Method, apparatus and medium for point cloud coding

Abstract

An embodiment of the present disclosure provides a solution for point cloud coding. A method for point cloud coding is proposed, the method comprising: performing a conversion between a current point cloud frame of a point cloud sequence and a bitstream of the point cloud sequence, where a first slice in the current point cloud frame is directly dependent only by a single dependent slice.

Description

[Technical Field]

[0001] FIELD Embodiments of the present disclosure relate generally to point cloud coding techniques, and more particularly to slices and parameter sets in geometry-based point cloud compression. [Background technology]

[0002] A point cloud is a collection of individual data points in a three-dimensional (3D) plane, with each point having set coordinates on the X, Y, and Z axes. Point clouds can therefore be used to represent physical content in three-dimensional space. Point clouds have shown to be a promising way to represent 3D visual data for a wide range of immersive applications, from augmented reality to autonomous vehicles.

[0003] Point cloud coding standards have evolved primarily through developments within the well-known MPEG organization. MPEG stands for Moving Picture Experts Group and is one of the major standardization groups dealing with multimedia. In 2017, the MPEG 3D Graphics Coding Group (3DG) issued a Call for Proposals (CFP) document to initiate the development of a point cloud coding standard. The final standard will consist of two classes of solutions: video-based point cloud compression (V-PCC or VPCC) is suitable for point sets with a relatively uniform distribution of points; geometry-based point cloud compression (G-PCC or GPCC) is suitable for more sparse distributions. However, the coding efficiency of traditional point cloud coding techniques is generally expected to be further improved. Summary of the Invention

[0004] Embodiments of the present disclosure provide a solution for point cloud coding.

[0005] In a first aspect, a method for point cloud coding is proposed, the method comprising performing a conversion between a current point cloud frame of a point cloud sequence and a bitstream of the point cloud sequence, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice.

[0006] Based on the method according to the first aspect of the present disclosure, a slice is directly dependent on only a single dependent slice. Compared with conventional solutions without such constraints, the proposed method has the advantage of better supporting the application of slices, thereby improving the efficiency of point cloud processing.

[0007] In a second aspect, an apparatus for processing point cloud data is proposed, the apparatus comprising a processor and a non-transitory memory with instructions that, when executed by the processor, cause the processor to perform a method according to the first aspect of the present disclosure.

[0008] In a third aspect, a non-transitory computer-readable storage medium is proposed, the non-transitory computer-readable storage medium storing instructions for causing a processor to perform the method according to the first aspect of the present disclosure.

[0009] In a fourth aspect, another non-transitory computer-readable storage medium is proposed, the non-transitory computer-readable storage medium storing a bitstream of a point cloud sequence generated by a method executed by a point cloud processing device, the method comprising performing a transformation between a current point cloud frame of the point cloud sequence and the bitstream, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice.

[0010] In a fifth aspect, a method for storing a bitstream of a point cloud sequence is proposed, the method comprising: performing a transformation between a current point cloud frame of the point cloud sequence and the bitstream, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice; and storing the bitstream on a non-transitory computer-readable recording medium.

[0011] This description is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. It 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 explanation of the drawings]

[0012] These and other objects, features, and advantages of exemplary embodiments of the present disclosure will become more apparent through the following detailed description taken in conjunction with the accompanying drawings, in which like reference numerals generally refer to like components.

[0013] [Figure 1] FIG. 1 is a block diagram illustrating an example point cloud coding system that may utilize techniques of this disclosure.

[0014] [Figure 2] FIG. 1 shows a block diagram illustrating an exemplary point cloud encoder, according to some embodiments of the present disclosure.

[0015] [Figure 3] FIG. 1 shows a block diagram illustrating an exemplary point cloud decoder, in accordance with some embodiments of the present disclosure.

[0016] [Figure 4] 1 illustrates a flowchart of a method for point cloud coding according to some embodiments of the present disclosure.

[0017] [Figure 5] FIG. 1 illustrates a block diagram of a computing device capable of implementing various embodiments of the present disclosure.

[0018] Throughout the drawings, the same or similar reference numbers generally refer to the same or similar elements. DETAILED DESCRIPTION OF THE INVENTION

[0019] Next, the principles of the present disclosure will be explained with reference to some embodiments. It should be understood that these embodiments are provided for illustrative purposes only, to help those skilled in the art understand and embody the present disclosure, and do not imply any limitations on the scope of the present disclosure. The disclosure described herein can be embodied in various ways other than those described below.

[0020] In the following description and claims, unless otherwise defined, 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.

[0021] References in this disclosure to "one embodiment," "one embodiment," "exemplary embodiment," etc. indicate that the described embodiment may include a particular feature, structure, or characteristic, but not all embodiments necessarily include the particular feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Furthermore, when a particular feature, structure, or characteristic is described in connection with an exemplary embodiment, it is noted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments, whether or not explicitly stated.

[0022] Terms such as "first" and "second" may be used herein to describe various elements, but it should be understood that these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, a first element could be referred to as a second element, and similarly, a second element could be referred to as a first element, without departing from the scope of the exemplary embodiments. As used herein, the term "and / or" includes any and all combinations of one or more of the listed terms.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit example embodiments. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly dictates otherwise. It will be further understood that the terms "comprise," "comprise," "have," "have," "contain," and / or "comprise," when used herein, specify the presence of stated 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.

[0024] Example Environment 1 is a block diagram illustrating an exemplary point cloud coding system 100 that may utilize the techniques of this disclosure. As shown, the point cloud coding 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 encoding 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 this disclosure are generally directed to supporting coding (encoding and / or decoding) of point cloud data, i.e., point cloud compression. The coding may be effective for compressing and / or decompressing the point cloud data.

[0025] Source device 100 and destination device 120 may include any of a wide range of devices, including desktop computers, notebook (i.e., laptop) computers, tablet computers, set-top boxes, telephones 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, augmented reality devices, etc. In some cases, source device 100 and destination device 120 may be equipped for wireless communication.

[0026] Source device 100 may include a data source 112, memory 114, a GPCC encoder 116, and an input / output (I / O) interface 118. Destination device 120 may include an input / output (I / O) interface 128, a GPCC decoder 126, memory 124, and a data consumer 122. According to this disclosure, the GPCC encoder 116 of source device 100 and the GPCC decoder 126 of destination device 120 may be configured to apply techniques of this disclosure related to point cloud coding. Thus, source device 100 represents an example of an encoding device, and destination device 120 represents an example of a decoding device. In other examples, source device 100 and destination device 120 may include other components or arrangements. For example, source device 100 may receive data (e.g., point cloud data) from an internal or external source. Similarly, destination device 120 may interface with an external data consumer rather than including the data consumer in the same device.

[0027] Generally, data source 112 represents a source of point cloud data (i.e., raw, unencoded point cloud data) and may provide a continuous series of “frames” of point cloud data to GPCC encoder 116, which encodes the frame point cloud data. In some examples, data source 112 generates the point cloud data. Data source 112 of source device 100 may include any of a variety of cameras or sensors, such as one or more video cameras, an archive containing previously captured point cloud data, a point cloud capture device such as 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 may generate point cloud data based on signals from a LIDAR device. Alternatively or additionally, point cloud data may be computer-generated from scanner, camera, sensor, or other data. For example, data source 112 may generate point cloud data or a combination of live point cloud data, archived point cloud data, and computer-generated point cloud data. In either case, the GPCC encoder 116 encodes the captured, pre-captured, or computer-generated point cloud data. The GPCC encoder 116 may rearrange frames of the point cloud data from the order in which they were received (sometimes referred to as "display order") into a coding order for coding. The GPCC encoder 116 may generate one or more bitstreams containing the encoded point cloud data. The source device 100 may 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 may be transmitted directly to the destination device 120 over the network 130A via the I / O interface 118. The encoded point cloud data may also be stored on a storage medium / server 130B for access by the destination device 120.

[0028] The memory 114 of the source device 100 and the memory 124 of the destination device 120 may represent general-purpose memory. In some examples, the memory 114 and the memory 124 may 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 may store software instructions executable by, e.g., the GPCC encoder 116 and the GPCC decoder 126, respectively. While the memory 114 and the memory 124 are shown separate 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 may also include internal memory for functionally similar or equivalent purposes. Furthermore, the memory 114 and the memory 124 may 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 to store raw, decoded, and / or encoded point cloud data. For example, memory 114 and memory 124 may store point cloud data.

[0029] I / O interface 118 and I / O interface 128 may 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 the various IEEE 802.11 standards, or other physical components. In examples in which I / O interface 118 and I / O interface 128 include wireless components, I / O interface 118 and I / O interface 128 may be configured to transfer data, such as encoded point cloud data, according to a cellular communication standard such as 4G, 4G-LTE (Long Term Evolution), LTE-Advanced, 5G, etc. In some examples in which I / O interface 118 includes a wireless transmitter, I / O interface 118 and I / O interface 128 may be configured to transfer data, such as encoded point cloud data, according to other wireless standards such as the IEEE 802.11 standard. In some examples, source device 100 and / or destination device 120 may include respective system-on-chip (SoC) devices. For example, the source device 100 may include an SoC device that performs functions attributed to the GPCC encoder 116 and / or the I / O interface 118, and the destination device 120 may include an SoC device that performs functions attributed to the GPCC decoder 126 and / or the I / O interface 128.

[0030] The techniques of this disclosure may be applied to encoding and decoding in support of any of a variety of applications, such as communication between autonomous vehicles, communication between processing device devices such as scanners, cameras, sensors and local or remote servers, geographic mapping, or other applications.

[0031] 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, which is also used by the GPCC decoder 126, such as syntax elements having values ​​representing the point cloud. The data consumer 122 uses the decoded data. For example, the data consumer 122 may use the decoded point cloud data to determine the location of a physical object. In some examples, the data consumer 122 may include a display that presents an image based on the point cloud data.

[0032] The GPCC encoder 116 and the GPCC decoder 126 may each be embodied as any of a variety of suitable encoder and / or decoder circuits, 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 combinations thereof. If the techniques are embodied partially in software, a device may store software instructions on a suitable non-transitory computer-readable medium and execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Each of the GPCC encoder 116 and the GPCC decoder 126 may be included in one or more encoders or decoders, any of which may be integrated as part of a combined encoder / decoder (CODEC) in the respective device. A device including the GPCC encoder 116 and / or the GPCC decoder 126 may include one or more integrated circuits, microprocessors, and / or other types of devices.

[0033] The GPCC encoder 116 and the GPCC decoder 126 may operate according to a coding standard, such as the Video Point Cloud Compression (VPCC) standard or the Geometry Point Cloud Compression (GPCC) standard. This disclosure may generally refer to coding (e.g., encoding and decoding) of frames, which includes the processes of encoding or decoding data. The encoded bitstream generally includes a series of values ​​of syntax elements that represent coding decisions (e.g., coding modes).

[0034] A point cloud may include a set of points in 3D space and may have attributes associated with the points. The attributes may be color information such as R, G, B, Y, Cb, Cr, or reflectance information, or other attributes. Point clouds may be captured by various cameras and sensors, such as LIDAR sensors and 3D scanners, or may be computer-generated. Point cloud data is used in a variety of applications, including, but not limited to, construction (modeling), graphics (3D models for visualization and animation), and the automotive industry (LIDAR sensors used for navigation).

[0035] Figure 2 is a block diagram illustrating an example of a GPCC encoder 200, which may be an example of a GPCC encoder 116 in the system 100 shown in Figure 1, according to some embodiments of the present disclosure. Figure 3 is a block diagram illustrating an example of a GPCC decoder 300, which may be an example of a GPCC decoder 126 in the system 100 shown in Figure 1, according to some embodiments of the present disclosure.

[0036] In both the GPCC encoder 200 and the GPCC decoder 300, the point cloud location is coded first. Attribute coding depends on the decoded geometry. In Figures 2 and 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 typically 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 typically used for Category 3 data. All other units are common to Categories 1 and 3.

[0037] For Category 3 data, the compressed geometry is typically represented as an octree extending from the root down to the leaf level of individual voxels. For Category 1 data, the compressed geometry is typically represented by a pruned octree (i.e., an octree extending from the root down to the leaf level of blocks larger than a voxel) and a model approximating the surface within each leaf of the pruned octree. In this way, both Category 1 and Category 3 data share the octree coding mechanism, but Category 1 data may additionally approximate the voxels within each leaf with a surface model. The surface model used is a triangulation with 1 to 10 triangles per block, resulting in a triangle soup. Therefore, Category 1 geometry codecs are known as Trisoup geometry codecs, and Category 3 geometry codecs are known as Octree geometry codecs.

[0038] In the example of FIG. 2, 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 encoding unit 214, a geometry reconstruction unit 216, a RAHT unit 218, an LOD generation unit 220, a lifting unit 222, a coefficient quantization unit 224, and an arithmetic encoding unit 226.

[0039] 2, the GPCC encoder 200 may receive a set of locations and a set of attributes. The locations may include coordinates of points within the point cloud. The attributes may include information about the points within the point cloud, such as a color associated with the points within the point cloud.

[0040] The coordinate transformation unit 202 may apply a transform to the coordinates of the points to convert the coordinates from an initial domain to a transformed domain. In this disclosure, the transformed coordinates may be referred to as transformed coordinates. The color transformation unit 204 may apply a transform to convert the color information of the attributes to a different domain. For example, the color transformation unit 204 may convert the color information from an RGB color space to a YCbCr color space.

[0041] Further, in the example of FIG. 2, the voxelization unit 206 may voxelize the transformed coordinates. Voxelizing 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 contained within a single "voxel" and then treated as one point in some respects. Further, the octree analysis unit 210 may generate an octree based on the voxelized transformed coordinates. Additionally, in the example of FIG. 2, the surface approximation analysis unit 212 may analyze the points to potentially determine a surface representation of the set of points. The arithmetic encoding unit 214 may perform arithmetic encoding on syntax elements representing the octree and / or surface information determined by the surface approximation analysis unit 212. The GPCC encoder 200 may output these syntax elements in a geometry bitstream.

[0042] The geometry reconstruction unit 216 may reconstruct transformation 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. The number of transformation coordinates reconstructed by the geometry reconstruction unit 216 may differ from the number of original points in the point cloud due to voxelization and surface approximation. In this disclosure, the resulting points may be referred to as reconstructed points. The attribute transfer unit 208 may transfer attributes of the original points of the point cloud to the reconstructed points of the point cloud data.

[0043] Further, the RAHT unit 218 may apply RAHT coding to the attributes of the reconstructed 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 reconstructed 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 encoding unit 226 may apply arithmetic coding to syntax elements representing the quantized coefficients. The GPCC encoder 200 may output these syntax elements in an attribute bitstream.

[0044] In the example of FIG. 3, the GPCC decoder 300 may include a geometry 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 geometry reconstruction unit 312, a RAHT unit 314, an LOD generation unit 316, an inverse lifting unit 318, a coordinate inverse transform unit 320, and a color inverse transform unit 322.

[0045] The GPCC decoder 300 may obtain a geometry bitstream and an attribute bitstream. A geometry arithmetic decoding unit 302 of the decoder 300 may apply arithmetic decoding (e.g., CABAC or other types of arithmetic decoding) to syntax elements in the geometry bitstream. Similarly, an attribute arithmetic decoding unit 304 may apply arithmetic decoding to syntax elements in the attribute bitstream.

[0046] The octree synthesis unit 306 may synthesize an octree based on syntax elements parsed from the geometry bitstream. If surface approximation is used in the geometry bitstream, the surface approximation synthesis unit 310 may determine a surface model based on the syntax elements and octrees parsed from the geometry bitstream.

[0047] Further, the geometry reconstruction unit 312 may perform the reconstruction to determine the coordinates of the points in the point cloud. The coordinate inverse transformation unit 320 may apply an inverse transform to the reconstructed coordinates to convert the reconstructed coordinates (positions) of the points in the point cloud from the transformed domain back to the initial domain.

[0048] 3, the inverse quantization unit 308 may inverse quantize the attribute values, which may be based on syntax elements obtained from the attribute bitstream (e.g., including syntax elements decoded by the attribute arithmetic decoding unit 304).

[0049] Depending on how the attribute values ​​are encoded, the RAHT unit 314 may perform RAHT coding to determine color values ​​for the points of the point cloud based on the dequantized attribute values. Alternatively, the LOD generation unit 316 and the inverse lifting unit 318 may determine color values ​​for the points of the point cloud using a level-of-detail-based technique.

[0050] 3, color inverse transform unit 322 may apply an inverse color transform to the color values. The inverse color transform may be the inverse of the color transform applied by color transform unit 204 of encoder 200. For example, color transform unit 204 may convert the color information from the RGB color space to the YCbCr color space. Thus, color inverse transform unit 322 may convert the color information from the YCbCr color space to the RGB color space.

[0051] The various units in FIGS. 2 and 3 are shown to aid in understanding the operations performed by the encoder 200 and the decoder 300. The units may be embodied as fixed-function circuits, programmable circuits, or a combination thereof. A fixed-function circuit refers to a circuit that provides a specific function and is preconfigured with respect to the operations it can perform. A programmable circuit refers to a circuit that can be programmed to perform various tasks and provides flexible functionality in the operations it can perform. For example, a programmable circuit may execute software or firmware that causes the programmable circuit to operate in a manner defined by the software or firmware instructions. While a fixed-function circuit may execute software instructions (e.g., to receive parameters or output parameters), the types of operations it performs are generally immutable. In some examples, one or more units may be separate circuit blocks (fixed function or programmable), and in some examples, one or more units may be integrated circuits.

[0052] Some exemplary embodiments of the present disclosure are described in detail below. It should be understood that section headings are used herein for ease of understanding and are not intended to limit the embodiments disclosed in a section to that section alone. Furthermore, while certain embodiments are described with reference to GPCC or other specific point cloud codecs, the disclosed techniques are also applicable to other point cloud coding techniques. Furthermore, while some embodiments describe point cloud coding steps in detail, it will be understood that the corresponding steps of decoding to undo the coding are implemented by a decoder. 1. Overview This disclosure relates to point cloud compression techniques, particularly to the design of slices and parameter sets for the Geometry-based Point Cloud Compression (G-PCC) standard. The ideas can be applied individually or in various combinations to point cloud compression standards or non-standard point cloud codecs (e.g., the G-PCC standard under development). 2. Abbreviations APS Attribute parameter set ADU Attribute data unit DU Data unit FBDU Frame boundary data unit FSAP Frame-specific attribute parameters GDU Geometry data unit GPS Geometry parameter set G-PCC Geometry based point cloud compression LSB Least significant bit MSB Most significant bit PCC Point cloud compression SPS Sequence parameter set TI Tile inventory 3. Background 3.1 General Advances in 3D capturing and rendering technologies are enabling new applications and services in the areas of assisted and autonomous driving, mapping, cultural heritage, industrial processes, immersive real-time communications, and virtual / augmented / mixed reality (VR / AR / MR) content creation, transmission, and communication. Point clouds have emerged as one of the primary representations for such applications. A point cloud frame consists of a set of 3D points, where each point may be associated with a 3D position as well as a number of other attributes such as color, transparency, reflectance, timestamp, surface normal, classification, etc. Such a representation requires a large amount of data, which can be costly in terms of storage and transmission. The Moving Picture Experts Group (MPEG) is developing two point cloud compression standards: the video-based point cloud compression (V-PCC) standard, which is suitable for point sets with a relatively uniform distribution of points, and the geometry-based point cloud compression (G-PCC) standard, which is suitable for a more sparse distribution. 3.2 Some basic concepts of G-PCC 3.2.1 Terms and Definitions point A basic element of a point cloud consisting of a position specified as a Cartesian coordinate and zero or more attributes. point cloud an unordered list of points Point Cloud Sequence a sequence of zero or more points Point Cloud Frame Point clouds in a point cloud sequence Geometry Point positions associated with a set of points attribute Scalar or vector properties associated with each point in the point cloud e.g. color, reflectance, frame index, etc. Bitstream A sequence of bits forming a representation of the coded point cloud sequence Coded Point Cloud Frame A coded representation of the point cloud frame Bounding Box An axis-aligned rectangular prism that defines a region of space bounding a set of points tile The set of slices identified by a common slice_tag syntax element value, whose geometry is contained within the bounding box specified in the tile inventory data unit. slice Part or all of a coded point cloud frame consisting of a GDU and zero or more corresponding ADUs Note 1: The bounding boxes of any two slices may intersect. 3.2.2 Coded Point Cloud Sequence A coded representation of a point cloud sequence consists of one or more point cloud frames encoded as a sequence of DUs. The coded point cloud sequence shall consist of: - An SPS that lists the attributes present in the coded point cloud format and conveys both metadata and decoding parameters associated with the entire coded point cloud sequence. - At least one GPS that conveys the parameters used for decoding the geometry data. - If an ADU is present in the coded point cloud sequence, at least one APS conveying the parameters used for decoding the attribute data. - DU containing each coded point cloud frame. Profiles and levels specify limits on the number of bits required to represent geometry and attribute component information. 3.2.3 Coded Point Cloud Frames and Slices A coded point cloud frame contains a sequence of zero or more slices with the same FrameCtr value. Empty frames are indicated using consecutive frame boundary data units. A coded point cloud frame consists of the following data units: - Geometry, attribute, or default attribute data units - Zero or more Frame Boundary Data Units that identify the boundary between two coded point cloud frames A slice is an unordered list of points. The positions of the slice points are coded relative to the slice origin in the coding coordinate system. The coding volume of a slice may intersect, including within the point cloud frame. Each slice shall consist of a single GDU followed by zero or more ADUs. The GDU header serves as the slice header. An ADU depends on the corresponding GDU in the same slice. DUs belonging to different slices shall not be interleaved. The decoded point cloud frame is the connection of all points in all constituent slices of the frame. Matching points in the point cloud frame can result from the connection of multiple slices. Slices are either independent or dependent. An independent slice does not require the other slices to be decoded first. A dependent slice requires the previous slice in bitstream order to be decoded first. A slice shall be dependent on at most a single dependent slice. 3.2.4 Slices and Tiles A group of slices within a point cloud frame may be identified by a common value of slice_tag. The tile inventory provides a means to associate bounding boxes with groups of slices. Each tile consists of a single bounding box and an identifier (tileId). Tile bounding boxes may overlap. If a tile inventory is present in the bitstream, the slice_tag shall identify the tile by its tileId. Otherwise, the use of the slice_tag is application-specific. The tile information is not used in the decoding process described in this document. A decoder implementation may use a tile inventory to support spatial random access. A decoder performing spatial random access to decode region R may use the tile inventory to determine the tileIds of the set of tiles that intersect with R. Only slices with matching tileIds need to be decoded. 3.2.5 Parameter Set 3.2.5.1 Activating a Parameter Set The parameters contained in the SPS, GPS, or APS shall have no effect until the respective parameter set is activated. At any moment during the decoding process, at most one SPS, GPS, and APS shall be active. Activating a parameter set shall deactivate any previously active parameter set of the same type. At the start of the coded point cloud sequence, there are no active parameter sets. The SPS shall be activated by parsing the GDU. Once activated, the activated SPS shall remain active throughout the entire coded point cloud sequence. The GPS shall be activated by the analysis of the GDU. The APS shall be activated by the analysis of the ADU. Note: Other DUs containing a reference to an SPS, GPS, or APS DU do not activate the referenced parameter set. 3.2.5.2 Parameter Set Order The DUs shall be delivered to the decoder in an order such that any activation parameter sets are available at the time of activation. 3.2.5.3 Overlapping Parameter Sets All parameter set DUs with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence. 3.3 G-PCC GDU Header (i.e., Slice Header) 3.3.1 Geometry Data Unit Header Syntax [Table 1] 3.3.2 Geometry Data Unit Header Syntax gdu_geometry_parameter_set_id specifies the value of the active GPS gps_geom_parameter_set_id. In bitstreams conforming to this version of this document, gdu_reserved_zero_3bits shall be equal to 0. Other values ​​of gdu_reserved_zero_3bits are reserved for future use by ISO / IEC. Decoders shall ignore values ​​of gdu_reserved_zero_3bits. The slice_id identifies the slice for reference by other syntax elements. The slice_tag may be used to identify one or more slices with a particular value of slice_tag. If a tile inventory data unit is present, the slice_tag is a tile id. Otherwise, if a tile inventory data unit is not present, the interpretation of the slice_tag is specified by external means. frame_ctr_lsb specifies the least significant bit of the frame_ctr_lsb_bits of the conceptual frame number counter. Consecutive slices with different values ​​of frame_ctr_lsb form part of different output point cloud frames. Consecutive slices with the same value of frame_ctr_lsb, with no intervening frame boundary marker data units, form part of the same coded point cloud frame. It is a bitstream-compliant requirement that each coded point cloud frame have a unique value of FrameCtr. slice_entropy_continuation equal to 1 specifies that the entropy analysis state restoration process (XREF) shall be applied to the GDU and any ADUs within the slice. slice_entropy_continuation equal to 0 specifies that the entropy analysis of the GDU and any ADUs within the slice is independent of other slices. If not present, slice_entropy_continuation shall be inferred to be 0. If the GDU is the first DU in a coded point cloud frame, it is a bitstream compliance requirement that slice_entropy_continuation be equal to 0. prev_slice_id shall be equal to the value of slice_id of the previous GDU in bitstream order. Decoders shall ignore slices where prev_slice_id is present and is not equal to the value of slice_id of the previous slice. NOTE: It is RECOMMENDED that slice_entropy_continuation shall not be equal to 1 if slice_tag is not equal to the slice_tag of the GDU identified by prev_slice_id. ... 4. Problems The latest draft G-PCC specification design has the following problems: 1) It is specified that a slice shall be dependent on at most a single dependent slice. However, it is unclear whether slice C is allowed to depend on slice B, which in turn depends on slice A. In this case, slice A is dependent on both dependent slices B and C. Furthermore, it is unclear whether a slice may be dependent on slices in different point cloud frames. 2) If the slice_tag of the current slice is not equal to the slice_tag of a slice with a slice_id equal to the current slice's prev_slice_id, then slice_entropy_continuation for the current slice is allowed to be equal to 1. In other words, slice dependencies between tiles within a point cloud frame are allowed. However, this may invalidate the following spatial random access use case described in the latest draft G-PCC specification: A decoder performing spatial random access to decode region R may use its tile inventory to determine the tileIds of the set of tiles that intersect with R, and it needs to decode only slices with matching tileIds. 3) Regarding parameter set duplication, it is specified that all parameter set DUs with the same parameter set identifier are identical for the duration of the coded point cloud sequence. However, parameter sets of different types in a coded point cloud sequence may have the same parameter set identifier value. Therefore, this constraint should be narrowed down to specific types of parameter sets. 5. Detailed Solutions To solve the above problems, the methods summarized below are disclosed. The solutions should be considered as examples to illustrate the general concept and should not be interpreted narrowly. Furthermore, these solutions can be applied individually or in any combination. 1) To solve the first problem, one or more of the following items are specified: a. The first slice shall be directly depended upon by at most a single dependent slice. i. Alternatively, it is specified that the first slice shall be depended upon (directly or indirectly) by at most a single dependent slice. ii. In one example, the dependent slice may be explicitly signaled by the first slice. iii. In one example, the dependent slices for the first slice may be implicitly derived. 1. For example, the dependent slice may be a slice before the first slice in decoding order. b. A slice in a point cloud frame must not be dependent (directly or indirectly) on a slice in another point cloud frame. c. A slice in one tile must not depend (directly or indirectly) on a slice in another tile. 2) To solve the second problem, it is specified that if the slice_tag of slice A is not equal to the slice_tag of slice slice B which has a slice_id equal to the prev_slice_id of slice A, then the value of slice_entropy_continuation of slice slice A is equal to 0. a. Alternatively, if there is a tile inventory data unit that applies to a point cloud frame, it specifies that if the slice_tag of slice A is not equal to the slice_tag of slice slice B, whose slice_id is equal to slice A's prev_slice_id, then the value of slice_entropy_continuation of slice slice A in the point cloud frame shall be equal to 0. 3) To solve the third problem, it is specified that all parameter set DUs of a particular type of parameter set with the same parameter set identifier are identical for the duration of the coded point cloud sequence. Alternatively, the following may be specified: i. All SPS DUs with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence. ii. All GPS DUs with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence. iii. All APS DUs with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence. 6. Implementation [Outside 1] TIFF0007827358000002.tif261706.1 Embodiment 1 This embodiment corresponds to items 1.a, 1.b, 2, and 3 of Section 5. 6.1.1 Coded Point Cloud Frames and Slices A coded point cloud frame contains a sequence of zero or more slices with the same FrameCtr value. Empty frames are indicated using consecutive frame boundary data units. A coded point cloud frame consists of the following data units: - Geometry, attribute, or default attribute data units - Zero or more Frame Boundary Data Units that identify the boundary between two coded point cloud frames A slice is an unordered list of points. The positions of the slice points are coded relative to the slice origin in the coding coordinate system. The coding volume of a slice may intersect, including within the point cloud frame. Each slice shall consist of a single GDU followed by zero or more ADUs. The GDU header serves as the slice header. An ADU depends on the corresponding GDU in the same slice. DUs belonging to different slices shall not be interleaved. The decoded point cloud frame is the connection of all points in all constituent slices of the frame. Matching points in the point cloud frame can result from the connection of multiple slices. Slices can be independent or dependent: an independent slice does not require the other slice to be decoded first, and a dependent slice requires the previous slice in bitstream order to be decoded first. A slice is bound by at most one dependent slice directly It shall be relied upon. 6.1.2 Parameter Set 6.1.2.1 Activating a Parameter Set The parameters contained in the SPS, GPS, or APS shall have no effect until the respective parameter set is activated. At any moment during the decoding process, at most one SPS, GPS, and APS shall be active. Activating a parameter set shall deactivate any previously active parameter set of the same type. At the start of the coded point cloud sequence, there are no active parameter sets. The SPS shall be activated by parsing the GDU. Once activated, the activated SPS shall remain active throughout the entire coded point cloud sequence. The GPS shall be activated by the analysis of the GDU. The APS shall be activated by the analysis of the ADU. Note: Other DUs containing a reference to an SPS, GPS, or APS DU do not activate the referenced parameter set. 6.1.2.2 Parameter Set Order The DUs shall be delivered to the decoder in an order such that any activation parameter sets are available at the time of activation. 6.1.2.3 Overlapping Parameter Sets have the same parameter set identifier For a particular type of parameter set All parameter sets DU shall be the same for the duration of the coded point cloud sequence. 6.1.3 Geometry Data Unit Header Syntax gdu_geometry_parameter_set_id specifies the value of the active GPS gps_geom_parameter_set_id. In bitstreams conforming to this version of this document, gdu_reserved_zero_3bits shall be equal to 0. Other values ​​of gdu_reserved_zero_3bits are reserved for future use by ISO / IEC. Decoders shall ignore values ​​of gdu_reserved_zero_3bits. The slice_id identifies the slice for reference by other syntax elements. The slice_tag may be used to identify one or more slices with a particular value of slice_tag. If a tile inventory data unit is present, the slice_tag is a tile id. Otherwise, if a tile inventory data unit is not present, the interpretation of the slice_tag is specified by external means. frame_ctr_lsb specifies the least significant bit of the frame_ctr_lsb_bits of the conceptual frame number counter. Consecutive slices with different values ​​of frame_ctr_lsb form part of different output point cloud frames. Consecutive slices with the same value of frame_ctr_lsb, with no intervening frame boundary marker data units, form part of the same coded point cloud frame. It is a bitstream-compliant requirement that each coded point cloud frame have a unique value of FrameCtr. slice_entropy_continuation equal to 1 specifies that the entropy analysis state restoration process (XREF) shall be applied to the GDU and any ADUs within the slice. slice_entropy_continuation equal to 0 specifies that the entropy analysis of the GDU and any ADUs within the slice is independent of other slices. If not present, slice_entropy_continuation shall be inferred to be 0. If the GDU is the first DU in a coded point cloud frame, it is a bitstream compliance requirement that slice_entropy_continuation be equal to 0. prev_slice_id shall be equal to the value of slice_id of the previous GDU in bitstream order. Decoders shall ignore slices where prev_slice_id is present and is not equal to the value of slice_id of the previous slice. [Outside 2] TIFF0007827358000003.tif11165 The bitstream compliance requirement is that if the slice_tag of sliceA is not equal to the slice_tag of slice sliceB which has a slice_id equal to the prev_slice_id of sliceA, then the value of slice_entropy_continuation of slice sliceA shall be equal to 0. ...

[0053] Further details of embodiments of the present disclosure related to slicing and parameter sets in geometry-based point cloud compression are described below.

[0054] As used herein, the term "point cloud sequence" may refer to a sequence of zero or more point clouds. The term "point cloud frame" may refer to a point cloud within a point cloud sequence. The term "coded point cloud frame" may refer to a coded representation of a point cloud frame. The term "bounding box" may refer to an axis-aligned rectangular prism that defines a spatial region bounding a set of points. The term "slice" may refer to part or all of a coded group frame consisting of a geometry data unit (GDU) and zero or more corresponding attribute data units (ADUs).

[0055] 4 illustrates a flowchart of a method 400 of point cloud coding according to some embodiments of the present disclosure. As shown in FIG. 4, at 402, a conversion between a current point cloud frame of a point cloud sequence and a bitstream of the point cloud sequence is performed. In some embodiments, the current point cloud frame may be encoded into a bitstream during the conversion at 402. Additionally or alternatively, the current point cloud frame may be decoded from the bitstream during the conversion at 402.

[0056] During the transformation at 402, a first slice in the current point cloud frame is directly dependent on only a single dependent slice. That is, the first slice is directly dependent on only a single dependent slice, or the first slice is not directly dependent on anything. In other words, a slice is directly dependent on only a single dependent slice. In one example, the first slice may be directly dependent on a second slice, and the second slice may be directly dependent on a third slice. In such a case, the first slice is also indirectly dependent on the third slice.

[0057] Considering the above, a slice is assumed to be directly dependent only by a single dependent slice. Compared to conventional solutions without such constraints, the proposed method has the advantage of better supporting the application of slices, thereby improving the efficiency of point cloud processing.

[0058] In some embodiments, the number of dependent slices that directly or indirectly depend on a first slice may be only one. That is, a slice may be dependent (directly or indirectly) on at most one dependent slice. In other words, a slice may not be indirectly dependent on anything.

[0059] In some embodiments, there may be a single dependent slice in the current point cloud frame, i.e., no slice in a point cloud frame is dependent (directly or indirectly) on by a slice in another point cloud frame.

[0060] In some embodiments, the single dependent slice may be indicated by the first slice. For example, the dependent slice may be explicitly signaled by the first slice. In some alternative embodiments, the single dependent slice for the first slice may be implicitly derived. In one example, the single dependent slice may be determined based on the coding order. In another example, the single dependent slice precedes the first slice in coding order.

[0061] In some embodiments, the first slice and the single dependent slice may be in the same tile within the current point cloud frame. Additionally or alternatively, the first slice may not be allowed to be dependent on by slices in further point cloud frames other than the current point cloud frame. That is, the first slice shall not be dependent (directly or indirectly) on slices in another point cloud frame. In other words, slices in one tile shall not be dependent (directly or indirectly) on slices in another tile.

[0062] In some embodiments, the slice tag of a first slice may be different from the slice tag of a slice preceding the first slice in bitstream order. In one example, the slice preceding the first slice in bitstream order is the slice with a slice_id equal to the prev_slice_id of the first slice. Geometry data units (GDUs) and attribute data units (ADUs) within the first slice may be parsed independently. As an example, the value of the syntax element slice_entropy_continuation of the first slice may be equal to 0.

[0063] In some embodiments, a tile inventory may be applied to the current point cloud frame. When there is a tile inventory data unit to be applied to a point cloud frame, if the slice_tag of the first slice is not equal to the slice_tag of a slice with a slice_id equal to the prev_slice_id of the first slice, then the value of the syntax element slice_entropy_continuation of the first slice shall be equal to 0.

[0064] In some embodiments, the conversion may be performed based on multiple data units of a first type of parameter set. The multiple data units may have the same parameter set identifier, and the multiple data units may be identical for the duration of the coded point cloud sequence of the point cloud sequence. In other words, all parameter set DUs of a particular type of parameter set with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence.

[0065] By way of example and not limitation, the first type of parameter set may be one of a sequence parameter set (SPS), a geometry parameter set (GPS), or an attribute parameter set (APS). That is, all SPS data units (DUs) with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence. All GPS DUs with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence. All APS DUs with the same parameter set identifier shall be identical for the duration of the coded point cloud sequence.

[0066] According to an embodiment of the present disclosure, a non-transitory computer-readable recording medium is proposed. A bit stream of a point cloud sequence is stored in the non-transitory computer-readable recording medium. The bit stream can be generated by a method executed by a point cloud processing device. The method performs a conversion between a current point cloud frame of the point cloud sequence and the bit stream. A first slice of the current point cloud frame is directly dependent on only a single dependent slice.

[0067] According to an embodiment of the present disclosure, a method for storing a bitstream of a point cloud sequence is proposed, in which a conversion between a current point cloud frame of the point cloud sequence and the bitstream is performed, where a first slice of the current point cloud frame is directly dependent on only a single dependent slice, and the bitstream is stored in a non-transitory computer-readable recording medium.

[0068] Implementations of the present disclosure may be described in light of the following clauses, the features of which may be combined in any reasonable manner.

[0069] Clause 1. A method of point cloud coding, comprising the step of performing a conversion between a current point cloud frame of a point cloud sequence and a bitstream of said point cloud sequence, wherein a first slice in said current point cloud frame is directly dependent on only a single dependent slice.

[0070] Clause 2. The method described in clause 1, wherein the number of dependent slices that directly or indirectly depend on the first slice is only one.

[0071] Clause 3. The method of any one of clauses 1 to 2, wherein the single dependent slice is in the current point cloud frame.

[0072] Clause 4. A method according to any one of clauses 1 to 2, wherein the first slice is not allowed to be dependent on by a slice in a further point cloud frame different from the current point cloud frame.

[0073] Clause 5. The method of any one of clauses 1 to 4, wherein the single dependent slice is indicated by the first slice.

[0074] Clause 6. The method of any one of clauses 1 to 4, wherein the single dependent slice is determined based on a coding order.

[0075] Clause 7. The method of any one of clauses 1 to 4, wherein the single dependent slice precedes the first slice in coding order.

[0076] Clause 8. The method of any one of clauses 1 to 7, wherein the first slice and the single dependent slice are within the same tile in the current point cloud frame.

[0077] Clause 9. A method according to any one of clauses 1 to 8, wherein the slice tag of the first slice is different from the slice tag of a slice preceding the first slice in bitstream order, and wherein geometry data units (GDUs) and attribute data units (ADUs) within the first slice are parsed independently.

[0078] Clause 10. The method of clause 8, wherein a tile inventory is applied to the current point cloud frame.

[0079] Clause 11. A method according to any one of clauses 1 to 10, wherein the conversion is performed based on a plurality of data units of a first type of parameter set, the plurality of data units having the same parameter set identifier, and the plurality of data units being identical for the duration of the coded point cloud sequence of the point cloud sequence.

[0080] Clause 12. The method of clause 11, wherein the first type parameter set is one of a sequence parameter set (SPS), a geometry parameter set (GPS), or an attribute parameter set (APS).

[0081] Clause 13. The method of any one of clauses 1 to 12, wherein the converting comprises encoding the current point cloud frame into the bitstream.

[0082] Clause 14. The method of any one of clauses 1 to 12, wherein the conversion comprises decoding the current point cloud frame from the bitstream.

[0083] Clause 15. An apparatus for processing point cloud data comprising a processor and a non-transitory memory comprising instructions that, when executed by the processor, cause the processor to perform a method according to any one of clauses 1 to 14.

[0084] Clause 16. A non-transitory computer-readable storage medium storing instructions that cause a processor to perform the method of any one of clauses 1 to 14.

[0085] Clause 17. A non-transitory computer-readable recording medium storing a bitstream of a point cloud sequence generated by a method executed by a point cloud processing device, the method including a step of performing a conversion between a current point cloud frame of the point cloud sequence and the bitstream, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice.

[0086] Clause 18. A method for storing a bitstream of a point cloud sequence, the method comprising the steps of: performing a conversion between a current point cloud frame of the point cloud sequence and the bitstream, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice; and storing the bitstream on a non-transitory computer-readable recording medium.

[0087] Exemplary Devices 5 illustrates a block diagram of a computing device 500 capable of implementing various embodiments of the present disclosure. The computing device 500 may be embodied as or included in the source device 110 (or a GPCC encoder 116 or 200) or the destination device 120 (or a GPCC decoder 126 or 300).

[0088] It will be understood that the computing device 500 shown in FIG. 5 is for illustrative purposes only and is not intended to limit in any way the functionality and scope of the embodiments of the present disclosure.

[0089] 5, the computing device 500 includes a general-purpose computing device 500. The computing device 500 may include at least one or more processors or processing units 510, a memory 520, a storage unit 530, one or more communication units 540, one or more input devices 550, and one or more output devices 560.

[0090] In some embodiments, computing device 500 may be embodied as any user terminal or server terminal having computing capabilities. The server terminal may be a server provided by a service provider, a large-scale computing device, or the like. The user terminal may be any type of mobile, fixed, or portable terminal, including, for example, a mobile phone, a station, a unit, a device, a multimedia computer, a multimedia tablet, 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 receiver, an electronic book device, a gaming device, or any combination thereof (including accessories and peripherals of these devices, or any combination thereof). It is contemplated that computing device 500 may support any type of interface to a user (e.g., "wearable" circuitry, etc.).

[0091] The processing unit 510 may be a physical or virtual processor and may implement various processes based on programs stored in the memory 520. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to increase the parallel processing capabilities of the computing device 500. The processing unit 510 may be referred to as a central processing unit (CPU), a microprocessor, a controller, or a microcontroller.

[0092] Computing device 500 typically includes a variety of computer storage media. Such media may be any media accessible by computing device 500, including, but not limited to, volatile and nonvolatile media, or removable and non-removable media. Memory 520 may be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or any combination thereof. Storage unit 530 may be any removable or non-removable media, including machine-readable media such as memory, a flash memory drive, a magnetic disk, or another medium, that can be used to store information and / or data and that can be accessed by computing device 500.

[0093] The computing device 500 may further include additional removable / non-removable, volatile / non-volatile memory media. Although not shown in FIG. 5, a magnetic disk drive that reads from and writes to a removable non-volatile magnetic disk and an optical disk drive that reads from and writes to a removable non-volatile optical disk may be provided. In such cases, each drive may be connected to a bus (not shown) via one or more data medium interfaces.

[0094] The communications unit 540 communicates with additional computing devices via a communications medium. Additionally, the functionality of the components within the computing device 500 may be embodied by a single computing cluster or multiple computing machines that can communicate via communications connections. Thus, the computing device 500 may operate in a networked environment using logical connections with one or more other servers, networked personal computers (PCs), or additional general network nodes.

[0095] The input device(s) 550 may be one or more of a variety of input devices such as a mouse, a keyboard, a tracking ball, an audio input device, etc. The output device(s) 560 may be one or more of a variety of output devices such as a display, a loudspeaker, a printer, etc. The communication unit 540 may further enable the computing device 500 to communicate with one or more external devices (not shown), such as a storage device and a display device, one or more devices that allow a user to interact with the computing device 500, or any device (such as a network card, a modem, etc.) that allows the computing device 500 to communicate with one or more other computing devices, as needed. Such communication may be performed via an input / output (I / O) interface (not shown).

[0096] In some embodiments, instead of being integrated into a single device, some or all of the components of computing device 500 may be located in a cloud computing architecture. In a cloud computing architecture, components may be provided remotely and work together to perform the functions described in this disclosure. In some embodiments, cloud computing provides computing, software, data access, and storage services without end users needing to be aware of the physical location or configuration of the systems or hardware providing these services. In various embodiments, cloud computing provides services over a wide area network (e.g., the Internet) using appropriate protocols. For example, a cloud computing provider may provide applications over a wide area network that can be accessed through a web browser or other computing component. Software or components of a cloud computing architecture and corresponding data may be stored on servers in remote locations. Computing resources in a cloud computing environment may be consolidated or distributed across remote data center locations. A cloud computing infrastructure may act as a single access point for users but provide services through a shared data center. Thus, a cloud computing architecture may be used to provide the components and functions described herein from a service provider in a remote location. Alternatively, they may be provided from traditional servers or installed directly or otherwise on client devices.

[0097] The computing device 500 may be used to implement point cloud encoding / decoding in embodiments of the present disclosure. The memory 520 may include one or more point cloud coding modules 525 having one or more program instructions. These modules are accessible and executable by the processing unit 510 to perform the functions of various embodiments described herein.

[0098] In an example embodiment performing point cloud encoding, input device 550 may receive point cloud data to be encoded as input 570. The point cloud data may be processed, for example, by point cloud coding module 525 to generate an encoded bitstream. The encoded bitstream may be provided as output 580 via output device 560.

[0099] In an example embodiment performing point cloud decoding, the input device 550 may receive an encoded bitstream as input 570. The encoded bitstream may be processed, for example, by the point cloud coding module 525 to generate decoded point cloud data. The decoded point cloud data may be provided as output 580 via the output device 560.

[0100] While the present disclosure has been particularly shown and described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the present application as defined by the appended claims. Such variations are intended to be within the scope of the present application. Accordingly, the foregoing description of the embodiments of the present application is not intended to be limiting.

Claims

1. 1. A method of point cloud coding, comprising:

1. A method comprising: performing a conversion between a current point cloud frame of a point cloud sequence and a bitstream of the point cloud sequence, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice, and the first slice is not allowed to be dependent on by slices in further point cloud frames different from the current point cloud frame.

2. The method of claim 1 , wherein the single dependent slice is in the current point cloud frame.

3. The method of claim 1 , wherein the number of dependent slices that directly or indirectly depend on the first slice is only one.

4. The method of claim 1 , wherein the single dependent slice is indicated by the first slice.

5. The method of claim 1 , wherein the single dependent slice is determined based on a coding order.

6. The method of claim 1 , wherein the single dependent slice precedes the first slice in coding order.

7. The method of claim 1 , wherein the first slice and the single dependent slice are within the same tile in the current point cloud frame.

8. 2. The method of claim 1, wherein a slice tag of the first slice is different from a slice tag of a slice preceding the first slice in bitstream order, and geometry data units (GDUs) and attribute data units (ADUs) within the first slice are parsed independently.

9. The method of claim 8 , wherein a tile inventory is applied to the current point cloud frame.

10. 2. The method of claim 1, wherein the conversion is performed based on a plurality of data units of a first type of parameter set, the plurality of data units having the same parameter set identifier, and the plurality of data units being identical for the duration of a coded point cloud sequence of the point cloud sequence.

11. The first type of parameter set comprises: Sequence Parameter Set (SPS), Geometry parameter set (GPS), or The method of claim 10, wherein the parameter is one of an attribute parameter set (APS).

12. The method of claim 1 , wherein the converting comprises encoding the current point cloud frame into the bitstream.

13. The method of claim 1 , wherein the converting comprises decoding the current point cloud frame from the bitstream.

14. 1. An apparatus for processing point cloud data comprising a processor and a non-transitory memory with instructions, Apparatus, wherein the instructions, when executed by the processor, cause the processor to perform the method of any one of claims 1 to 13.

15. A non-transitory computer readable storage medium storing instructions that cause a processor to perform the method of any one of claims 1 to 13.

16. 1. A method for storing a bitstream of a point cloud sequence, comprising: performing a conversion between a current point cloud frame of the point cloud sequence and the bitstream, wherein a first slice in the current point cloud frame is directly dependent on only a single dependent slice, and the first slice is not allowed to be dependent on by slices in further point cloud frames different from the current point cloud frame; and storing the bitstream on a non-transitory computer-readable recording medium.

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