 10 and 11 , the reception device of  FIG. 13 , the XR device  1430  of  FIG. 14 , the decoder and scalable decoder of  FIG. 15 , the (sub-)bitstream classifier of  FIG. 40 , the reception/decoding process of  FIG. 41 , and the region-wise (layer-wise) reception/decoding of  FIGS. 42 to 48 . 
     According to embodiments, the point cloud data may be transmitted/received based on a slice/subgroup bounding box structure for spatial access. For example, points may be compressed and reconstructed by generating a subbounding box structure (including a hierarchical layered structure) of an upper layer group including lower subgroup bounding boxes. Signaling information indicating these operations may be generated and transmitted. 
     Referring to  FIG. 1 , a method for transmitting point cloud data according to embodiments may include encoding point cloud data, and transmitting a bitstream including the point cloud data. 
     Referring to  FIG. 42 , the encoding of the point cloud data may include encoding the point cloud data based on one or more regions. 
     Referring to  FIG. 43 , the encoding of the point cloud data may include encoding geometry data of the point cloud data, and encoding attribute data of the point cloud data, wherein the point cloud data may be represented based on a layered structure. 
     Referring to  FIG. 43 , a layer group and a sub-bounding box may have a dependent (inclusive) relationship with each other. For example, the point cloud data may be represented based on a tree having one or more depths, wherein the depth may correspond to a layer. A layer group including one or more layers may be generated. The layer group may include a subgroup of point cloud data contained in one or more layers. The subgroup may include a bounding box corresponding to a region of point cloud data. A bounding box for a subgroup corresponding to a lower layer may belong to a bounding box for a subgroup corresponding to an upper layer. 
     A group and a subgroup may be construed as concepts corresponding to each other. The term “sub” is construed as meaning a part. Similarly, the bounding box and the sub-bounding box may be construed as concepts corresponding to each other. 
     Referring to  FIG. 44 , layer/subgroup parameter information according to embodiments may be generated and transmitted/received. The bitstream may include information about a bounding box of a subgroup of a layer group for point cloud data. The bitstream may include information about a child subgroup of the subgroup of the layer group. 
     Referring to  FIG. 47 , a bitstream may be selectively transmitted based on layers. The encoding of the point cloud data may include encoding the point cloud data based on a layer structure for a region of the point cloud data, and the transmitting of the bitstream may include transmitting point cloud data for one or more layers. 
     A reception method/device according to the embodiments may correspond to the transmission method/device according to the embodiments, and may perform the reverse process of the operations thereof. 
     The method for receiving point cloud data may include receiving a bitstream including point cloud data, and decoding the point cloud data. The decoding of the point cloud data may include decoding the point cloud data based on one or more regions. The decoding of the point cloud data may include decoding geometry data of the point cloud data, and decoding attribute data of the point cloud data, wherein the point cloud data may be represented based on a layered structure. The point cloud data may be represented based on a tree having one or more depths, wherein the depth may correspond to a layer. A layer group including one or more layers may be generated. The layer group may include a subgroup of point cloud data contained in one or more layers. The subgroup may include a bounding box (which may be referred to as a subbounding box) corresponding to a region of point cloud data. A bounding box for a subgroup corresponding to a lower layer (referred to as a subbounding box) may belong to a bounding box for a subgroup corresponding to a higher layer. The bitstream may include information about a bounding box of a subgroup of a layer group for point cloud data. The bitstream may include information about a child subgroup of the subgroup of the layer group. 
     The receiving of the bitstream may include receiving point cloud data for one or more layers, and the decoding of the point cloud data may include decoding the point cloud data based on a layer structure for a region of the point cloud data. 
     The embodiments have been described in terms of a method and/or a device, and the description of the method and the description of the device may be applied complementary to each other. 
     Although the accompanying drawings have been described separately for simplicity, it is possible to design new embodiments by combining the embodiments illustrated in the respective drawings. Designing a recording medium readable by a computer on which programs for executing the above-described embodiments are recorded as needed by those skilled in the art also falls within the scope of the appended claims and their equivalents. The devices and methods according to embodiments may not be limited by the configurations and methods of the embodiments described above. Various modifications can be made to the embodiments by selectively combining all or some of the embodiments. Although preferred embodiments have been described with reference to the drawings, those skilled in the art will appreciate that various modifications and variations may be made in the embodiments without departing from the spirit or scope of the disclosure described in the appended claims. Such modifications are not to be understood individually from the technical idea or perspective of the embodiments. 
     Various elements of the devices of the embodiments may be implemented by hardware, software, firmware, or a combination thereof. Various elements in the embodiments may be implemented by a single chip, for example, a single hardware circuit. According to embodiments, the components according to the embodiments may be implemented as separate chips, respectively. According to embodiments, at least one or more of the components of the device according to the embodiments may include one or more processors capable of executing one or more programs. The one or more programs may perform any one or more of the operations/methods according to the embodiments or include instructions for performing the same. Executable instructions for performing the method/operations of the device according to the embodiments 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 a transitory CRM or other computer program products configured to be executed by one or more processors. In addition, the memory according to the embodiments may be used as a concept covering not only volatile memories (e.g., RAM) but also nonvolatile memories, flash memories, and PROMs. In addition, it may also be implemented in the form of a carrier wave, such as transmission over the Internet. In addition, the processor-readable recording medium may be distributed to computer systems connected over a network such that the processor-readable code may be stored and executed in a distributed fashion. 
     In the present disclosure, “/” and “,” should be interpreted as indicating “and/or.” For instance, the expression “A/B” may mean “A and/or B.” Further, “A, B” may mean “A and/or B.” Further, “A/B/C” may mean “at least one of A, B, and/or C.” Also, “A/B/C” may mean “at least one of A, B, and/or C.” Further, in this specification, the term “or” should be interpreted as indicating “and/or.” For instance, the expression “A or B” may mean 1) only A, 2) only B, or 3) both A and B. In other words, the term “or” used in this document should be interpreted as indicating “additionally or alternatively.” 
     Terms such as first and second may be used to describe various elements of the embodiments. However, various components according to the embodiments should not be limited by the above terms. These terms are only used to distinguish one element from another. 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. Use of these terms should be construed as not departing from the scope of the 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 context clearly dictates otherwise. 
     The terms used to describe the embodiments are used for the purpose of describing specific embodiments, and are not intended to limit the embodiments. As used in the description of the embodiments and in the claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. The expression “and/or” is used to include all possible combinations of terms. The terms such as “includes” or “has” are intended to indicate existence of figures, numbers, steps, elements, and/or components and should be understood as not precluding possibility of existence of additional existence of figures, numbers, steps, elements, and/or components. As used herein, conditional expressions such as “if” and “when” are not limited to an optional case and are intended to perform the related operation or interpret the related definition according to a specific condition when the specific condition is satisfied. 
     Operations according to the embodiments described in this specification may be performed by a transmission/reception device including a memory and/or a processor according to embodiments. The memory may store programs for processing/controlling the operations according to the embodiments, and the processor may control various operations described in this specification. The processor may be referred to as a controller or the like. In embodiments, operations may be performed by firmware, software, and/or combinations thereof. The firmware, software, and/or combinations thereof may be stored in the processor or the memory. 
     The operations according to the above-described embodiments may be performed by the transmission device and/or the reception device according to the embodiments. The transmission/reception device may include a transmitter/receiver configured to transmit and receive media data, a memory configured to store instructions (program code, algorithms, flowcharts and/or data) for the processes according to the embodiments, and a processor configured to control the operations of the transmission/reception device. 
     The processor may be referred to as a controller or the like, and may correspond to, for example, hardware, software, and/or a combination thereof. The operations according to the above-described embodiments may be performed by the processor. In addition, the processor may be implemented as an encoder/decoder for the operations of the above-described embodiments. 
     As described above, related details have been described in the best mode for carrying out the embodiments. 
     As described above, the embodiments are fully or partially applicable to a point cloud data transmission/reception device and system. 
     Those skilled in the art may change or modify the embodiments in various ways within the scope of the embodiments. 
     Embodiments may include variations/modifications within the scope of the claims and their equivalents.