Method, device and medium for point cloud coding and decoding

Abstract

The embodiment of the invention provides a method for point cloud coding and decoding. In the method, for a conversion between a current codec unit of a point cloud sequence and a bit stream of the point cloud sequence, a capture laser that captures a point in the current codec unit is determined. Based on the captured laser, at least one coordinate of the point in at least one direction is determined. A transformation is performed based on the updated at least one coordinate of the point.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to point cloud encoding and decoding technology, and more particularly to point cloud geometric coordinate correction. Background Art

[0002] A point cloud is a collection of data points in a three-dimensional (3D) plane, where each point has defined coordinates on the X, Y, and Z axes. Therefore, point clouds can be used to represent the physical content of a three-dimensional space. Point clouds have proven to be a promising way to represent 3D visual data for a variety of immersive applications, from augmented reality to self-driving cars.

[0003] Point cloud codec standards have evolved primarily through the development of the well-known MPEG organization. MPEG stands for Moving Picture Experts Group, which is one of the main standardization groups dealing with multimedia. In 2017, the MPEG 3D Graphics Codec Group (3DG) released a call for proposals (CFP) document to begin the development of a point cloud codec standard. The final standard will encompass two categories of solutions. Video-based point cloud compression (V-PCC or VPCC) is suitable for point sets with relatively uniform point distributions. Geometry-based point cloud compression (G-PCC or GPCC) is suitable for more sparse distributions. However, overall, there is a desire to further improve the codec efficiency of conventional point cloud codec techniques. Summary of the Invention

[0004] An embodiment of the present disclosure provides a method for point cloud encoding and decoding.

[0005] In a first aspect, a method for point cloud encoding and decoding is presented. The method includes: determining a capture laser that captures a point in the current encoding and decoding unit for a point cloud sequence and a bitstream of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the capture laser; and performing a conversion based on the at least one updated coordinate of the point. The method according to the first aspect of the present disclosure corrects the coordinates of the point based on the capture laser of the point. In this way, the effectiveness and efficiency of point cloud geometry encoding and decoding can be improved.

[0006] In a second aspect, a method for point cloud encoding and decoding is provided. The apparatus includes a processor and a non-volatile memory having instructions thereon. The instructions, when executed by the processor, cause the processor to perform the method according to the first aspect of the present disclosure.

[0007] In a third aspect, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores instructions for causing a processor to execute the method according to the first aspect of the present disclosure.

[0008] In a fourth aspect, another non-transitory computer-readable recording medium is provided. The non-transitory computer-readable recording medium stores a bitstream of a point cloud sequence generated by a method performed by a point cloud processing apparatus. The method includes: determining a capture laser that captures a point in a current codec unit of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the capture laser; and generating a bitstream based on the at least one updated coordinate of the point.

[0009] In a fifth aspect, a method for storing a bitstream of a point cloud sequence is provided. The method includes: determining a capture laser that captures a point in a current codec unit of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the capture laser; generating a bitstream based on the at least one updated coordinate of the point; and storing the bitstream in a non-transitory computer-readable recording medium.

[0010] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will become more apparent through the following detailed description with reference to the accompanying drawings.In the exemplary embodiments of the present disclosure, the same reference numerals generally refer to the same components.

[0012] Figure 1 is a block diagram illustrating an example point cloud encoding and decoding system that may utilize the techniques of this disclosure;

[0013] Figure 2 shows a block diagram illustrating an example point cloud encoder according to some embodiments of the present disclosure;

[0014] Figure 3 shows a block diagram illustrating an example point cloud decoder according to some embodiments of the present disclosure;

[0015] Figure 4 A flowchart of improved point cloud geometry encoding and decoding using LIDAR characteristics according to an embodiment of the present disclosure is shown;

[0016] Figure 5 Another flowchart of improved point cloud geometry encoding and decoding using LIDAR characteristics according to an embodiment of the present disclosure is shown;

[0017] Figure 6 A flowchart of a method for point cloud encoding and decoding according to an embodiment of the present disclosure is shown; and

[0018] Figure 7 A block diagram is shown of a computing device in which various embodiments of the present disclosure may be implemented.

[0019] Throughout the drawings, the same or similar reference numbers generally refer to the same or similar elements. DETAILED DESCRIPTION

[0020] The principles of the present disclosure will now be described with reference to some embodiments. It should be understood that these embodiments are described only for the purpose of illustrating and helping those skilled in the art to understand and implement the present disclosure, and do not imply any limitation on the scope of the present disclosure. In addition to the methods described below, the disclosure described herein can also be implemented in various ways.

[0021] In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0022] References in this disclosure to "one embodiment," "an embodiment," "an example embodiment," and the like indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment is required to include that particular feature, structure, or characteristic. Furthermore, these phrases do not necessarily refer to the same embodiment. Furthermore, when a particular feature, structure, or characteristic is described in conjunction with an example embodiment, it is intended that such feature, structure, or characteristic, whether or not explicitly described, be applicable to other embodiments and that it is within the knowledge of those skilled in the art to apply such feature, structure, or characteristic.

[0023] It should be understood that although the terms "first" and "second" and the like may be used herein to describe various elements, these elements should not be limited to these terms. These terms are only used to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element without departing from the scope of the example embodiments. As used herein, the term "and / or" includes any and all combinations of one or more of the listed terms.

[0024] The terms used herein are used only for the purpose of describing specific embodiments and are not intended to limit the example embodiments. As used herein, the singular forms "a," "an," and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the terms "comprise," "including," "having," "including," and / or "comprising" when used herein indicate the presence of the features, elements, and / or components, etc., but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof. Sample Environment

[0025] Figure 1is a block diagram illustrating an example point cloud codec system 100 that may utilize the techniques of the present disclosure. As shown, the point cloud codec system 100 may include a source device 110 and a destination device 120. The source device 110 may also be referred to as a point cloud codec device, and the destination device 120 may also be referred to as a point cloud decoding device. In operation, the source device 110 may be configured to generate encoded point cloud data, and the destination device 120 may be configured to decode the encoded point cloud data generated by the source device 110. The techniques of the present disclosure are generally directed to encoding and decoding (encoding and / or decoding) point cloud data, i.e., supporting point cloud compression. The codec may be effective in compressing and / or decompressing point cloud data.

[0026] Source device 100 and destination device 120 may include any of a variety of devices, including desktop computers, notebook (i.e., laptop) computers, tablet computers, set-top boxes, telephone handsets (such as smartphones and mobile phones), televisions, cameras, display devices, digital media players, video game consoles, video streaming devices, vehicles (e.g., land or sea vehicles, spacecraft, aircraft, etc.), robots, LIDAR devices, satellites, extended reality devices, etc. In some cases, source device 100 and destination device 120 may be equipped for wireless communication.

[0027] The source device 100 may include a data source 112, a memory 114, a GPCC encoder 116, and an input / output (I / O) interface 118. The destination device 120 may include an input / output (I / O) interface 128, a GPCC decoder 126, a memory 124, and a data consumer 122. According to the present disclosure, the GPCC encoder 116 of the source device 100 and the GPCC decoder 126 of the destination device 120 may be configured to apply the techniques of the present disclosure related to point cloud encoding and decoding. Therefore, the source device 100 represents an example of an encoding device, while the destination device 120 represents an example of a decoding device. In other examples, the source device 100 and the destination device 120 may include other components or arrangements. For example, the source device 100 may receive data (e.g., point cloud data) from an internal source or an external source. Similarly, the destination device 120 may be connected to an external data consumer interface instead of including the data consumer in the same device.

[0028] In general, data source 112 represents a source of point cloud data (i.e., raw, unencoded point cloud data) and can provide a continuous series of "frames" of point cloud data to GPCC encoder 116, which encodes the point cloud data for the frames. In some examples, data source 112 generates point cloud data. Data source 112 of source device 100 can include a point cloud acquisition device, such as any of a variety of cameras or sensors, for example, one or more video cameras, an archive containing previously acquired point cloud data, a 3D scanner, or a light detection and ranging (LIDAR) device, and / or a data feed interface that receives point cloud data from a data content provider. Thus, in some examples, data source 112 can generate point cloud data based on a signal from a LIDAR device. Alternatively or additionally, point cloud data can be computer-generated from a scanner, camera, sensor, or other data. For example, data source 112 can generate point cloud data, or produce a combination of real-time point cloud data, archived point cloud data, and computer-generated point cloud data. In each case, the GPCC encoder 116 encodes the acquired, pre-acquired, or computer-generated point cloud data. The GPCC encoder 116 can rearrange the frames of the point cloud data from the order in which they were received (sometimes referred to as "display order") to the codec order for encoding and decoding. The GPCC encoder 116 can generate one or more bitstreams comprising the encoded point cloud data. The source device 100 can then output the encoded point cloud data via the I / O interface 118 for receipt and / or retrieval by, for example, the I / O interface 128 of the destination device 120. The encoded point cloud data can be transmitted directly to the destination device 120 via the network 130A via the I / O interface 118. The encoded point cloud data can also be stored on the storage medium / server 130B for access by the destination device 120.

[0029] The memory 114 of the source device 100 and the memory 124 of the destination device 120 can represent general purpose memory. In some examples, the memory 114 and the memory 124 can store raw point cloud data, e.g., raw point cloud data from the data source 112 and raw, decoded point cloud data from the GPCC decoder 126. Additionally or alternatively, the memory 114 and the memory 124 can store software instructions executable by, for example, the GPCC encoder 116 and the GPCC decoder 126, respectively. Although the memory 114 and the memory 124 are shown separately from the GPCC encoder 116 and the GPCC decoder 126 in this example, it should be understood that the GPCC encoder 116 and the GPCC decoder 126 can also include internal memory for functionally similar or equivalent purposes. Furthermore, the memory 114 and the memory 124 can store encoded point cloud data, e.g., output from the GPCC encoder 116 and input to the GPCC decoder 126. In some examples, portions of memory 114 and memory 124 may be allocated as one or more buffers, e.g., to store raw point cloud data, decoded point cloud data, and / or encoded point cloud data. For example, memory 114 and memory 124 may store point cloud data.

[0030] I / O interface 118 and I / O interface 128 can represent a wireless transmitter / receiver, a modem, a wired networking component (e.g., an Ethernet card), a wireless communication component operating according to any of a variety of IEEE 802.11 standards, or other physical components. In examples where I / O interface 118 and I / O interface 128 include wireless components, I / O interface 118 and I / O interface 128 can be configured to transmit data, such as encoded point cloud data, according to a cellular communication standard (such as 4G, 4G-LTE (Long Term Evolution), Advanced LTE, 5G, etc.). In some examples where I / O interface 118 includes a wireless transmitter, I / O interface 118 and I / O interface 128 can be configured to transmit data, such as encoded point cloud data, according to other wireless standards (such as IEEE 802.11 specifications). In some examples, source device 100 and / or destination device 120 can include corresponding system-on-chip (SoC) devices. For example, source device 100 may include a SoC device for performing the functions attributed to GPCC encoder 116 and / or I / O interface 118 , and destination device 120 may include a SoC device for performing the functions attributed to GPCC decoder 126 and / or I / O interface 128 .

[0031] The techniques disclosed herein can be applied to encoding and decoding to support any of a variety of applications, such as communication between autonomous vehicles, communication between scanners, cameras, sensors and processing devices (e.g., local servers or remote servers), geographic mapping, or other applications.

[0032] The I / O interface 128 of the destination device 120 receives the encoded bitstream from the source device 110. The encoded bitstream may include signaling information defined by the GPCC encoder 116 and used by the GPCC decoder 126, such as syntax elements with values ​​representing a point cloud. The decoded data is used by the data consumer 122. For example, the data consumer 122 may use the decoded point cloud data to determine the position of a physical object. In some examples, the data consumer 122 may include a display for presenting an image based on the point cloud data.

[0033] The GPCC encoder 116 and the GPCC decoder 126 can each be implemented as any of a variety of suitable encoder circuit systems and / or decoder circuit systems, such as one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), discrete logic, software, hardware, firmware, or any combination thereof. When the technology is partially implemented in software, the device can store instructions for the software in a suitable non-transitory computer-readable medium and execute the instructions in hardware using one or more processors to perform the technology of the present disclosure. Each of the GPCC encoder 116 and the GPCC decoder 126 can be included in one or more encoders or decoders, either of which can be integrated as part of a combined encoder / decoder (CODEC) in the corresponding device. The device that includes the GPCC encoder 116 and / or the GPCC decoder 126 may include one or more integrated circuits, microprocessors, and / or other types of devices.

[0034] The GPCC encoder 116 and the GPCC decoder 126 may operate in accordance with a codec standard, such as the Video Point Cloud Compression (VPCC) standard or the Geometric Point Cloud Compression (GPCC) standard. Generally, the present disclosure may refer to the encoding and decoding of a frame (e.g., encoding and decoding) to include the process of encoding data or decoding data. The encoded bitstream typically includes a series of values ​​for syntax elements that represent codec decisions (e.g., codec mode).

[0035] A point cloud can contain a set of points in 3D space and can have attributes associated with the points. The attributes can be color information (such as R, G, B or Y, Cb, Cr), or reflectivity information, or other attributes. Point clouds can be collected by various cameras or sensors (such as LIDAR sensors and 3D scanners), and can also be computer-generated. Point cloud data is used in various applications, including but not limited to architecture (modeling), graphics (3D models for visualization and animation), and the automotive industry (LIDAR sensors to help navigation).

[0036] Figure 2 is a block diagram illustrating an example of a GPCC encoder 200 according to some embodiments of the present disclosure, which may be Figure 1 An example of a GPCC encoder 116 in the system 100 is shown. Figure 3 is a block diagram illustrating an example of a GPCC decoder 300 according to some embodiments of the present disclosure. The GPCC decoder 300 may be Figure 1 An example of the GPCC decoder 126 in the system 100 is shown.

[0037] In both the GPCC encoder 200 and the GPCC decoder 300, the point cloud position is first encoded and decoded. The attribute encoding and decoding depends on the decoded geometry. Figure 2 and Figure 3 , the region adaptive hierarchical transform (RAHT) unit 218, the surface approximation analysis unit 212, the RAHT unit 314, and the surface approximation synthesis unit 310 are options commonly used for category 1 data. The level of detail (LOD) generation unit 220, the lifting unit 222, the LOD generation unit 316, and the inverse lifting unit 318 are options commonly used for category 3 data. All other units are common between category 1 and category 3.

[0038] For category 3 data, the compressed geometry is typically represented as an octree from the root down to the leaf level for each voxel. For category 1 data, the compressed geometry is typically represented by a pruned octree (i.e., an octree from the root down to the leaf level for blocks larger than a voxel) plus a model for approximating the surface within each leaf node of the pruned octree. In this way, category 1 and category 3 data both share the octree codec mechanism, while category 1 data can additionally utilize a surface model to approximate the voxels within each leaf node. The surface model used is a triangulation of 1 to 10 triangles per block, resulting in a triangle soup. Therefore, category 1 geometry codecs are called trisoup geometry codecs, while category 3 geometry codecs are called octree geometry codecs.

[0039] exist Figure 2 In the example, the GPCC encoder 200 may include a coordinate transformation unit 202, a color transformation unit 204, a voxelization unit 206, an attribute transfer unit 208, an octree analysis unit 210, a surface approximation analysis unit 212, an arithmetic coding unit 214, a geometric reconstruction unit 216, a RAHT unit 218, an LOD generation unit 220, a lifting unit 222, a coefficient quantization unit 224 and an arithmetic coding unit 226.

[0040] like Figure 2 As shown in the example of , the GPCC encoder 200 can receive a set of locations and a set of attributes. The locations can include the coordinates of a point in the point cloud. The attributes can include information about the point in the point cloud, such as the color associated with the point in the point cloud.

[0041] The coordinate transformation unit 202 can apply a transformation to the coordinates of the point to transform the coordinates from the original domain to the transformed domain. This disclosure may refer to the transformed coordinates as transformed coordinates. The color transformation unit 204 can apply a transformation to convert the color information of the attribute to a different domain. For example, the color transformation unit 204 can convert the color information from the RGB color space to the YCbCr color space.

[0042] In addition, Figure 2 In the example of , the voxelization unit 206 may voxelize the transformed coordinates. Voxelization of the transformed coordinates may include quantizing and removing some points of the point cloud. In other words, multiple points of the point cloud may be grouped into a single "voxel", which may thereafter be treated as a point in some aspects. In addition, the octree analysis unit 210 may generate an octree based on the voxelized transformed coordinates. Additionally, in Figure 2 In the example of FIG, the surface approximation analysis unit 212 can analyze the points to potentially determine a surface representation of the set of points. The arithmetic coding unit 214 can perform arithmetic coding on syntax elements representing information about the octree and / or information about the surface determined by the surface approximation analysis unit 212. The GPCC encoder 200 can output these syntax elements in a geometry bitstream.

[0043] The geometric reconstruction unit 216 can reconstruct the transformed coordinates of points in the point cloud based on the octree, data indicating the surface determined by the surface approximation analysis unit 212, and / or other information. Due to voxelization and surface approximation, the number of transformed coordinates reconstructed by the geometric reconstruction unit 216 may differ from the original number of points in the point cloud. This disclosure may refer to the resulting points as reconstructed points. The attribute transfer unit 208 can transfer attributes of the original points of the point cloud to the reconstructed points of the point cloud data.

[0044] Furthermore, the RAHT unit 218 may apply RAHT coding to the attributes of the reconstruction points. Alternatively or additionally, the LOD generation unit 220 and the lifting unit 222 may apply LOD processing and lifting, respectively, to the attributes of the reconstruction points. The RAHT unit 218 and the lifting unit 222 may generate coefficients based on the attributes. The coefficient quantization unit 224 may quantize the coefficients generated by the RAHT unit 218 or the lifting unit 222. The arithmetic coding unit 226 may apply arithmetic coding to syntax elements representing the quantized coefficients. The GPCC encoder 200 may output these syntax elements in the attribute bitstream.

[0045] exist Figure 3 In the example, the GPCC decoder 300 may include a geometric arithmetic decoding unit 302, an attribute arithmetic decoding unit 304, an octree synthesis unit 306, an inverse quantization unit 308, a surface approximation synthesis unit 310, a geometric reconstruction unit 312, a RAHT unit 314, an LOD generation unit 316, an inverse lifting unit 318, a coordinate inverse transformation unit 320 and a color inverse transformation unit 322.

[0046] The GPCC decoder 300 may obtain a geometry bitstream and an attribute bitstream. The geometry arithmetic decoding unit 302 of the decoder 300 may apply arithmetic decoding (e.g., CABAC or other types of arithmetic decoding) to the syntax elements in the geometry bitstream. Similarly, the attribute arithmetic decoding unit 304 may apply arithmetic decoding to the syntax elements in the attribute bitstream.

[0047] The octree synthesis unit 306 may synthesize an octree based on syntax elements parsed from the geometry bitstream. In the case where surface approximation is used in the geometry bitstream, the surface approximation synthesis unit 310 may determine a surface model based on syntax elements parsed from the geometry bitstream and based on the octree.

[0048] Furthermore, the geometric reconstruction unit 312 may perform reconstruction to determine the coordinates of the points in the point cloud. The coordinate inverse transformation unit 320 may apply an inverse transformation to the reconstructed coordinates to convert the reconstructed coordinates (positions) of the points in the point cloud from the transformed domain back to the original domain.

[0049] Additionally, in Figure 3 In the example of , the inverse quantization unit 308 may inverse quantize the property value. The property value may be based on syntax elements obtained from the property bitstream (eg, including syntax elements decoded by the property arithmetic decoding unit 304).

[0050] Depending on how the attribute values ​​are encoded, the RAHT unit 314 may perform RAHT decoding to determine color values ​​for points in the point cloud based on the inverse quantized attribute values. Alternatively, the LOD generation unit 316 and the inverse lifting unit 318 may use a level of detail based technique to determine color values ​​for points in the point cloud.

[0051] In addition, Figure 3 In the example of FIG, the inverse color transform unit 322 can apply an inverse color transform to the color values. The inverse color transform can be the inverse of the color transform applied by the color transform unit 204 of the encoder 200. For example, the color transform unit 204 can transform the color information from the RGB color space to the YCbCr color space. Accordingly, the inverse color transform unit 322 can transform the color information from the YCbCr color space to the RGB color space.

[0052] Figure 2 and Figure 3 Various units are shown to help understand the operations performed by the encoder 200 and the decoder 300. These units can be implemented as fixed-function circuits, programmable circuits, or a combination thereof. Fixed-function circuits refer to circuits that provide specific functions and are preset with respect to the operations that can be performed. Programmable circuits refer to circuits that can be programmed to perform various tasks and provide flexible functionality in the operations that can be performed. For example, a programmable circuit can execute software or firmware that causes the programmable circuit to operate in a manner defined by the instructions of the software or firmware. Fixed-function circuits can execute software instructions (for example, to receive parameters or output parameters), but the types of operations performed by fixed-function circuits are generally immutable. In some examples, one or more of these units can be different circuit blocks (fixed-function or programmable), and in some examples, one or more of these units can be integrated circuits.

[0053] The following describes some exemplary embodiments of the present disclosure in detail. It should be understood that the section headings used in this document are for ease of understanding and do not limit the embodiments disclosed in a section to that section. In addition, although some embodiments are described with reference to GPCC or other specific point cloud codecs, the disclosed techniques are also applicable to other point cloud codec technologies. In addition, although some embodiments describe the point cloud encoding and decoding steps in detail, it should be understood that the corresponding decoding steps for de-encoding will be implemented by the decoder. 1. Brief Overview This disclosure relates to point cloud coding and decoding techniques. Specifically, it relates to point cloud geometric coordinate correction using LIDAR characteristics. These concepts can be applied individually or in various combinations to any point cloud coding standard or non-standard point cloud codec, such as the under-development geometry-based point cloud compression (G-PCC). 2. Abbreviation G-PCC geometry-based point cloud compression MPEG Moving Picture Experts Group 3DG 3D Graphics Codec Group CFP Call for Proposals V-PCC video-based point cloud compression DCM direct encoding and decoding mode IDCM inferred direct codec mode 3. Introduction MPEG, short for Moving Picture Experts Group, is one of the main standardization groups dealing with multimedia. In 2017, the MPEG 3D Graphics Codec Group (3DG) released a Call for Proposals (CFP) document to begin developing a point cloud codec standard. The final standard will include two categories of solutions. Video-based Point Cloud Compression (V-PCC) is suitable for point sets with relatively uniform distributions. Geometry-based Point Cloud Compression (G-PCC) is suitable for more sparse distributions. Both V-PCC and G-PCC support encoding and decoding for single point clouds and point cloud sequences. A point cloud can contain both geometric and attribute information. Geometric information describes the geometric position of data points. Attribute information records details about the data points, such as texture, normal vector, and reflectance. One of the key applications of point clouds is autonomous driving. In autonomous driving, point cloud data is primarily captured by LiDAR. Therefore, some key characteristics of LiDAR can be exploited to compress point clouds. For example, standard spinning LiDARs always consist of multiple laser diodes aligned vertically, resulting in an effective vertical (pitch) field of view. The entire unit can then rotate at a fixed speed along its vertical axis to provide a full 360-degree azimuth field of view. The pitch and azimuth angles of the laser beam can be used to compress point cloud geometric information. Point cloud codecs can handle various types of information in different ways. Typically, codecs include a number of optional tools to support encoding and decoding of geometric and attribute information, respectively. Among the geometry encoding and decoding tools in G-PCC, the following tools have a significant impact on point cloud geometry encoding and decoding performance. 3.1 Octree Geometry Compression In G-PCC, one of the important point cloud geometry encoding and decoding tools is octree geometry compression, which utilizes the spatial correlation of point cloud geometry. If the geometry encoding and decoding tool is enabled, the Axis-Aligned Bounding Box of the cube associated with the root node of the octree will be determined based on the point cloud geometry information. The bounding box will then be subdivided into 8 sub-cubes, which are associated with the 8 child nodes of the root node (cubes are equivalent to nodes below). An 8-bit code is then generated in a specific order to indicate whether the 8 child nodes contain points, with one bit associated with a node. The 8-bit code is named an occupancy code and will be transmitted by signal based on the occupancy information of neighboring nodes. Nodes that contain only points will be further subdivided into 8 child nodes. This process will be performed recursively until the node size is 1. Thus, the point cloud geometry information is converted into an occupancy code sequence. At the decoder side, the occupancy code sequence will be decoded and the point cloud geometry information can be reconstructed based on the occupancy code sequence. 3.2 Plane Mode Planar mode is a tool for more efficiently improving the occtree node occupancy codes. Before encoding or decoding a node's occupancy code, the node is individually judged to be suitable for planar mode based on specific applicability criteria in three dimensions. Take the z-axis as an example. If plane mode is applicable on the z-axis, a binary flag zIsPlanar is encoded and decoded to signal whether its occupied child nodes belong to the same horizontal plane. If zIsPlaner is true, an additional bit zPlanePosition is signaled to indicate whether the plane is the bottom or top plane, and the empty plane occupancy code can be ignored. Otherwise, the node continues the normal tree encoding and decoding process. Applicability is based on tracking the probability that the node encoded in the past is a plane, as follows. If and only if p planar ≥T and d local >3, then the node is applicable, where T is a user-defined probability threshold, and d local It is the local density that can be derived based on the information of neighboring nodes. When node occupancy is encoded (decoded) and / or node plane information is encoded (decoded), the probability p is updated as follows planar : p planar =(L×p planar +δ) / (L+1) where L=255, and δ is 1 if the encoded node is a plane, and 0 otherwise. The flag zIsPlaner is encoded and decoded using the three contexts based on the axis information using the binary arithmetic codec. If zIsPlaner is true, zPlanePosition is encoded and decoded using the binary arithmetic codec. 3.3 Inferred Direct Codec Mode (IDCM) Octree representations (or more generally any tree representation) are efficient at representing points with spatial correlations because the tree tends to decompose the high-order bits of the point coordinates. For an octree, each depth level refines the point coordinates within the child nodes by one bit per component, at a cost of 8 bits per refinement. Further compression is achieved by entropy encoding and decoding the partitioning information associated with each tree node. However, if an octree node contains isolated points, directly encoding and decoding their relative coordinates within the node is superior to the octree representation. Because no other points exist in the node, spatial correlation cannot be used. Directly encoding and decoding point coordinates within the node / child nodes is called direct encoding and decoding mode (DCM). Using DCM also reduces time complexity because the recursive octree partitioning process cannot be performed. In G-PCC, each node is judged to be suitable for DCM according to certain applicability conditions, which is called Inferred Direct Codec Mode (IDCM). If the node is suitable for DCM, a binary flag is encoded to signal to the node whether DCM is applied (flag = 1) or not (flag = 0). If the flag is equal to 1, the points belonging to the associated volume are directly encoded and decoded using DCM. Otherwise (flag is equal to 0), the tree encoding and decoding process continues for the current node. Currently, there are two applicability conditions for IDCM. Based on parent's suitability. At the parent node level there is only one occupied child (= current node), and a grandparent node has at most two occupied children (= parent node + possibly one other node). 6N applicability. There is only one occupied child (=current node) at the parent node level, and no occupied neighbors N (among the six neighbors that share faces with the current cube associated with the current node). 3.4 Angle Mode In G-PCC, angle mode is introduced to improve the compression of isolated point relative coordinates and planar positions in the IDCM. This can be used only for real-time LIDAR point cloud data. For standard spindle-type LIDAR, each laser has a fixed elevation angle and captures a fixed maximum number of points per rotation. Angle mode uses the previously fixed elevation angle of each laser. It uses the subnode elevation distance from the laser elevation angle to improve the compression of the binary occupancy codec by predicting the planar position in the planar mode and the z-coordinate bit in the DCM node. Angular mode is applied to nodes that meet elevation eligibility criteria, i.e., if the elevation dimension is below the minimum elevation delta between two adjacent lasers. If a node is eligibility, it is passed by only one laser in the elevation direction. Lasers passing the node's elevation angle are then found, and the elevation angles of several key points for the node are calculated. Based on the relationship between the key point elevation angles and the lasers passing the node's elevation angle, a context is determined to help encode and decode the z-coordinate in the DCM and the planar position of the z-axis in the planar mode. 3.5 azimuth mode Similar to the angle mode, the azimuth mode was introduced to improve the compression of the relative coordinates of isolated points in the IDCM and the planar position in the plane. It can also be used for real-time LIDAR point cloud data. The azimuth mode uses the prior information of a fixed maximum number of points to be captured per laser rotation. It uses the azimuth of the encoded node to improve the compression of the binary occupancy codec by predicting the x or y planar position of the planar mode and the x or y coordinate bits of the DCM node. In the current G-PCC, if a node is applicable to angle mode, it is also applicable to azimuth mode. If a node is applicable to azimuth mode, the index of the laser passing through the node is found. Based on the laser information and the azimuth of the already encoded node with the same laser as the current node, a predicted azimuth is determined. The azimuths of several key points of the node are then calculated. Based on the positional relationship between the azimuths of the key points and the predicted azimuth, a context is determined to help encode and decode the x-coordinate or y-coordinate bits in the DCM and the planar position of the x or y axis in the planar mode. 3.6 Geometric Quantization Geometry quantization is one of the important tools for compressing geometric information. It will significantly improve the geometric compression efficiency, but it will bring geometric distortion in coordinates, such as the accuracy of x, y, and z coordinates. 4. Question The existing designs for point cloud geometry encoding and decoding have the following problems: 1. In current G-PCC, geometric quantization significantly improves geometric compression efficiency, but it introduces distortion in the x, y, and z coordinates. At the same time, for LIDAR-captured point cloud data, there is some prior information that can be used to reduce the distortion of the geometric coordinates. Specifically, pitch angle information can be used to reduce the distortion of the z coordinate, and azimuth angle information can be used to reduce the distortion of the x and y coordinates. For example, the pitch angle of the decoded point's capture laser can be used to correct its z coordinate. For another example, the azimuth angle of the decoded point's capture laser beam can be used to correct its x and y coordinates. 5. Detailed solution In order to solve the above problems and some unmentioned problems, the following methods are disclosed. The embodiments should be considered as examples to explain the general concept and should not be interpreted in a narrow way. In addition, these embodiments can be applied alone or in combination in any way. 1) Propose a capture laser with a fixed point. a. In one example, the capture laser of the point may be a laser that captures the point when collecting point cloud data. b. In one example, the coordinates of the point may have been quantized. c. In one example, the captured laser at a point can be determined by searching the pitch angles of all lasers and comparing them with the pitch angle of a point. i. In one example, the capture laser of a point may be the capture laser with the smallest pitch angle difference with the point. ii. In one example, the pitch angle may be represented by an angle value. 1. In one example, the pitch angle of a point can be calculated based on its coordinates. a. In one example, the pitch angle θ of a point (x, y, z) can be calculated as follows, Where arctan() is the inverse tangent function. iii. In one example, the pitch angle may be represented by the tangent of the angle. 1. In one example, the pitch angle of a point can be replaced by its tangent value. In this case, the tangent value θ of the point (x, y, z) is T It can be calculated as follows: 2. In one example, the pitch angle of the laser can be replaced by the corresponding tangent value. d. In one example, the captured laser light at a point can be determined by searching for the corresponding values ​​of all laser light and comparing them with the corresponding values ​​at that point. i. In one example, the capture laser for a point may be the capture laser that has the smallest difference relative to the corresponding value for that point. ii. In one example, the corresponding value may be positively correlated with the pitch angle. iii. In one example, the corresponding value may be the tangent of the pitch angle. iv. In one example, the corresponding value may be a z-coordinate. v. In one example, the corresponding value can be calculated based on its coordinates. e. In one example, the capture laser can be determined by inheriting from a previous point. f. In one example, the determination may be derived at the encoder. g. In one example, the determination can be derived at the decoder. 2) It is proposed to correct the z coordinate of a point according to the pitch angle of the capture laser of the point. a. In one example, the base z coordinate of a point is obtained based on the pitch angle of the capturing laser of the point. i. In one example, the base z coordinate z of the point (x, y, z) b Will be obtained as follows, z b =f(x,y,θ) Where θ is the pitch angle of the capture laser, and f() is the function that can map the point to the pitch angle of its capture laser in the z direction. 1. In one example, the function could be 2. In one example, the function could be b. In one example, when calculating the base z coordinate, the laser head position displacement in the z direction can be added. i. In one example, the base z coordinate z of the point (x, y, z) b Will be obtained as follows, z b =f(x,y,θ)+z s Where θ is the pitch angle of the capture laser, f() is the function that can map the point to the pitch angle of its capture laser in the z direction, z s is the laser head position displacement in the z direction. 1. In one example, the function could be 2. In one example, the function could be c. In one example, the base z coordinate can directly replace the point's z coordinate. d. In one example, the base z-coordinate can replace the point's z-coordinate when certain conditions are met. i. In one example, one of the conditions may be that the difference between the z coordinate and the base z coordinate is less than a threshold. 1. In one example, the threshold value can be related to the geometric quantization step size. a. In one example, the threshold can be set to the geometric quantization step size. e. In one example, the z-coordinate of a point may be summed with a function of the difference between the z-coordinate and the base z-coordinate. i. In one example, the function can be a linear function, a power function, an exponential function, etc. f. In one example, the correction may be performed at the encoder. g. In one example, the correction may be performed at the decoder. 3) It is proposed to correct the x-coordinate or y-coordinate of a point according to the azimuth angle of the captured laser beam. a. In one example, each point is associated with a capturing laser beam. b. In one example, the base x-coordinate of a point will be obtained based on the azimuth angle of the capturing laser beam at that point. i. In one example, the base x coordinate x of the point (x, y, z) b Will be obtained as follows, in is the azimuth angle of the capture laser beam, and f() is a function that can map the point to the azimuth angle of the capture laser beam in the x direction. c. In one example, the base x-coordinate can directly replace the point's x-coordinate. d. In one example, the base x-coordinate can replace the point's x-coordinate when certain conditions are met. i. In one example, one of the conditions may be that the difference between x and the base x coordinate is less than a threshold. 1. In one example, the threshold value can be related to the geometric quantization step size. a. In one example, the threshold can be set to the geometric quantization step size. e. In one example, the base y-coordinate of a point will be obtained based on the azimuth angle of the capturing laser beam of the point. i. In one example, the base y coordinate y of the point (x,y,z) b Will be obtained as follows, in is the azimuth angle of the capture laser beam, and f() is a function that can map the point to the azimuth angle of the capture laser beam in the y direction. f. In one example, the base y coordinate can directly replace the point's y coordinate. g. In one example, the base y-coordinate can replace the point's y-coordinate when some conditions are met. i. In one example, one of the conditions may be that the difference between y and the base y coordinate is less than a threshold. 1. In one example, the threshold may be the geometric quantization step size. a. In one example, the threshold can be set to the geometric quantization step size. h. In one example, the correction may be performed at the encoder. i. In one example, the correction may be performed at the decoder. 4) It is proposed to correct the coordinates of a point only when it meets certain conditions. a. In one example, the coordinate may be an x-coordinate or / and a y-coordinate. b. In one example, the coordinate may be a z-coordinate. c. In one example, one of the conditions may be that quantization distortion does not result in finding a wrong trapping laser. i. In one example, for a point (x, y, z), one of the conditions can be: Where Qs is the geometric quantization step size, θ is the pitch angle of the capture laser, and θ n is the pitch angle of the previous laser or the next laser, and abs() is the absolute value function. ii. In one example, for a point (x, y, z), one of the conditions can be: Where Qs is the geometric quantization step size, θ is the pitch angle of the capture laser, and θ n is the pitch angle of the previous laser or the next laser, and abs() is the absolute value function. d. In one example, one of the conditions may be that quantization distortion does not result in finding a wrong capture laser beam. i. In one example, the trapping laser beam may be found after the trapping laser has already been found. e. The above conditions can be used independently or in combination to constrain the correction of coordinates. 5) It is proposed to use at least one indicator (eg, a binary value) to indicate whether the prior information from LIDAR is used to correct the coordinates. a. In one example, the prior information may be the pitch angle information of the laser. b. In one example, the prior information may be the azimuth angle of the laser beam. c. In one example, the coordinate may be an x-coordinate or / and a y-coordinate. d. In one example, the coordinate may be a z-coordinate. e. In one example, the coordinates may be the coordinates of a decoded point cloud. f. In one example, the indicator may be consistent within a codec unit. i. In one example, the encoding and decoding unit may be a frame. ii. In one example, the coding unit may be a slice. iii. In one example, the coding unit may be a slice. iv. In one example, the encoding / decoding unit may be a group of frames (GOF). v. In one example, the encoding and decoding unit can be a point cloud sequence. g. In one example, the indicator may be signaled in the bitstream. i. Alternatively, the indicator may be inferred at the decoder and / or encoder. h. In one example, the indicator may be conditionally signaled. i. In one example, an indicator may be signaled only if the proposed coordinate correction is allowed. 1. In one example, whether the proposed coordinate correction is allowed may depend on codec information. 2. In one example, whether the proposed coordinate correction is allowed is signaled. i. In one example, the indicator may be binarized using fixed-length codec, EG codec, (truncation) unary codec, etc. j. In one example, the indicator may be encoded and decoded using at least one context in arithmetic coding. k. In one example, the indicator may be bypassed for encoding and decoding. 6) It is proposed to perform geometric coordinate correction before attribute encoding and decoding. a. In one example, the attributes may be color, reflectivity, normal, etc. b. In one example, attribute encoding and decoding can rely on corrected geometric coordinates. 7) It is proposed to perform geometric coordinate correction after attribute encoding and decoding. a. In one example, the attributes may be color, reflectivity, normal, etc. b. In one example, attribute encoding and decoding may not rely on the corrected geometric coordinates. 8) Whether and / or Or how to apply the above method. 9) Whether and / or how to apply the above disclosed method may depend on the coded information, such as dimension, color format, color component, slice / picture type. 6. Examples Figure 4 An example flow chart of an encoding and decoding process 400 for point cloud geometry correction using LIDAR characteristics is depicted in FIG. As shown, at box 410, the point cloud geometry of the point cloud bitstream 401 is decoded. For example, the point cloud geometry may include the geometric coordinates of the points in the point cloud sequence. At box 420, the point cloud attributes of the point cloud bitstream 401 are decoded. At box 430, it is determined whether the geometric coordinates are modified. If the geometric coordinates are modified, then at box 440, the point cloud geometric coordinates are modified according to the LIDAR characteristics (such as pitch and azimuth information). Then, a reconstructed point cloud 441 can be output. Otherwise, if the geometric coordinates are not modified, the reconstructed point cloud 441 can be output. In another example, point cloud attribute encoding and decoding depends on the corrected geometric coordinates. Figure 5 Another example flow chart of an encoding process 500 for point cloud geometry correction using LIDAR characteristics is depicted in FIG. As shown, at box 510, the point cloud geometry of the point cloud bitstream 501 is decoded. For example, the point cloud geometry may include the geometric coordinates of a point in a point cloud sequence. At box 520, it is determined whether the geometric coordinates are modified. If the geometric coordinates are modified, then at box 530, the point cloud geometric coordinates are modified based on LIDAR characteristics (such as pitch and azimuth information). At box 540, the point cloud attributes of the point cloud bitstream 501 are decoded. Then, the reconstructed point cloud 441 can be output. Otherwise, if the geometric coordinates are not modified, then at box 540, the point cloud attributes of the point cloud bitstream 501 are decoded. Then, the reconstructed point cloud 541 can be output.

[0054] More details are discussed further below. Figure 6 A flowchart of a method 600 for point cloud encoding and decoding according to an embodiment of the present disclosure is shown. The method 600 is implemented for converting between a current encoding and decoding unit of a point cloud sequence and a bit stream of the point cloud sequence.

[0055] At block 610, a capture laser is determined for capturing a point in the current codec unit. At block 620, at least one coordinate of the point in at least one direction is updated based on the capture laser. As used herein, updating coordinates may be referred to as "correcting coordinates" or "correcting coordinates." In some embodiments, the at least one coordinate of the point may include at least one of the following: a first coordinate of the point in a first direction (such as the x coordinate), a second coordinate of the point in a second direction (such as the y coordinate), or a third coordinate of the point in a third direction (such as the z coordinate). The position of the point may be represented by (x, y, z).

[0056] At block 630, a conversion is performed based on the updated at least one coordinate of the point. In some embodiments, the conversion includes encoding the current codec unit into a bitstream. Alternatively or additionally, in some embodiments, the conversion includes decoding the current codec unit from the bitstream.

[0057] Method 600 enables the correction of point coordinates based on the captured laser light. In this way, the distortion of geometric coordinates can be reduced. Therefore, the effectiveness and efficiency of point cloud geometry encoding and decoding can be improved.

[0058] In some embodiments, the capture laser captures at least one point in the collected point cloud data, the at least one point including the point.

[0059] In some embodiments, the at least one coordinate of the point is quantized.

[0060] In some embodiments, determining the captured laser comprises: determining a plurality of differences between a plurality of measurement values ​​of the plurality of lasers and the measurement value of the point; and determining the captured laser based on the plurality of differences.

[0061] In some embodiments, the measurement value of the point or the measurement value of the laser among the multiple lasers includes at least one of the following: the pitch angle of the point or the laser, a value positively correlated with the pitch angle of the point or the laser, the tangent value of the pitch angle of the point or the laser, the coordinates of the point or the laser, or a value associated with the coordinates of the point or the laser.

[0062] In some embodiments, the pitch angle of the point is determined based on at least one coordinate of the point.

[0063] In some embodiments, the pitch angle of the point is determined by: Wherein, x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, z represents the third coordinate of the point in the third direction, θ represents the pitch angle of the point, and arctan() represents the inverse tangent measure.

[0064] In some embodiments, the tangent of the pitch angle at the point is determined by: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, z represents the third coordinate of the point in the third direction, and θ T Indicates the tangent of the point's pitch angle.

[0065] In some embodiments, the pitch angle of the point or the laser is replaced by the tangent value of the pitch angle of the point or the laser.

[0066] In some embodiments, the capture laser is a laser having the smallest difference among the plurality of differences.

[0067] In some embodiments, the capture laser is determined based on another capture laser of another codec unit that was encoded before the current codec unit. That is, the capture laser can be determined by inheriting from the previous point.

[0068] In some embodiments, the capture laser is determined by at least one of: an encoder or a decoder for conversion.

[0069] In some embodiments, updating at least one coordinate of the point includes: determining a revised third coordinate of the point based on a third coordinate of the point in a third direction and a pitch angle of a capture laser of the point; and updating the third coordinate based on the revised third coordinate. As used herein, the revised third coordinate may be referred to as a "base z."

[0070] In some embodiments, the corrected third coordinate of the point is determined based on a first metric that maps the point to the pitch angle of the capture laser in the third direction. For example, the base z coordinate z of the point (x, y, z) is b Will be obtained as follows, z b =f(x,y,θ) Where θ is the pitch angle of the capture laser, and f() is the function that can map the point to the pitch angle of its capture laser in the z direction.

[0071] In some embodiments, a revised third coordinate of the point is further determined based on the laser head position displacement in the third direction.For example, the revised third coordinate can be determined by adding the laser head position displacement to the value determined by the first metric.

[0072] In some embodiments, the first metric includes one of the following: or Wherein x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, and θ represents the pitch angle of the point.

[0073] In some embodiments, updating the third coordinate based on the revised third coordinate includes replacing the third coordinate of the point with the revised third coordinate.

[0074] In some embodiments, based on at least one condition being satisfied, the third coordinate of the point is replaced with a revised third coordinate.

[0075] In some embodiments, the at least one condition includes a condition that a difference between the third coordinate of the point and the revised third coordinate is less than a threshold value.

[0076] In some embodiments, the threshold is related to the step size of the geometric quantization.

[0077] In some embodiments, the threshold is the step size of the geometric quantization.

[0078] In some embodiments, updating the third coordinate based on the revised third coordinate includes: determining a metric value of a difference between the third coordinate of the point and the revised third coordinate based on the second metric; and updating the third coordinate based on the metric value.

[0079] In some embodiments, the second metric includes at least one of: a linear metric, a power metric, or an exponential metric.

[0080] In some embodiments, the third coordinate is updated by adding the metric value to the third coordinate.

[0081] In some embodiments, the third coordinate is updated by at least one of: an encoder or a decoder used for the conversion.

[0082] In some embodiments, updating at least one coordinate of a point includes determining an azimuth angle of a capture laser beam of a capture laser, the capture laser beam being associated with the point; and updating at least one of a first coordinate of the point in a first direction or a second coordinate of the point in a second direction based on the azimuth angle of the capture laser beam.

[0083] In some embodiments, updating the first coordinate of the point includes: determining a revised first coordinate of the point based on the azimuth; and updating the first coordinate based on the revised first coordinate. As used herein, the term “revised first coordinate” may be referred to as “base x”.

[0084] In some embodiments, the revised first coordinate is determined based on a third metric that maps the point to an azimuth angle of the capture laser beam in the first direction.

[0085] In some embodiments, updating the first coordinate based on the revised first coordinate includes replacing the first coordinate of the point with the revised first coordinate.

[0086] In some embodiments, based on at least one condition being satisfied, the first coordinates of the point are replaced with the revised first coordinates.

[0087] In some embodiments, the at least one condition includes a condition that a difference between the first coordinate of the point and the revised first coordinate is less than a threshold.

[0088] In some embodiments, the threshold is related to the step size of the geometric quantization.

[0089] In some embodiments, the threshold is the step size of the geometric quantization.

[0090] In some embodiments, updating the second coordinate of the point includes: determining a revised second coordinate of the point based on the azimuth; and updating the second coordinate based on the revised second coordinate. As used herein, the term "revised second coordinate" may be referred to as "base y."

[0091] In some embodiments, the corrected second coordinate is determined based on a fourth metric that maps the point to an azimuth angle of the capture laser beam in the second direction.

[0092] In some embodiments, updating the second coordinate based on the revised second coordinate includes replacing the second coordinate of the point with the revised second coordinate.

[0093] In some embodiments, based on at least one condition being satisfied, the second coordinate of the point is replaced with a revised second coordinate.

[0094] In some embodiments, the at least one condition includes a condition that a difference between the second coordinate of the point and the revised second coordinate is less than a threshold value.

[0095] In some embodiments, the threshold is related to the step size of the geometric quantization.

[0096] In some embodiments, the threshold is the step size of the geometric quantization.

[0097] In some embodiments, at least one of the first coordinate or the second coordinate is updated by at least one of: an encoder or a decoder used for the conversion.

[0098] In some embodiments, based on at least one condition being satisfied, at least one coordinate of the point is updated.

[0099] In some embodiments, the at least one coordinate includes at least one of the following: a first coordinate in the first direction, a second coordinate in the second direction, or a third coordinate in the third direction.

[0100] In some embodiments, the at least one condition includes a condition that the quantization distortion of the point is less than or equal to a first threshold associated with the determination of the captured laser. With this condition, the quantization distortion does not lead to finding a false captured laser.

[0101] In some embodiments, the at least one condition includes: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, Qs represents the step size of geometric quantization, θ represents the pitch angle of the capture laser, and θ n represents another pitch angle of another laser light preceding or following the capture laser light, and abs() represents an absolute value function.

[0102] In some embodiments, the at least one condition includes: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, Qs represents the step size of geometric quantization, θ represents the pitch angle of the capture laser, and θ n represents another pitch angle of another laser light preceding or following the capture laser light, and abs() represents an absolute value function.

[0103] In some embodiments, the at least one condition includes the condition that the quantization distortion of the point is less than or equal to a second threshold associated with determining the capture laser beam of the capture laser. For example, the condition may be that the quantization distortion does not result in finding a false capture laser beam.

[0104] It should be understood that these conditions and any other suitable conditions may be applied alone or in any combination.The scope of the present disclosure is not limited herein.

[0105] In some embodiments, the capture laser beam is determined after the capture laser is determined. That is, the capture laser beam can be found after the capture laser has been found.

[0106] In some embodiments, at least one coordinate of the point is updated based on a priori information of the laser system including at least one laser including a capture laser of the point.

[0107] In some embodiments, coordinates of points in the encoded point cloud are updated based on a priori information of a laser system whose at least one laser captured the points in the encoded point cloud.

[0108] In some embodiments, the prior information includes at least one of the following: pitch angle information of at least one laser, or azimuth angle information of at least one laser beam of at least one laser.

[0109] In some embodiments, the at least one coordinate includes at least one of the following: a first coordinate in the first direction, a second coordinate in the second direction, or a third coordinate in the third direction.

[0110] In some embodiments, at least one indicator indicates whether to update at least one coordinate based on a priori information, or whether to update coordinates of a point in the encoded point cloud based on a priori information.

[0111] In some embodiments, the at least one indicator is consistent across coding units. As an example, a coding unit comprises one of: a frame, a slice, a slice, a group of frames (GOF), or a point cloud sequence.

[0112] In some embodiments, the at least one indicator is determined by at least one of: an encoder or a decoder used for the conversion.

[0113] In some embodiments, at least one indicator is included in the bitstream.

[0114] In some embodiments, at least one indicator is included in the bitstream based on at least one condition being satisfied. In some embodiments, the at least one condition includes updating of at least one coordinate being allowed.

[0115] In some embodiments, whether updating of the at least one coordinate is allowed is based on codec information.

[0116] In some embodiments, whether updates to at least one coordinate are allowed is indicated in the bitstream.

[0117] In some embodiments, the at least one indicator is binarized using at least one of: a fixed length codec, an Exponential Golomb (EG) codec, a unary codec, or a truncated unary codec.

[0118] In some embodiments, the at least one indicator is encoded using at least one context in arithmetic coding.

[0119] In some embodiments, at least one indicator is bypass coded.

[0120] In some embodiments, updating the at least one coordinate is performed before encoding of the attribute of the current codec unit.

[0121] In some embodiments, the attribute information of the attribute codec includes at least one of the following: color information, reflectivity information, or normal information.

[0122] In some embodiments, the attribute codec is based on the updated at least one coordinate.

[0123] In some embodiments, updating the at least one coordinate is performed after encoding of the attribute of the current codec unit.

[0124] In some embodiments, the attribute information of the attribute codec includes at least one of the following: color information, reflectivity information, or normal information.

[0125] In some embodiments, the attribute information is encoded without using the updated at least one coordinate.

[0126] In some embodiments, information about whether and / or how to apply the method is included in at least one of: a frame, a block, a slice or an octree in a bitstream, or the bitstream.

[0127] In some embodiments, the information is based on coded information, for example, the coded information includes at least one of the following: dimension, color format, color component, slice type, or picture type.

[0128] According to another embodiment of the present disclosure, a non-transitory computer-readable recording medium is provided. The non-transitory computer-readable recording medium stores a bitstream of a point cloud sequence generated by a method performed by a point cloud encoding and decoding apparatus. In this method, a capture laser is determined for capturing a point in a current encoding and decoding unit of the point cloud sequence. At least one coordinate of the point in at least one direction is updated based on the capture laser. A bitstream is generated based on the at least one updated coordinate of the point.

[0129] According to further embodiments of the present disclosure, a method for storing a bitstream of a point cloud sequence is provided. In this method, a capture laser that captures a point in a current codec unit of the point cloud sequence is determined. At least one coordinate of the point in at least one direction is updated based on the capture laser. A bitstream is generated based on the updated at least one coordinate of the point. The bitstream is stored in a non-transitory computer-readable recording medium.

[0130] Implementations of the present disclosure may be described according to the following items, the features of which may be combined in any reasonable way.

[0131] Item 1. A method for point cloud encoding and decoding, comprising: determining a capture laser for capturing a point in a current encoding and decoding unit of a point cloud sequence and a bit stream of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the capture laser; and performing the conversion based on the at least one updated coordinate of the point.

[0132] Item 2. The method of Item 1, wherein the capture laser captures at least one point in the collected point cloud data, the at least one point including the point.

[0133] Clause 3. The method of clause 1 or clause 2, wherein the at least one coordinate of the point is quantized.

[0134] Item 4. The method of any one of Items 1 to 3, wherein determining the capture laser comprises: determining a plurality of differences between a plurality of measurement values ​​of a plurality of lasers and a measurement value of the point; and determining the capture laser based on the plurality of differences.

[0135] Item 5. A method according to Item 4, wherein the measurement value of the point or the measurement value of the laser among the multiple lasers includes at least one of the following: the pitch angle of the point or the laser, a value positively correlated with the pitch angle of the point or the laser, the tangent value of the pitch angle of the point or the laser, the coordinates of the point or the laser, or a value associated with the coordinates of the point or the laser.

[0136] Clause 6. The method of clause 5, wherein the pitch angle of the point is determined based on the at least one coordinate of the point.

[0137] Clause 7. The method of clause 6, wherein the pitch angle of the point is determined by: Wherein x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, z represents the third coordinate of the point in the third direction, θ represents the pitch angle of the point, and arctan() represents the inverse tangent measure.

[0138] Clause 8. The method of clause 5, wherein the tangent of the elevation angle of the point is determined by: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, z represents the third coordinate of the point in the third direction, and θ T Represents the tangent value of the pitch angle of the point.

[0139] Item 9. The method according to any one of Items 5 to 8, wherein the pitch angle of the point or the laser is replaced by the tangent of the pitch angle of the point or the laser.

[0140] Item 10. The method according to any one of Items 4 to 9, wherein the trapping laser is a laser having a smallest difference among the plurality of differences.

[0141] Item 11. The method according to any one of Items 1 to 3, wherein the capture laser is determined based on another capture laser of another codec unit that was encoded before the current codec unit.

[0142] Item 12. The method of any one of Items 1 to 11, wherein the trapping laser is determined by at least one of: an encoder or a decoder used for the conversion.

[0143] Item 13. A method according to any one of Items 1 to 12, wherein updating at least one coordinate of the point includes: determining a corrected third coordinate of the point based on a third coordinate of the point in a third direction and a pitch angle of the capture laser of the point; and updating the third coordinate based on the corrected third coordinate.

[0144] Item 14. The method of Item 13, wherein the modified third coordinate of the point is determined based on a first metric that maps the point to the pitch angle of the capture laser in the third direction.

[0145] Item 15. The method of Item 14, wherein the corrected third coordinate of the point is further determined based on a laser head position displacement in the third direction.

[0146] Item 16. The method of Item 15, wherein the modified third coordinate is determined by adding the laser head position displacement to a value determined by the first metric.

[0147] Clause 17. The method of any one of Clauses 14 to 16, wherein the first metric comprises one of: or Wherein x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, and θ represents the pitch angle of the point.

[0148] Item 18. The method of any one of Items 13 to 17, wherein updating the third coordinate based on the revised third coordinate comprises replacing the third coordinate of the point with the revised third coordinate.

[0149] Item 19. The method of Item 18, wherein the third coordinate of the point is replaced with the revised third coordinate based on at least one condition being satisfied.

[0150] Item 20. The method of Item 19, wherein the at least one condition comprises a condition that a difference between the third coordinate of the point and the modified third coordinate is less than a threshold.

[0151] Item 21. The method of Item 20, wherein the threshold is related to a step size of geometric quantization.

[0152] Item 22. The method of Item 20, wherein the threshold is a step size of geometric quantization.

[0153] Item 23. A method according to any one of Items 13 to 17, wherein updating the third coordinate based on the corrected third coordinate includes: determining a measurement value of the difference between the third coordinate of the point and the corrected third coordinate based on a second measurement; and updating the third coordinate based on the measurement value.

[0154] Item 24. The method of Item 23, wherein the second metric comprises at least one of: a linear metric, a power metric, or an exponential metric.

[0155] Clause 25. The method of clause 23 or clause 24, wherein the third coordinate is updated by adding the metric value to the third coordinate.

[0156] Item 26. A method according to any one of Items 13 to 25, wherein the third coordinate is updated by at least one of: an encoder or a decoder used for the conversion.

[0157] Item 27. A method according to any one of Items 1 to 26, wherein updating at least one coordinate of the point comprises: determining an azimuth angle of a capture laser beam of the capture laser, the capture laser beam being associated with the point; and updating at least one of a first coordinate of the point in a first direction or a second coordinate of the point in a second direction based on the azimuth angle of the capture laser beam.

[0158] Item 28. The method of Item 27, wherein updating the first coordinate of the point comprises: determining a revised first coordinate of the point based on the azimuth; and updating the first coordinate according to the revised first coordinate.

[0159] Item 29. The method of Item 28, wherein the corrected first coordinate is determined based on a third metric that maps the point to the azimuth angle of the capture laser beam in the first direction.

[0160] Item 30. The method of Item 28 or Item 29, wherein updating the first coordinate based on the modified first coordinate comprises replacing the first coordinate of the point with the corrected first coordinate.

[0161] Item 31. The method of Item 30, wherein the first coordinate of the point is replaced by a corrected first coordinate based on at least one condition being satisfied.

[0162] Item 32. The method of Item 31, wherein the at least one condition comprises a condition that a difference between the first coordinate of the point and the corrected first coordinate is less than a threshold.

[0163] Item 33. The method of Item 32, wherein the threshold is related to a step size of geometric quantization.

[0164] Item 34. The method of Item 32, wherein the threshold is a geometric quantization step size.

[0165] Item 35. The method of Item 27, wherein updating the second coordinate of the point comprises: determining a revised second coordinate of the point based on the azimuth; and updating the second coordinate based on the revised second coordinate.

[0166] Item 36. The method of Item 35, wherein the corrected second coordinate is determined based on a fourth metric that maps the point to the azimuth angle of the capture laser beam in the second direction.

[0167] Item 37. The method of Item 35 or Item 36, wherein updating the second coordinate based on the modified second coordinate comprises replacing the second coordinate of the point with the corrected second coordinate.

[0168] Item 38. The method of Item 37, wherein the second coordinate of the point is replaced with a modified second coordinate based on at least one condition being satisfied.

[0169] Item 39. The method of Item 38, wherein the at least one condition comprises a condition that a difference between the second coordinate of the point and the modified second coordinate is less than a threshold.

[0170] Item 40. The method of Item 39, wherein the threshold is related to a step size of geometric quantization.

[0171] Item 41. The method of Item 39, wherein the threshold is a step size of geometric quantization.

[0172] Item 42. A method according to any one of Items 27 to 41, wherein at least one of the first coordinate or the second coordinate is updated by at least one of: an encoder or a decoder used for the conversion.

[0173] Item 43. A method according to any one of Items 1 to 42, wherein said at least one coordinate of said point is updated based on at least one condition being satisfied.

[0174] Item 44. The method of Item 43, wherein the at least one coordinate comprises at least one of: a first coordinate in a first direction, a second coordinate in a second direction, or a third coordinate in a third direction.

[0175] Item 45. The method of Item 43 or Item 44, wherein the at least one condition comprises a condition that a quantization distortion of the point is less than or equal to a first threshold associated with the determination of the trapped laser.

[0176] Clause 46. The method of clause 43 or clause 44, wherein the at least one condition comprises: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, Qs represents the step size of geometric quantization, θ represents the pitch angle of the capture laser, and θ n represents another pitch angle of another laser preceding or following the trapping laser, and abs() represents an absolute value function.

[0177] Clause 47. The method of clause 43 or clause 44, wherein the at least one condition comprises: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, Qs represents the step size of geometric quantization, θ represents the pitch angle of the capture laser, and θ n represents another pitch angle of another laser light preceding or following the trapping laser light, and abs() represents an absolute value function.

[0178] Item 48. The method of Item 43 or Item 44, wherein the at least one condition comprises a condition that a quantization distortion of the point is less than or equal to a second threshold associated with determination of a capture laser beam of the capture laser.

[0179] Item 49. The method of Item 48, wherein the capture laser beam is determined after determining the capture laser.

[0180] Item 50. The method of any one of Items 1 to 49, wherein the at least one coordinate of the point is updated based on a priori information of a laser system comprising: at least one laser comprising the capture laser of the point.

[0181] Item 51. The method of Item 50, wherein coordinates of points in the encoded point cloud are updated based on the a priori information of the laser system, the at least one laser of the laser system capturing the points in the encoded point cloud.

[0182] Item 52. The method according to Item 50 or Item 51, wherein the prior information includes at least one of the following: pitch angle information of the at least one laser, or azimuth angle information of at least one laser beam of the at least one laser.

[0183] Item 53. The method according to any one of Items 50 to 52, wherein the at least one coordinate comprises at least one of: a first coordinate in a first direction, a second coordinate in a second direction, or a third coordinate in a third direction.

[0184] Item 54. The method of Item 51, wherein at least one indicator indicates whether to update the at least one coordinate based on the a priori information, or whether to update the coordinates of a point in the encoded point cloud based on the a priori information.

[0185] Item 55. The method of Item 54, wherein the at least one indicator is consistent across codec units.

[0186] Item 56. The method of Item 55, wherein the encoding / decoding unit comprises one of: a frame, a slice, a strip, a group of frames (GOF), or the point cloud sequence.

[0187] Item 57. A method according to any one of Items 54 to 56, wherein the at least one indicator is determined by at least one of: an encoder or a decoder used for the conversion.

[0188] Item 58. The method of any one of items 54 to 56, wherein the at least one indicator is included in the bitstream.

[0189] Item 59. The method of Item 58, wherein the at least one indicator is included in the bitstream based on at least one condition being satisfied.

[0190] Item 60. The method of Item 59, wherein the at least one condition comprises: updating of the at least one coordinate is allowed.

[0191] Item 61. The method of Item 60, wherein whether the update of the at least one coordinate is allowed is based on codec information.

[0192] Item 62. The method of Item 60, wherein whether the update to the at least one coordinate is allowed is indicated in the bitstream.

[0193] Item 63. A method according to any one of items 54 to 62, wherein the at least one indicator is binarized using at least one of the following: a fixed length codec, an Exponential Golomb (EG) codec, a unary codec, or a truncated unary codec.

[0194] Item 64. A method according to any one of items 54 to 62, wherein the at least one indicator is encoded using at least one context in arithmetic coding.

[0195] Item 65. A method according to any one of items 54 to 62, wherein the at least one indicator is bypass coded.

[0196] Item 66. A method according to any one of Items 1 to 65, wherein updating the at least one coordinate is performed before encoding of the attributes of the current encoding unit.

[0197] Item 67. The method according to Item 66, wherein the attribute information of the attribute codec includes at least one of the following: color information, reflectivity information or normal information.

[0198] Item 68. The method of Item 66 or Item 67, wherein the attribute encoding is based on the updated at least one coordinate.

[0199] Item 69. A method according to any one of Items 1 to 65, wherein updating the at least one coordinate is performed after encoding and decoding the attributes of the current encoding and decoding unit.

[0200] Item 70. The method according to Item 69, wherein the attribute information of the attribute codec includes at least one of the following: color information, reflectivity information, or normal information.

[0201] Item 71. The method of Item 70, wherein the attribute information is encoded and decoded without using the updated at least one coordinate.

[0202] Item 72. A method according to any one of items 1 to 71, wherein information about whether and / or how to apply the method is included in at least one of the following: a frame, a block, a slice or an octree in the bitstream, or the bitstream.

[0203] Item 73. The method of Item 72, wherein the information is based on encoded information.

[0204] Item 74. The method of Item 73, wherein the encoded information comprises at least one of: dimension, color format, color component, slice type, or picture type.

[0205] Item 75. A method according to any one of Items 1 to 74, wherein the converting comprises encoding the current codec unit into the bitstream.

[0206] Item 76. A method according to any one of Items 1 to 74, wherein the converting comprises decoding the current codec unit from the bitstream.

[0207] Item 77. An apparatus for point cloud encoding and decoding, comprising a processor and a non-volatile memory having instructions thereon, wherein the instructions, when executed by the processor, cause the processor to perform the method according to any one of items 1 to 76.

[0208] Item 78. A non-transitory computer-readable storage medium storing instructions that cause a processor to perform the method of any one of Items 1 to 76.

[0209] Item 79. A non-transitory computer-readable recording medium storing a bit stream of a point cloud sequence generated by a method performed by a point cloud processing device, wherein the method comprises: determining a capture laser that captures a point in a current codec unit of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the capture laser; and generating the bit stream based on the at least one updated coordinate of the point.

[0210] Item 80. A method for storing a bitstream of a point cloud sequence, comprising: determining a capture laser that captures a point in a current codec unit of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the capture laser; generating the bitstream based on the at least one updated coordinate of the point; and storing the bitstream in a non-transitory computer-readable recording medium. Example device

[0211] Figure 7 A block diagram of a computing device 700 in which various embodiments of the present disclosure may be implemented is shown. The computing device 700 may be implemented as a source device 110 (or GPCC encoder 116 or 200) or a destination device 120 (or GPCC decoder 126 or 300), or may be included in the source device 110 (or GPCC encoder 116 or 200) or the destination device 120 (or GPCC decoder 126 or 300).

[0212] It should be understood that Figure 7 The computing device 700 shown in FIG. 7 is for illustrative purposes only and is not intended to in any way imply any limitation on the functionality and scope of the disclosed embodiments.

[0213] like Figure 7 As shown, computing device 700 comprises a general purpose computing device 700. Computing device 700 may include at least one or more processors or processing units 710, memory 720, storage unit 730, one or more communication units 740, one or more input devices 750, and one or more output devices 760.

[0214] In some embodiments, the computing device 700 can be implemented as any user terminal or server terminal with computing capabilities. The server terminal can be a server, a large computing device, etc. provided by a service provider. The user terminal can be, for example, any type of mobile terminal, fixed terminal, or portable terminal, including a mobile phone, a station, a unit, a device, a multimedia computer, a multimedia tablet computer, an Internet node, a communicator, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a personal communication system (PCS) device, a personal navigation device, a personal digital assistant (PDA), an audio / video player, a digital camera / camcorder, a positioning device, a television receiver, a radio broadcast receiver, an e-book device, a gaming device, or any combination thereof, including accessories and peripherals of these devices, or any combination thereof. It is conceivable that the computing device 700 can support any type of interface to the user (such as a "wearable" circuit device, etc.).

[0215] The processing unit 710 may be a physical processor or a virtual processor and may implement various processes based on a program stored in the memory 720. In a multi-processor system, multiple processing units execute computer-executable instructions in parallel to increase the parallel processing capability of the computing device 700. The processing unit 710 may also be referred to as a central processing unit (CPU), a microprocessor, a controller, or a microcontroller.

[0216] The computing device 700 typically includes various computer storage media. Such media can be any media accessible by the computing device 700, including but not limited to volatile media and non-volatile media, or removable media and non-removable media. The memory 720 can be a volatile memory (e.g., registers, cache, random access memory (RAM)), a non-volatile memory (such as read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM) or flash memory) or any combination thereof. The storage unit 730 can be any removable or non-removable medium and can include machine-readable media, such as memory, flash drive, disk or other media that can be used to store information and / or data and can be accessed in the computing device 700.

[0217] The computing device 700 may also include additional removable / non-removable storage media, volatile / non-volatile storage media. Figure 7 Although not shown, a magnetic disk drive for reading from and / or writing to a removable nonvolatile magnetic disk, and an optical disk drive for reading from and / or writing to a removable nonvolatile optical disk may be provided. In this case, each drive may be connected to a bus (not shown) via one or more data medium interfaces.

[0218] The communication unit 740 communicates with another computing device via a communication medium. In addition, the functionality of the components in the computing device 700 can be implemented by a single computing cluster or multiple computing machines that can communicate via a communication connection. Thus, the computing device 700 can operate in a networked environment using logical connections to one or more other servers, networked personal computers (PCs), or other general-purpose network nodes.

[0219] Input device 750 may be one or more of various input devices, such as a mouse, keyboard, trackball, voice input device, and the like. Output device 760 may be one or more of various output devices, such as a display, speaker, printer, and the like. With the aid of communication unit 740, computing device 700 may also communicate with one or more external devices (not shown), such as storage devices and display devices, one or more devices that enable a user to interact with computing device 700, or, if desired, any device that enables computing device 700 to communicate with one or more other computing devices (e.g., a network card, a modem, and the like). Such communication may be performed via an input / output (I / O) interface (not shown).

[0220] In some embodiments, some or all components of the computing device 700 may also be arranged in a cloud computing architecture rather than being integrated into a single device. In a cloud computing architecture, components can be provided remotely and work together to implement the functionality described in this disclosure. In some embodiments, cloud computing provides computing, software, data access, and storage services without requiring the end user to know the physical location or configuration of the systems or hardware providing these services. In various embodiments, cloud computing provides services via a wide area network (such as the Internet) using appropriate protocols. For example, a cloud computing provider provides an application via a wide area network that can be accessed through a web browser or any other computing component. The software or components of the cloud computing architecture and the corresponding data can be stored on servers in a remote location. Computing resources in a cloud computing environment can be consolidated or distributed across remote data centers. Cloud computing infrastructure can provide services through shared data centers, although to users, they appear as a single access point. Therefore, cloud computing architecture can be used to provide the components and functionality described herein from a service provider in a remote location. Alternatively, the components and functionality described herein can be provided by a conventional server or installed directly or otherwise on a client device.

[0221] In embodiments of the present disclosure, computing device 700 may be used to implement point cloud encoding / decoding. Memory 720 may include one or more point cloud encoding / decoding modules 725 having one or more program instructions. These modules are accessible and executable by processing unit 710 to perform the functions of various embodiments described herein.

[0222] In an example embodiment of performing point cloud encoding, an input device 750 may receive point cloud data as input 770 to be encoded. The point cloud data may be processed, for example, by a point cloud encoding / decoding module 725 to generate an encoded bitstream. The encoded bitstream may be provided as output 780 via an output device 760.

[0223] In an example embodiment of performing point cloud decoding, an input device 750 may receive an encoded bitstream as input 770. The encoded bitstream may be processed, for example, by a point cloud codec module 725 to generate decoded point cloud data. The decoded point cloud data may be provided as output 780 via an output device 760.

[0224] Although the present disclosure has been specifically shown and described with reference to the preferred embodiments of the present disclosure, it will be understood by those skilled in the art that various changes in form and details may be made without departing from the spirit and scope of the present application as defined by the appended claims. Such variations are intended to be encompassed by the scope of the present application. Therefore, the foregoing description of the embodiments of the present application is not intended to be limiting.

Claims

1. A method for point cloud encoding and decoding, comprising: determining, for conversion between a current codec unit of a point cloud sequence and a bit stream of the point cloud sequence, a capture laser for capturing a point in the current codec unit; updating at least one coordinate of the point in at least one direction based on the captured laser; as well as The conversion is performed based on the at least one updated coordinate of the point. 2 . The method according to claim 1 , wherein the capture laser captures at least one point in the collected point cloud data, the at least one point including the point.

3. A method according to claim 1 or claim 2, wherein the at least one coordinate of the point is quantized.

4. The method according to any one of claims 1 to 3, wherein determining the trapped laser comprises: determining a plurality of differences between a plurality of metric values ​​of a plurality of lasers and a metric value of the point; as well as Based on the plurality of differences, the trapping laser is determined.

5. The method according to claim 4, wherein the measurement value of the point or the measurement value of the laser in the plurality of lasers comprises at least one of the following: the pitch angle of the point or the laser, A value positively correlated with the pitch angle of the point or the laser, the tangent value of the pitch angle of the point or the laser, the coordinates of the point or the laser, or A value associated with the coordinates of the point or the laser. The method of claim 5 , wherein the pitch angle of the point is determined based on the at least one coordinate of the point.

7. The method of claim 6, wherein the pitch angle of the point is determined by: Wherein x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, z represents the third coordinate of the point in the third direction, θ represents the pitch angle of the point, and arctan() represents the inverse tangent measure.

8. The method of claim 5, wherein the tangent of the pitch angle of the point is determined by: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, z represents the third coordinate of the point in the third direction, and θ T Represents the tangent value of the pitch angle of the point. 9 . The method according to claim 5 , wherein the pitch angle of the point or the laser is replaced by the tangent value of the pitch angle of the point or the laser. 10 . The method according to claim 4 , wherein the trapping laser is a laser having a smallest difference among the plurality of differences.

11. The method according to any one of claims 1 to 3, wherein the capture laser is determined based on another capture laser of another codec unit that was encoded before the current codec unit.

12. The method according to any one of claims 1 to 11, wherein the trapping laser is determined by at least one of: an encoder or a decoder used for the conversion.

13. The method according to any one of claims 1 to 12, wherein updating at least one coordinate of the point comprises: determining a corrected third coordinate of the point based on the third coordinate of the point in the third direction and the pitch angle of the capturing laser of the point; as well as Based on the corrected third coordinate, the third coordinate is updated.

14. The method of claim 13, wherein the modified third coordinate of the point is determined based on a first metric that maps the point to the pitch angle of the capture laser in the third direction.

15. The method of claim 14, wherein the corrected third coordinate of the point is determined further based on a laser head position displacement in the third direction.

16. The method of claim 15, wherein the modified third coordinate is determined by adding the laser head position displacement to a value determined by the first metric.

17. The method according to any one of claims 14 to 16, wherein the first metric comprises one of the following: or Wherein x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, and θ represents the pitch angle of the point.

18. The method according to any one of claims 13 to 17, wherein updating the third coordinate based on the corrected third coordinate comprises: The third coordinate of the point is replaced by the corrected third coordinate. The method of claim 18 , wherein the third coordinate of the point is replaced with the revised third coordinate based on at least one condition being satisfied. 20 . The method of claim 19 , wherein the at least one condition comprises a condition that a difference between the third coordinate of the point and the modified third coordinate is less than a threshold. The method according to claim 20 , wherein the threshold is related to a step size of geometric quantization. The method of claim 20 , wherein the threshold is a step size of geometric quantization.

23. The method according to any one of claims 13 to 17, wherein updating the third coordinate based on the revised third coordinate comprises: determining a metric value of a difference between the third coordinate of the point and a corrected third coordinate based on a second metric; as well as Based on the metric value, the third coordinate is updated.

24. The method of claim 23, wherein the second metric comprises at least one of: Linear metrics, Power metrics, or Index measurement.

25. The method of claim 23 or claim 24, wherein the third coordinate is updated by adding the metric value to the third coordinate.

26. The method of any one of claims 13 to 25, wherein the third coordinate is updated by at least one of: an encoder or a decoder used for the conversion.

27. The method of any one of claims 1 to 26, wherein updating at least one coordinate of the point comprises: determining an azimuth angle of a capture laser beam of the capture laser, the capture laser beam being relative to the point; as well as At least one of a first coordinate of the point in the first direction or a second coordinate of the point in the second direction is updated based on the azimuth angle of the capture laser beam.

28. The method of claim 27, wherein updating the first coordinate of the point comprises: determining a revised first coordinate of the point based on the azimuth; as well as The first coordinate is updated according to the corrected first coordinate.

29. The method of claim 28, wherein the corrected first coordinate is determined based on a third metric that maps the point to the azimuth angle of the capture laser beam in the first direction.

30. The method of claim 28 or claim 29, wherein updating the first coordinate based on the modified first coordinate comprises: The first coordinate of the point is replaced by the corrected first coordinate. The method of claim 30 , wherein the first coordinate of the point is replaced by a revised first coordinate based on at least one condition being satisfied.

32. The method of claim 31, wherein the at least one condition comprises a condition that a difference between the first coordinate of the point and the revised first coordinate is less than a threshold. The method of claim 32 , wherein the threshold is related to a step size of geometric quantization.

34. The method of claim 32, wherein the threshold is a geometric quantization step size.

35. The method of claim 27, wherein updating the second coordinate of the point comprises: determining a revised second coordinate of the point based on the azimuth; as well as Based on the corrected second coordinate, the second coordinate is updated.

36. The method of claim 35, wherein the corrected second coordinate is determined based on a fourth metric that maps the point to the azimuth angle of the capture laser beam in the second direction.

37. The method of claim 35 or claim 36, wherein updating the second coordinate based on the modified second coordinate comprises: The second coordinate of the point is replaced by the corrected second coordinate.

38. The method of claim 37, wherein the second coordinate of the point is replaced with a modified second coordinate based on at least one condition being satisfied.

39. The method of claim 38, wherein the at least one condition comprises a condition that a difference between the second coordinate of the point and the modified second coordinate is less than a threshold.

40. The method of claim 39, wherein the threshold is related to a step size of geometric quantization.

41. The method of claim 39, wherein the threshold is a step size of geometric quantization.

42. The method of any one of claims 27 to 41, wherein at least one of the first coordinate or the second coordinate is updated by at least one of: an encoder or a decoder used for the conversion.

43. The method of any one of claims 1 to 42, wherein the at least one coordinate of the point is updated based on at least one condition being satisfied.

44. The method of claim 43, wherein the at least one coordinate comprises at least one of: The first coordinate in the first direction, a second coordinate in the second direction, or The third coordinate in the third direction.

45. The method of claim 43 or claim 44, wherein the at least one condition comprises a condition that a quantization distortion of the point is less than or equal to a first threshold associated with the determination of the trapped laser.

46. ​​The method of claim 43 or claim 44, wherein the at least one condition comprises: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, Qs represents the step size of geometric quantization, θ represents the pitch angle of the capture laser, and θ n represents another pitch angle of another laser preceding or following the trapping laser, and abs() represents an absolute value function.

47. The method of claim 43 or claim 44, wherein the at least one condition comprises: Where x represents the first coordinate of the point in the first direction, y represents the second coordinate of the point in the second direction, Qs represents the step size of geometric quantization, θ represents the pitch angle of the capture laser, and θ n represents another pitch angle of another laser light preceding or following the trapping laser light, and abs() represents an absolute value function.

48. The method of claim 43 or claim 44, wherein the at least one condition comprises the condition that a quantization distortion of the point is less than or equal to a second threshold associated with determination of a capture laser beam of the capture laser.

49. The method of claim 48, wherein the capture laser beam is determined after determining the capture laser.

50. The method of any one of claims 1 to 49, wherein the at least one coordinate of the point is updated based on a priori information of a laser system including at least one laser including the capturing laser of the point.

51. The method of claim 50, wherein coordinates of points in the encoded point cloud are updated based on the a priori information of the laser system whose at least one laser captured a point in the encoded point cloud.

52. The method of claim 50 or claim 51, wherein the prior information comprises at least one of the following: The elevation angle information of the at least one laser, or Azimuth angle information of at least one laser beam of the at least one laser.

53. The method of any one of claims 50 to 52, wherein the at least one coordinate comprises at least one of: The first coordinate in the first direction, a second coordinate in the second direction, or The third coordinate in the third direction.

54. The method of claim 51, wherein at least one indicator indicates whether to update the at least one coordinate based on the a priori information, or whether to update the coordinates of a point in the encoded point cloud based on the a priori information.

55. The method of claim 54, wherein the at least one indicator is consistent across a codec unit.

56. The method of claim 55, wherein the codec unit comprises one of the following: A frame, a slice, a strip, a group of frames (GOF), or a sequence of the point cloud.

57. The method of any one of claims 54 to 56, wherein the at least one indicator is determined by at least one of: an encoder or a decoder used for the conversion.

58. The method of any one of claims 54 to 56, the at least one indicator being included in the bitstream.

59. The method of claim 58, wherein the at least one indicator is included in the bitstream based on at least one condition being satisfied.

60. The method of claim 59, wherein the at least one condition comprises: Updates to the at least one coordinate are permitted.

61. The method of claim 60, wherein whether the update of the at least one coordinate is allowed is based on codec information.

62. The method of claim 60, wherein whether the update to the at least one coordinate is allowed is indicated in the bitstream.

63. The method of any one of claims 54 to 62, wherein the at least one indicator is binarized using at least one of: Fixed-length codec, Exponential Columbus (EG) codec, Unary codec, or Truncated unary encoding and decoding.

64. The method according to any one of claims 54 to 62, wherein the at least one indicator is coded using at least one context in arithmetic coding.

65. The method of any one of claims 54 to 62, wherein the at least one indicator is bypass coded.

66. The method according to any one of claims 1 to 65, wherein updating the at least one coordinate is performed before attribute encoding of the current encoding unit.

67. The method according to claim 66, wherein the attribute information of the attribute codec includes at least one of the following: Color information, reflectivity information, or normal information.

68. The method of claim 66 or claim 67, wherein the attribute codec is based on the updated at least one coordinate.

69. The method according to any one of claims 1 to 65, wherein updating the at least one coordinate is performed after attribute encoding of the current encoding unit.

70. The method according to claim 69, wherein the attribute information of the attribute codec includes at least one of the following: Color information, reflectivity information, or normal information.

71. The method of claim 70, wherein the attribute information is encoded and decoded without using the updated at least one coordinate.

72. The method of any one of claims 1 to 71, wherein information about whether and / or how to apply the method is included in at least one of: A frame, a block, a slice or an octree in the bitstream, or the bitstream.

73. The method of claim 72, wherein the information is based on coded information.

74. The method of claim 73, wherein the encoded information comprises at least one of: Dimensions, color format, color components, stripe type, or picture type.

75. The method of any one of claims 1 to 74, wherein the converting comprises encoding the current codec unit into the bitstream.

76. The method of any one of claims 1 to 74, wherein the converting comprises decoding the current codec unit from the bitstream.

77. An apparatus for point cloud encoding and decoding, comprising a processor and a non-volatile memory having instructions thereon, wherein the instructions, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 76.

78. A non-transitory computer-readable storage medium storing instructions, the instructions causing a processor to execute the method according to any one of claims 1 to 76.

79. A non-transitory computer-readable recording medium storing a bit stream of a point cloud sequence generated by a method performed by a point cloud processing apparatus, wherein the method comprises: Determining a capture laser that captures a point in a current encoding / decoding unit of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the captured laser; as well as The bitstream is generated based on the at least one updated coordinate of the point.

80. A method for storing a bitstream of a point cloud sequence, comprising: Determining a capture laser that captures a point in a current encoding / decoding unit of the point cloud sequence; updating at least one coordinate of the point in at least one direction based on the captured laser; generating the bitstream based on the at least one updated coordinate of the point; as well as The bitstream is stored in a non-transitory computer-readable recording medium.

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