WO2024009562A1 - Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme - Google Patents

Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme Download PDF

Info

Publication number
WO2024009562A1
WO2024009562A1 PCT/JP2023/008642 JP2023008642W WO2024009562A1 WO 2024009562 A1 WO2024009562 A1 WO 2024009562A1 JP 2023008642 W JP2023008642 W JP 2023008642W WO 2024009562 A1 WO2024009562 A1 WO 2024009562A1
Authority
WO
WIPO (PCT)
Prior art keywords
node
node size
trisoup
minimum
size
Prior art date
Application number
PCT/JP2023/008642
Other languages
English (en)
Japanese (ja)
Inventor
恭平 海野
圭 河村
賢史 小森田
Original Assignee
Kddi株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Kddi株式会社 filed Critical Kddi株式会社
Publication of WO2024009562A1 publication Critical patent/WO2024009562A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/40—Tree coding, e.g. quadtree, octree
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/597—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards

Definitions

  • the present invention relates to a point cloud decoding device, a point cloud decoding method, and a program.
  • Non-Patent Document 1 discloses a technique for reconstructing a decoded point group using a method called Trisoup using one type of predetermined node size.
  • Non-Patent Document 1 has a problem in that there is only one type of node size (fixed node size), and there is room for improvement in terms of encoding efficiency.
  • the present invention has been made in view of the above-mentioned problems, and provides a point cloud decoding device, a point cloud decoding method, and a program that can improve encoding efficiency without impairing the subjective image quality of the decoded point cloud.
  • the purpose is to
  • a first feature of the present invention is a point cloud decoding device, which includes an approximate surface synthesis section, and the approximate surface synthesis section determines maximum and minimum node sizes based on the maximum node size and minimum node size decoded from control data. , and if the node size is not the minimum node size, generate a vertex position at the minimum node size based on the decoded vertices, and If there are multiple vertices generated from nodes with different node sizes adjacent to the certain edge, the vertices generated by the node with the largest node size among the different adjacent nodes are selected as the vertices of the certain edge.
  • the gist is that the configuration is such that the apex position is set at the apex position.
  • the second feature of the present invention is a point cloud decoding method in which a vertex decoding process is performed at each node size between the maximum and minimum based on the maximum node size and minimum node size decoded from control data. and if the node size is not the minimum node size, generating a vertex position in the minimum node size based on the decoded vertices, and determining on a certain edge a different node adjacent to the certain side. If there are a plurality of vertices generated from nodes of the same size, the step of setting the vertex generated by the node having the largest node size among the different adjacent nodes as the vertex position of the certain edge.
  • the gist is that.
  • a third feature of the present invention is a program that causes a computer to function as a point cloud decoding device, wherein the point cloud decoding device includes an approximate surface synthesizing section, and the approximate surface synthesizing section decodes data from control data.
  • the point cloud decoding device includes an approximate surface synthesizing section, and the approximate surface synthesizing section decodes data from control data.
  • the point cloud decoding device includes an approximate surface synthesizing section, and the approximate surface synthesizing section decodes data from control data.
  • a point cloud decoding device it is possible to provide a point cloud decoding device, a point cloud decoding method, and a program that can improve encoding efficiency without impairing the subjective image quality of a decoded point group.
  • FIG. 1 is a diagram illustrating an example of the configuration of a point cloud processing system 10 according to an embodiment.
  • FIG. 2 is a diagram illustrating an example of functional blocks of a point cloud decoding device 200 according to an embodiment.
  • FIG. 3 is a diagram illustrating an example of the configuration of encoded data (bitstream) received by the geometric information decoding unit 2010 of the point cloud decoding device 200 according to an embodiment.
  • FIG. 4 is a diagram showing an example of the syntax configuration of the GPS 2011.
  • FIG. 5 is a diagram showing an example of the syntax configuration of GSH2012.
  • FIG. 6 is a diagram showing an example of the syntax configuration of GSH2012.
  • FIG. 7 is a diagram showing an example of the syntax configuration of GSH2012.
  • FIG. 1 is a diagram illustrating an example of the configuration of a point cloud processing system 10 according to an embodiment.
  • FIG. 2 is a diagram illustrating an example of functional blocks of a point cloud decoding device 200 according to an embodiment.
  • FIG. 3 is illustrating an
  • FIG. 8 is a flowchart illustrating an example of processing in the tree synthesis unit 2020 of the point cloud decoding device 200 according to an embodiment.
  • FIG. 9 is a flowchart illustrating an example of processing in the tree synthesis unit 2020 of the point cloud decoding device 200 according to an embodiment.
  • FIG. 10 is a flowchart illustrating an example of processing of the approximate surface synthesis unit 2030 of the point cloud decoding device 200 according to an embodiment.
  • FIG. 11A is a diagram for explaining an example of the process of step S1006 in FIG. 10.
  • FIG. 11B is a diagram for explaining an example of the process of step S1006 in FIG. 10.
  • FIG. 12A is a diagram for explaining an example of the process of step S1006 in FIG. 10.
  • FIG. 11A is a diagram for explaining an example of the process of step S1006 in FIG. 10.
  • FIG. 12B is a diagram for explaining an example of the process of step S1006 in FIG. 10.
  • FIG. 13 is a flowchart illustrating an example of the vertex decoding process used in step S1002 in FIG.
  • FIG. 14 is a flowchart illustrating an example of the process of step S1304 in FIG. 13.
  • FIG. 15 is a diagram illustrating an example of functional blocks of the point cloud encoding device 100 according to this embodiment.
  • FIG. 1 is a diagram showing a point cloud processing system 10 according to an embodiment of the present invention.
  • the point cloud processing system 10 includes a point cloud encoding device 100 and a point cloud decoding device 200.
  • the point cloud encoding device 100 is configured to generate encoded data (bitstream) by encoding an input point cloud signal.
  • Point cloud decoding device 200 is configured to generate an output point cloud signal by decoding a bitstream.
  • the input point group signal and the output point group signal are composed of position information and attribute information of each point in the point group.
  • the attribute information is, for example, color information or reflectance of each point.
  • such a bitstream may be transmitted from the point cloud encoding device 100 to the point cloud decoding device 200 via a transmission path. Further, the bitstream may be stored in a storage medium and then provided from the point cloud encoding device 100 to the point cloud decoding device 200.
  • FIG. 2 is a diagram illustrating an example of functional blocks of the point cloud decoding device 200 according to the present embodiment.
  • the point cloud decoding device 200 includes a geometric information decoding unit 2010, a tree synthesis unit 2020, an approximate surface synthesis unit 2030, a geometric information reconstruction unit 2040, an inverse coordinate transformation unit 2050, and an attribute It includes an information decoding section 2060, an inverse quantization section 2070, a RAHT section 2080, an LoD calculation section 2090, an inverse lifting section 2100, and an inverse color conversion section 2110.
  • the geometric information decoding unit 2010 is configured to input a bit stream related to geometric information (geometric information bit stream) among the bit streams output from the point cloud encoding device 100 and decode the syntax.
  • the decoding process is, for example, context adaptive binary arithmetic decoding process.
  • the syntax includes control data (flags and parameters) for controlling the decoding process of position information.
  • the tree synthesis unit 2020 inputs the control data decoded by the geometric information decoding unit 2010 and an occupancy code indicating in which node in the tree the point group exists, which will be described later, and determines in which area in the decoding target space the point is located. It is configured to generate tree information indicating whether it exists.
  • the tree synthesis unit 2020 may be configured to decode the occurrence code.
  • This process divides the decoding target space into rectangular parallelepipeds, refers to the occupancy code to determine whether a point exists within each rectangular parallelepiped, divides the rectangular parallelepiped in which the point exists into multiple rectangular parallelepipeds, and refers to the occupancy code.
  • Tree information can be generated by repeating the process recursively.
  • inter prediction when decoding such an occupancy code, inter prediction, which will be described later, may be used.
  • the tree synthesis unit 2020 is configured to decode the coordinates of each point based on an arbitrary tree configuration determined by the point cloud encoding device 100. ing.
  • the approximate surface synthesis unit 2030 is configured to generate approximate surface information using the tree information generated by the tree synthesis unit 2020, and decode the point group based on the approximate surface information.
  • Approximate surface information is used, for example, when decoding 3D point cloud data of an object, when the point cloud is densely distributed on the object surface, instead of decoding each individual point cloud. This is an approximation of the region in which a group exists using a small plane.
  • the approximate surface synthesis unit 2030 can generate approximate surface information and decode the point group using, for example, a method called "Trisoup.” A specific processing example of "Trisoup" will be described later. Further, when decoding a sparse point group obtained by Lidar or the like, this process can be omitted.
  • the geometric information reconstruction unit 2040 performs geometric information (decoding process is configured to reconstruct the position information (in the coordinate system assumed by the system).
  • the inverse coordinate transformation section 2050 inputs the geometric information reconstructed by the geometric information reconstruction section 2040, transforms it from the coordinate system assumed by the decoding process to the coordinate system of the output point group signal, and converts the position information into the coordinate system. is configured to print.
  • the attribute information decoding unit 2060 is configured to input a bit stream related to attribute information (attribute information bit stream) among the bit streams output from the point cloud encoding device 100 and decode the syntax.
  • the decoding process is, for example, context adaptive binary arithmetic decoding process.
  • the syntax includes control data (flags and parameters) for controlling the decoding process of attribute information.
  • attribute information decoding unit 2060 is configured to decode quantized residual information from the decoded syntax.
  • the dequantization unit 2070 performs dequantization based on the quantized residual information decoded by the attribute information decoding unit 2060 and the quantization parameter, which is one of the control data decoded by the attribute information decoding unit 2060. quantized residual information to generate inverse quantized residual information.
  • the dequantized residual information is output to either the RAHT section 2080 or the LoD calculation section 2090, depending on the characteristics of the point group to be decoded. Which one is output is specified by control data decoded by attribute information decoding section 2060.
  • the RAHT unit 2080 inputs the dequantized residual information generated by the dequantization unit 2070 and the geometric information generated by the geometric information reconstruction unit 2040, and performs a Haar transform (Region Adaptive Hierarchical Transform) called RAHT (Region Adaptive Hierarchical Transform).
  • RAHT Restion Adaptive Hierarchical Transform
  • the attribute information of each point is decoded using a type of inverse Haar transformation.
  • RAHT Adaptive Hierarchical Transform
  • the LoD calculation unit 2090 is configured to receive the geometric information generated by the geometric information reconstruction unit 2040 and generate LoD (Level of Detail).
  • LoD is a reference relationship (reference point and ) is the information for defining.
  • LoD is a hierarchy in which each point included in geometric information is classified into multiple levels, and attributes of points belonging to lower levels are encoded or decoded using attribute information of points belonging to higher levels. This is information that defines the structure.
  • Non-Patent Document 1 As a specific method for determining LoD, for example, the method described in the above-mentioned Non-Patent Document 1 may be used.
  • the inverse lifting unit 2100 uses the LoD generated by the LoD calculation unit 2090 and the inverse quantized residual information generated by the inverse quantization unit 2070 to calculate attribute information of each point based on the hierarchical structure defined by the LoD. is configured to decrypt the .
  • the method described in the above-mentioned Non-Patent Document 1 can be used.
  • the inverse color conversion unit 2110 converts the attribute information output from the RAHT unit 2080 or the inverse lifting unit 2100 when the attribute information to be decoded is color information and color conversion has been performed on the point cloud encoding device 100 side. It is configured to perform reverse color conversion processing. Whether or not to execute such reverse color conversion processing is determined based on the control data decoded by the attribute information decoding unit 2060.
  • the point cloud decoding device 200 is configured to decode and output the attribute information of each point in the point cloud through the above processing.
  • geometric information decoding unit 2010 The control data decoded by the geometric information decoding section 2010 will be explained below using FIGS. 3 to 7.
  • FIG. 3 is an example of the configuration of encoded data (bitstream) received by the geometric information decoding unit 2010.
  • the bitstream may include GPS2011.
  • GPS 2011 is also called a geometry parameter set, and is a collection of control data regarding decoding of geometry information. A specific example will be described later.
  • Each GPS 2011 includes at least GPS id information for identifying each GPS 2011 when a plurality of GPSs 2011 exist.
  • the bitstream may include GSH2012A/2012B.
  • GSH2012A/2012B is also called a geometry slice header or a geometry data unit header, and is a collection of control data corresponding to a slice, which will be described later.
  • the term “slice” will be used for explanation, but the term “slice” can also be read as "data unit”. A specific example will be described later.
  • GSH2012A/2012B includes at least GPS id information for specifying GPS 2011 corresponding to each GSH2012A/2012B.
  • the bitstream may include slice data 2013A/2013B next to GSH2012A/2012B.
  • the slice data 2013A/2013B includes data in which geometric information is encoded.
  • An example of the slice data 2013A/2013B is an occupancy code described later.
  • the bitstream has a configuration in which each slice data 2013A/2013B corresponds to one GSH 2012A/2012B and one GPS 2011.
  • a common GPS 2011 can be used for multiple slice data 2013A/2013B.
  • the GPS 2011 does not necessarily need to transmit each slice.
  • the bitstream may be configured such that GPS 2011 is not encoded immediately before GSH 2012B and slice data 2013B.
  • FIG. 3 is just an example. As long as GSH2012A/2012B and GPS2011 are configured to correspond to each slice data 2013A/2013B, elements other than those described above may be added as constituent elements of the bitstream.
  • the bitstream may include a sequence parameter set (SPS) 2001.
  • SPS sequence parameter set
  • the data upon transmission, may be formatted into a configuration different from that shown in FIG. 3.
  • it may be combined with a bitstream decoded by an attribute information decoding unit 2060, which will be described later, and transmitted as a single bitstream.
  • FIG. 4 is an example of the syntax configuration of GPS2011.
  • syntax names explained below are just examples. As long as the functions of the syntaxes explained below are the same, the syntax names may be different.
  • the GPS 2011 may include GPS id information (gps_geom_parameter_set_id) for identifying each GPS 2011.
  • ue(v) means an unsigned zero-order exponential Golomb code
  • u(1) means a 1-bit flag
  • the GPS 2011 may include a flag (trisoup_enabled_flag) that controls whether or not the approximate surface synthesis unit 2030 uses Trisoup.
  • Trisoup is not used when the value of trisoup_enabled_flag is "0", and that Trisoup is used when the value of trisoup_enabled_flag is "1".
  • the geometric information decoding unit 2020 may be configured to additionally decode the following syntax when using Trisoup, that is, when the value of trisoup_enabled_flag is "1".
  • trisoup_enabled_flag may be included in SPS2001 instead of GPS2011.
  • the GPS 2011 may include a flag (trisoup_multilevel_enabled_flag, first flag) that controls whether to permit trisoup at multiple levels.
  • trisoup_multilevel_enabled_flag when the value of trisoup_multilevel_enabled_flag is "0", it is defined that trisoup at multiple levels is not allowed, that is, trisoup is performed at a single level, and when the value of trisoup_multilevel_enabled_flag is "1", trisoup at multiple levels is not allowed. It may be defined that Trisoup is permitted.
  • the value of the syntax may be regarded as the value for performing Trisoup at a single level, that is, "0".
  • trisoup_multilevel_enabled_flag may be defined to be included in SPS2001 instead of GPS2011.
  • the value of the syntax may be regarded as the value for performing trisoup at a single level, that is, "0".
  • FIG. 5 is an example of the syntax configuration of GSH2012. Note that, as described above, GSH is also called GDUH (Geometry Data Unit Header).
  • GSH is also called GDUH (Geometry Data Unit Header).
  • the geometric information decoding unit 2020 may be configured to additionally decode the following syntax when trisoup at multiple levels is permitted, that is, when the value of trisoup_multilevel_enabled_flag is "1".
  • GSH 2012 may include a flag (adaptive_octree_enabled_flag) that enables a mode that adaptively selects only Octree and Trisoup within a slice.
  • adaptive Octree mode the mode that adaptively selects Octree and Trisoup (hereinafter referred to as “adaptive Octree mode”) is valid, and if the value of the flag is "0" may define that adaptive Octree mode is disabled.
  • the value of the flag may be implicitly assumed to be "0", that is, the adaptive Octree mode is invalid.
  • GSH 2012 may include syntax (log2_trisoup_max_node_size_minus2) that defines the maximum value of the Trisoup node size when allowing Trisoup at multiple levels.
  • the syntax may be expressed as a value obtained by converting the maximum value of the actual Trisoup node size into a base-2 logarithm. Furthermore, the syntax may be expressed as a value obtained by subtracting 2 after converting the maximum value of the actual Trisoup node size to a base 2 logarithm.
  • GSH 2012 may include syntax (log2_trisoup_min_node_size_minus2) that defines the minimum value of the Trisoup node size when allowing Trisoup at multiple levels.
  • the value of the syntax may be constrained to be always greater than or equal to 0 and less than or equal to log2_trisoup_max_node_size_minus2.
  • the Depth values corresponding to the maximum Trisoup node size and minimum Trisoup node size in Octree processing may be decoded.
  • the Depth value corresponding to the minimum Trisoup node size may be 8, and the Depth value corresponding to the maximum Trisoup node size may be 6.
  • the geometric information decoding unit 2020 may be configured to additionally decode the following syntax when trisoup at multiple levels is not permitted, that is, when the value of trisoup_multilevel_enabled_flag is "0".
  • GSH 2012 may include syntax (log2_trisoup_node_size_minus2) that defines the Trisoup node size when not allowing Trisoup at multiple levels and when using Trisoup.
  • the syntax may be expressed as a value obtained by converting the actual Trisoup node size into a base-2 logarithm. Furthermore, the syntax may be expressed as a value obtained by subtracting 2 after converting the actual Trisoup node size to a base 2 logarithm.
  • GSH2012 may include syntax (trisoup_sampling_value_minus1) that controls the sampling interval of decoding points.
  • a specific definition of the syntax can be, for example, the same as the definition described in Non-Patent Document 1 mentioned above.
  • unique_segments_exist_flag[i] For example, if the value of unique_segments_exist_flag[i] is "1", it means that at least one unique segment exists in layer i. Furthermore, when the value of unique_segments_exist_flag[i] is "0", it means that there is no unique segment in layer i.
  • GSH2012 additionally adds the syntax indicating the number of unique segments.
  • the syntax indicating the number of unique segments may include a syntax indicating the number of bits (num_unique_segments_bits_minus1[i]) and a syntax indicating the number of unique segments of the target layer (num_unique_segments_minus1[i]).
  • the values obtained by subtracting "1" from the respective original values may be encoded as syntax values.
  • FIG. 6 is an example of the syntax configuration of GSH2012. Hereinafter, only the differences from FIG. 5 will be explained.
  • the adaptive Octree mode when the adaptive Octree mode is enabled, that is, when the value of adaptive_octree_enabled_flag is "1", decoding of the syntax (log2_trisoup_min_node_size_minus2) that specifies the minimum value of the Trisoup node size may be omitted. .
  • the minimum value of the Trisoup node size may be regarded as a predetermined value.
  • the geometric information decoding unit 2010 decodes the flag that controls whether or not only Octree and Trisoup can be used within the same slice or data unit, and the value of the flag is set to "Used”. If "possible” is indicated, the configuration may be such that the value of the minimum Trisoup node size is implicitly assumed to be 1 ⁇ 1 ⁇ 1.
  • FIG. 7 is an example of the syntax configuration of GSH2012. Hereinafter, only the differences from FIG. 5 will be explained.
  • the values are transmitted after being converted to logarithms with a base of 2. It may also be a thing.
  • the geometric information decoding unit 2010 may be configured to decode the minimum Trisoup node size, and the minimum possible value of the minimum Trisoup node size is a value corresponding to 1 ⁇ 1 ⁇ 1. .
  • FIG. 6 is a flowchart illustrating an example of processing in the tree synthesis unit 2020. Note that an example in which trees are synthesized using "Octree" will be described below.
  • step S801 the tree synthesis unit 2020 checks whether all Depth processing has been completed. Note that the depth number may be included as control data in the bitstream transmitted from the point cloud encoding device 100 to the point cloud decoding device 200.
  • the tree synthesis unit 2020 calculates the node size of the target Depth.
  • the initial Depth node size may be defined as "2 to the power of the Depth number”. That is, when the number of Depths is N, the node size of the first Depth may be defined as 2 to the N power.
  • the node size is always defined as a power of 2
  • the value of the exponent part (N, N-1, N-2, etc.) may simply be considered the node size.
  • the node size refers to the value of the exponent part of the length of one side of the node.
  • the following explanation will be based on an example where the node shape is a cube, that is, where all sides of the node have the same length.
  • the length of the shortest side among the three directions is taken as the node size. You can think about it. Similarly, the length of the longest side among the three directions may be considered as the node size.
  • the tree synthesis unit 2020 processes The Depth number may be changed based on the value of the syntax (log2_trisoup_min_node_size_minus2) that defines the minimum value of the Trisoup node size or the syntax (log2_trisoup_node_size_minus2) that defines the Trisoup node size. In such a case, for example, it may be defined as follows.
  • the minimum Trisoup node size can be defined, for example, as (log2_trisoup_min_node_size_minus2+2). Similarly, the Trisoup node size can be defined as (log2_trisoup_node_size_minus2+2).
  • step S809 if the processing for all processing depths has been completed, the tree synthesis unit 2020 proceeds to step S809; otherwise, the tree synthesis unit 2020 proceeds to step S802.
  • the tree synthesis unit 2020 may determine that Trisoup is applied to all nodes having the node size (N - number of processing depths) when proceeding to step S809.
  • Step S801 may be configured as follows.
  • step S809 if the processing of all depths is completed, the tree synthesis unit 2020 proceeds to step S802.
  • step S802 the tree synthesis unit 2020 determines whether it is necessary to decode Trisoup_applied_flag, which will be described later, at the target Depth.
  • the tree synthesis module 2020 may determine that "Decoding of Trisoup_applied_flag is required.”
  • the tree synthesis unit 2020 may determine that "the Trisoup_applied_flag needs to be decoded” when the node size (N-n) of the Trisoup node size (N-n) is greater than or equal to the minimum Trisoup node size.
  • the tree synthesis unit 2020 may determine that "decoding of Trisoup_applied_flag is not necessary" if the above-mentioned conditions are not satisfied.
  • the maximum Trisoup node size can be defined, for example, as (log2_trisoup_max_node_size_minus3+2).
  • the minimum Trisoup node size can be defined, for example, as (log2_trisoup_min_node_size_minus2+2).
  • step S803 the tree synthesis unit 2020 moves to step S803.
  • step S803 the tree synthesis unit 2020 determines whether processing of all nodes included in the target Depth has been completed.
  • the tree synthesis unit 2020 moves to step S801 and performs the processing of the next Depth.
  • step S804 the tree synthesis unit 2020 checks whether or not the Trisoup_applied_flag determined in step S802 needs to be decoded.
  • step S805 If it is determined that decoding of Trisoup_applied_flag is necessary, the tree synthesis unit 2020 proceeds to step S805, and if it is determined that decoding of Trisoup_applied_flag is not necessary, the tree synthesis unit 2020 proceeds to step S808. .
  • step S805 the tree synthesis unit 2020 decodes Trisoup_applied_flag.
  • Trisoup_applied_flag is a 1-bit flag (second flag) indicating whether or not Trisoup is applied to the target node. For example, it may be defined that Trisoup is applied to the target node when the value of the flag is "1", and it may be defined that Trisoup is not applied to the target node when the value of the flag is "0".
  • step S806 After decoding the Trisoup_applied_flag, the tree synthesis unit 2020 moves to step S806.
  • step S806 the tree synthesis unit 2020 checks the value of Trisoup_applied_flag decoded in step S805.
  • Trisoup is to be applied to the target node, that is, if the value of Trisoup_applied_flag is "1"
  • the tree synthesis unit 2020 moves to step S807.
  • Trisoup is not applied to the target node, that is, if the value of Trisoup_applied_flag is "0", the tree synthesis unit 2020 moves to step S808.
  • step S807 the tree synthesis unit 2020 stores the target node as a node to which Trisoup is applied, that is, a Trisoup node. Node division using "Octree" will no longer be applied to such target nodes. After that, the tree synthesis unit 2020 advances to step S803 and moves to processing the next node.
  • step S808 the tree synthesis unit 2020 decodes information called occpancy code.
  • the occpancy code is used to divide the target node in half in each of the x, y, and z axes directions and divide it into 8 nodes (called child nodes). This is information indicating whether a point to be decoded is included.
  • the occpancy code allocates 1 bit of information to each child node, and if this 1 bit of information is "1", it is defined that the point to be decoded is included in the child node, and such 1 bit of information is "1". If the bit information is "0", it may be defined that the point to be decoded is not included in the child node.
  • the tree synthesis unit 2020 estimates in advance the probability that a point to be decoded exists in each child node, and entropy decodes the bits corresponding to each child node based on that probability. good.
  • the point cloud encoding device 100 may perform entropy encoding.
  • the point cloud decoding device 200 can use both Octree only and Trisoup within the same slice or data unit, and uses either Octree only or Trisoup for each node to extract geometric information of points. may be configured to decrypt the .
  • the tree synthesis unit 2020 performs Octree division to recursively divide the space, and decodes geometric information only using Octree for all nodes that are smaller than a predetermined minimum Trisoup node size. may be configured.
  • the tree synthesis unit 2020 decodes, for each node of a predetermined minimum Trisoup node size, a flag (Trisoup_applied_flag) indicating whether or not to apply Trisoup to the node. It may be configured to do so.
  • the geometric information decoding unit 2010 decodes the flag that controls whether or not both Octree and Trisoup can be used within the same slice or data unit, and the tree synthesis unit 2020 , if the value of the flag indicates "usable", the configuration may be such that geometric information is decoded only by Octree for all nodes that are smaller than a predetermined minimum Trisoup node size.
  • FIG. 9 is a flowchart illustrating an example of processing in the tree synthesis unit 2020.
  • the same reference numerals are given to the parts that perform the same processing as in FIG. 8, and the description thereof will be omitted.
  • step S901 if the processing for all processing depths has been completed, the tree synthesis unit 2020 proceeds to step S809; otherwise, the tree synthesis unit 2020 proceeds to step S802.
  • the tree synthesis unit 2020 uses the syntax (see figure It may be changed based on the value of log2_trisoup_node_size) shown in 7. At this time, the tree synthesis unit 2020 may set the minimum value of the Trisoup node size to 0.
  • the tree synthesis unit 2020 may implicitly set the minimum value of the Trisoup node size to 0 when the adaptive Octree mode is enabled. In such a case, for example, it may be defined as follows.
  • step S902 the tree synthesis unit 2020 determines whether it is necessary to decode Trisoup_applied_flag, which will be described later, at the target Depth.
  • the tree synthesis module 2020 may determine that "Decoding of Trisoup_applied_flag is required.”
  • the tree synthesis unit 2020 applies Trisoup to all nodes with the corresponding node size. It may be determined that
  • the tree synthesis unit 2020 uses the approximation described below.
  • the 1 ⁇ 1 ⁇ 1 node itself may be regarded as a decoded point, similar to when only Octree is executed without performing Trisoup processing.
  • the tree synthesis unit 2020 sets the predetermined minimum Trisoup node size to 1, and for nodes whose node size is 1 ⁇ 1 ⁇ 1, the tree synthesis unit 2020 uses only Octree to set the node size to 1 ⁇ 1 ⁇ 1.
  • Trisoup may be configured to each decide to decode the geometric information.
  • the above configuration has the advantage that the processing can be shared with the case where only Trisoup is used.
  • the approximate surface synthesis unit 2030 is configured to perform decoding processing on each node determined to be a Trisoup node by the tree synthesis unit 2020, as described with reference to FIGS. 10 and 14.
  • FIG. 10 is a flowchart illustrating an example of the processing of the approximate surface synthesis unit 2030.
  • step S1001 the approximate surface synthesis unit 2030 determines whether processing for all trisoup_depths has been completed.
  • step S1009 If the processing is completed for all trisoup_depths, the process advances to step S1009 and ends the process. If all trisoup_depth processing has not been completed, the process advances to step S1002.
  • step S1002 the approximate surface synthesis unit 2030 acquires and integrates the vertex positions for each node.
  • the approximate surface synthesis unit 2030 decodes the vertex position for each node in the Trisoup node size (hereinafter referred to as the Trisoup node size) corresponding to the trisoup_depth. Specific processing will be explained with reference to FIG. 13.
  • the approximate surface synthesis unit 2030 performs an integration process with vertices generated at a Trisoup node size larger than the Trisoup node size in step S1008, which will be described later. .
  • the approximate surface synthesis unit 2030 decodes vertices decoded using the method described in FIG. 13 (vertices in the Trisoup node size) on the edge of the node in the Trisoup node size, and the method described in step S1008. If both generated vertices (vertices generated in a Trisoup node size larger than the Trisoup node size) exist, only the vertex generated in the largest node size is retained, and the other vertices are deleted. . By doing this, each node can have at most one vertex.
  • step S1003 After completing the acquisition and integration of the vertex positions, the approximate surface synthesis unit 2030 proceeds to step S1003.
  • step S1003 the approximate surface synthesis unit 2030 determines a projection plane for each node in the Trisoup node size.
  • a plane obtained by degenerating any one axis is called a projection plane.
  • step S1003 the approximate surface synthesis unit 2030 determines which axis among the above-mentioned axes is to be degenerated, that is, which plane among the x-y plane, x-z plane, and y-z plane is to be the projection plane. decide. A specific method for determining the projection plane will be omitted since a known method can be applied.
  • step S1004 After determining the projection plane, the approximate surface synthesis unit 2030 proceeds to step S1004.
  • step S1004 the approximate surface synthesis unit 2030 sorts the vertices projected onto the projection plane, for example, in a counterclockwise order, and assigns an index according to this order. Note that when sorting is performed during the process of step S1003, the process of step S1004 can be omitted by saving the results of the sorting.
  • step S1005 the approximate surface synthesis unit 2030 generates a triangle based on the above-mentioned index and the number of vertices existing in the target node.
  • the approximate surface synthesis unit 2030 creates a table in advance that defines from which index a triangle is to be generated for each number of vertices, and can generate a triangle by referring to the table.
  • a table for example, the table described in the above-mentioned Non-Patent Document 1 can be used.
  • the approximate surface synthesis unit 2030 may first generate a centroid by averaging the coordinates of each vertex, and then generate a triangle using the three points of the centroid and two adjacent points in the order of the indexes described above.
  • step S1006 After generating the triangle, the approximate surface synthesis unit 2030 proceeds to step S1006.
  • step S1006 the approximate surface synthesis unit 2030 generates points based on the triangles generated in step S1005.
  • the method described in the above-mentioned Non-Patent Document 1 can be used.
  • step S1007 the approximate surface synthesis unit 2030 proceeds to step S1007.
  • step S1007 the approximate surface synthesis unit 2030 determines whether the Trisoup node size is equal to the minimum node size.
  • the approximate surface synthesis unit 2030 proceeds to step S1001 and performs the next trisoup_depth process; otherwise, proceeds to step S1008.
  • step S1008 the approximate surface synthesis unit 2030 generates vertices at the minimum Trisoup node size based on the point group at the Trisoup node size generated at Step S1006 or the triangle generated at Step S1005.
  • FIG. 11 shows an example of generating vertices at the minimum Trisoup node size from the point group at the Trisoup node size generated in step S1006.
  • FIG. 11A shows an example of the decoded point group generated in step S1006.
  • the approximate surface synthesis unit 2030 divides the node into each minimum Trisoup node size, as shown by the dotted line in FIG. 11A.
  • the approximate surface synthesis unit 2030 checks whether each point in the decoded point group exists on each edge (solid line and dotted line in FIG. 11A) when divided for each minimum Trisoup node size.
  • each edge exists at an interval of 2 (N-1) from an arbitrary origin
  • the coordinates of the edge in the z-axis direction are (A ⁇ 2 (N-1), B ⁇ 2 (N-1) ), z).
  • a and B are constants.
  • the approximate surface synthesis unit 2030 can extract points existing on edges from the decoded point group by performing such processing on all edges when divided by the minimum Trisoup node size.
  • the approximate surface synthesis unit 2030 uses the decoded point group to extract points existing on the edge in the z-axis direction. It is also possible to divide the x and y coordinates of each point within by 2 (N-1), and extract the point where both the x and y coordinates have a remainder of zero as a point on the edge.
  • FIG. 11B shows an example of the extraction result of points existing on the edge.
  • the approximate surface synthesis unit 2030 extracts only points on edges that exist on the surface of the Trisoup node size, and excludes points on edges that exist inside the Trisoup node size as extraction targets. Good too.
  • the approximate surface synthesis unit 2030 stores the points on the edges extracted as described above as vertices in the minimum Trisoup node size.
  • the approximate surface synthesis unit 2030 executes the decoding process for vertices at each node size between the maximum and minimum based on the maximum node size and minimum node size decoded from the control data, and the node size is If the node size is not the minimum node size, generate the vertex position at the minimum node size based on the decoded vertices, and if there are multiple vertices on an edge generated from nodes with different node sizes adjacent to the edge. , the vertex generated by the node with the largest node size among such adjacent nodes may be configured to be the vertex position of the edge.
  • the configuration when generating the vertex position at the minimum node size, the configuration may be such that the vertex is generated only on the surface of the node.
  • the approximate surface synthesis unit 2030 calculates the The point may be configured to be the vertex position at the minimum node size.
  • vertices can be generated by interpolation from vertices in the Trisoup node size. You can.
  • the approximate surface synthesis unit 2030 calculates an equation for a straight line connecting adjacent vertices based on the result of sorting the vertices in step S1003 or step S1004.
  • FIG. 12A shows an example in which the Trisoup node is divided into the minimum Trisoup node size, and an example of vertices in the Trisoup node size.
  • FIG. 12A shows an example in which straight lines connecting the 0th and 1st vertices, the 1st and 2nd vertices, and the 2nd and 0th vertices are generated in the sorted Index.
  • the 0th and 1st vertices exist on the same surface.
  • the 2nd and 0th vertices also exist on the same surface.
  • the straight line connecting these two points can be excluded from calculation.
  • the equation of the straight line connecting the two vertices can be expressed as the equation of a two-dimensional planar straight line.
  • FIG. 12B shows an example of vertices generated by the method described above.
  • the approximate surface synthesis unit 2030 calculates the intersection between the straight line connecting two points of the node vertices and the side when dividing the node by the minimum node size. may be configured to be the vertex position at the minimum node size.
  • step S1001 After the generation of vertices is completed as described above, the process advances to step S1001.
  • FIG. 13 is a flowchart illustrating an example of the vertex decoding process used in step S1002.
  • step S1301 the approximate surface synthesis unit 2030 determines whether processing for all trisoup_depths has been completed.
  • step S1305 If the processing is completed for all trisoup_depths, the process advances to step S1305 and ends the process. If all trisoup_depth processing has not been completed, the process advances to step S1302.
  • step S1302 the approximate surface synthesis unit 2030 checks the number of unique segments belonging to the target Trisoup layer.
  • the approximate surface synthesis unit 2030 proceeds to step S1301 and moves to processing of the next Trisoup layer.
  • step S1303 If the number of unique segments is greater than "0", the approximate surface synthesis unit 2030 moves to step S1303.
  • step S1303 the approximate surface synthesis unit 2030 decodes each unique segment to determine whether the vertex used in the Trisoup process is included.
  • the number of vertices that can exist for each unique segment may be limited to only one point. In this case, it can be interpreted that the number of unique segments in which vertices exist is equal to the number of vertices.
  • step S1304 the approximate surface synthesis unit 2030 decodes, for each unique segment determined to have a vertex in step S1303, position information indicating where the vertex exists on each unique segment.
  • FIG. 14 is a flowchart illustrating an example of the process in step S1304.
  • step S1401 the approximate surface synthesis unit 2030 determines whether processing has been completed for all segments.
  • step S1406 If the processing is completed for all segments, the process advances to step S1406 and ends. If processing has not been completed for all segments, the process advances to step S1402.
  • step S1402 the approximate surface synthesis unit 2030 acquires the direction of the segment. Specifically, the approximate surface synthesis unit 2030 acquires whether the segment is in the x-axis, y-axis, or z-axis direction.
  • the approximate surface synthesis unit 2030 can determine which axis direction the vertex is along by holding information on the coordinates of the starting point and the coordinates of the ending point for each segment. After acquiring the direction of the segment as described above, the process advances to step S1403.
  • step S1403 the approximate surface synthesis unit 2030 obtains the size of the segment.
  • the size of the segment corresponds to the node size at Depth of the target Octree.
  • the size will be the same in all x-axis, y-axis, and z-axis directions.
  • QtBt the values may differ in each of the x-axis, y-axis, and z-axis directions.
  • the approximate surface synthesis unit 2030 obtains the size of the segment based on the node size in each of the x-axis, y-axis, and z-axis directions at the depth and the direction of the segment obtained in step S1402.
  • the approximate surface synthesis unit 2030 can subtract the coordinate value of the start point from the coordinate value of the end point. You can get the size of the segment.
  • step S1404 After obtaining the size of the segment, the approximate surface synthesis unit 2030 proceeds to step S1404.
  • step S1404 the approximate surface synthesis unit 2030 sets the size of the segment obtained in step S1403 as the maximum possible value of the Position of the vertex to be decoded. After that, the process advances to step S1405.
  • step S1405 the approximate surface synthesis unit 2030 sets the range of possible values of Position to 0 to "the maximum value set in S1404" - 1, and then decodes Position.
  • Position may be encoded with an L-bit equal length code (the point cloud decoding device 200 may decode on the premise that it is encoded in this way).
  • the approximate surface synthesis unit 2030 may perform entropy encoding/decoding using Huffman encoding, arithmetic encoding, etc. after setting the range of possible values of Position to 0 to 2L-1. After decoding Position, the approximate surface synthesis unit 2030 proceeds to step S1401.
  • the approximate surface synthesis unit 2030 sets the range of possible values of the vertex position for each segment according to the node shape, and sets the range of possible values of the vertex position.
  • the vertex position may be decoded based on the vertex position.
  • the approximate surface synthesis unit 2030 is configured to set the range of possible values of the vertex position based on the axial direction of each segment when generating segments from nodes and the node shape. may have been done.
  • the approximate surface synthesis unit 2030 may be configured to set the range of possible values of the vertex position based on the starting point coordinates and ending point coordinates of each segment.
  • Trisoup can be applied even when the node size is not a cube but a rectangular parallelepiped, and improvement in encoding efficiency can be expected.
  • FIG. 15 is a diagram illustrating an example of functional blocks of the point cloud encoding device 100 according to this embodiment.
  • the point cloud encoding device 100 includes a coordinate transformation section 1010, a geometric information quantization section 1020, a tree analysis section 1030, an approximate surface analysis section 1040, a geometric information encoding section 1050, Geometric information reconstruction section 1060, color conversion section 1070, attribute transfer section 1080, RAHT section 1090, LoD calculation section 1100, lifting section 1110, attribute information quantization section 1120, and attribute information encoding section 1130 and has.
  • the coordinate conversion unit 1010 is configured to perform conversion processing from a three-dimensional coordinate system of an input point group to an arbitrary different coordinate system.
  • the coordinate transformation may be, for example, by rotating the input point group to convert the x, y, and z coordinates of the input point group to arbitrary s, t, and u coordinates.
  • the coordinate system of the input point group may be used as is.
  • the geometric information quantization unit 1020 is configured to quantize the position information of the input point group after coordinate transformation and remove points with overlapping coordinates. Note that when the quantization step size is 1, the position information of the input point group and the position information after quantization match. That is, when the quantization step size is 1, it is equivalent to not performing quantization.
  • the tree analysis unit 1030 is configured to receive the position information of the quantized point group as input and generate an occupancy code indicating in which node of the encoding target space a point exists based on the tree structure described later. has been done.
  • the tree analysis unit 1030 is configured to generate a tree structure by recursively dividing the encoding target space into rectangular parallelepipeds.
  • a tree structure can be generated by recursively executing the process of dividing the rectangular parallelepiped into a plurality of rectangular parallelepipeds until the rectangular parallelepiped reaches a predetermined size.
  • each such rectangular parallelepiped is called a node.
  • each rectangular parallelepiped generated by dividing a node is called a child node, and the occurrence code is expressed as 0 or 1 to indicate whether a point is included in the child node.
  • the tree analysis unit 1030 is configured to generate an occupancy code while recursively dividing nodes until a predetermined size is reached.
  • the tree analysis unit 1030 determines the tree structure, and the determined tree structure is transmitted to the point cloud decoding device 200 as control data.
  • the tree-structured control data may be configured to be decoded using the procedure described in FIG. 6.
  • the approximate surface analysis unit 1040 is configured to generate approximate surface information using the tree information generated by the tree analysis unit 1030.
  • Approximate surface information is used, for example, when decoding 3D point cloud data of an object, when the point cloud is densely distributed on the object surface, instead of decoding each individual point cloud. This is an approximation of the region in which a group exists using a small plane.
  • the approximate surface analysis unit 1040 may be configured to generate approximate surface information using, for example, a method called "Trisoup.” Further, when decoding a sparse point group obtained by Lidar or the like, this process can be omitted.
  • the geometric information encoding unit 1050 encodes the syntax of the occupancy code generated by the tree analysis unit 1030 and the approximate surface information generated by the approximate surface analysis unit 1040 to generate a bit stream (geometric information bit stream). It is configured as follows.
  • the bitstream may include, for example, the syntax described in FIGS. 4 and 5.
  • the encoding process is, for example, context adaptive binary arithmetic encoding process.
  • the syntax includes control data (flags and parameters) for controlling the decoding process of position information.
  • the geometric information reconstruction unit 1060 reconstructs the geometric information (code) of each point of the point cloud data to be encoded based on the tree information generated by the tree analysis unit 1030 and the approximate surface information generated by the approximate surface analysis unit 1040. It is configured to reconstruct the coordinate system assumed by the conversion process, that is, the position information after coordinate transformation in the coordinate transformation unit 1010.
  • the color conversion unit 1070 is configured to perform color conversion when the input attribute information is color information. Color conversion does not necessarily need to be performed, and whether or not to perform color conversion processing is encoded as part of the control data and transmitted to the point cloud decoding device 200.
  • the attribute transfer unit 1080 distorts the attribute information based on the position information of the input point group, the position information of the point group after reconstruction in the geometric information reconstruction unit 1060, and the attribute information after color change in the color conversion unit 1070.
  • the attribute value is corrected so that the value is minimized.
  • the RAHT unit 1090 inputs the attribute information transferred by the attribute transfer unit 1080 and the geometric information generated by the geometric information reconstruction unit 1060, and uses a type of Haar transformation called RAHT (Region Adaptive Hierarchical Transform) to transform each
  • RAHT Region Adaptive Hierarchical Transform
  • the system is configured to generate point residual information.
  • RAHT Restion Adaptive Hierarchical Transform
  • the LoD calculation unit 1100 is configured to receive the geometric information generated by the geometric information reconstruction unit 1060 and generate LoD (Level of Detail).
  • LoD is a reference relationship (reference point and ) is the information for defining.
  • LoD is a hierarchy in which each point included in geometric information is classified into multiple levels, and attributes of points belonging to lower levels are encoded or decoded using attribute information of points belonging to higher levels. This is information that defines the structure.
  • the lifting unit 1110 is configured to generate residual information through lifting processing using the LoD generated by the LoD calculation unit 1100 and the attribute information after attribute transfer by the attribute transfer unit 1080.
  • the attribute information quantization unit 1120 is configured to quantize the residual information output from the RAHT unit 1090 or the lifting unit 1110.
  • the quantization step size is 1, it is equivalent to not performing quantization.
  • the attribute information encoding unit 1130 performs encoding processing using the quantized residual information etc. output from the attribute information quantization unit 1120 as syntax, and generates a bit stream related to attribute information (attribute information bit stream). It is configured as follows.
  • the encoding process is, for example, context adaptive binary arithmetic encoding process.
  • the syntax includes control data (flags and parameters) for controlling the decoding process of attribute information.
  • the point cloud encoding device 100 is configured to perform encoding processing by inputting the position information and attribute information of each point in the point cloud, and output a geometric information bitstream and an attribute information bitstream. ing.
  • point cloud encoding device 100 and point cloud decoding device 200 may be implemented as a program that causes a computer to execute each function (each step).
  • the present invention has been described with reference to the application to the point cloud encoding device 100 and the point cloud decoding device 200, but the present invention is not limited to only such examples.
  • the present invention can be similarly applied to a point cloud encoding/decoding system having the functions of the point cloud encoding device 100 and the point cloud decoding device 200.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Processing (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)

Abstract

Dans un dispositif de décodage de nuage de points (200) selon la présente invention, une unité de synthèse de surface d'approximation (2030) est configurée pour : exécuter, d'après une taille de nœud maximale et une taille de nœud minimale décodées à partir de données de commande, un processus de décodage sur des sommets de nœuds ayant des tailles entre le maximum et le minimum ; lorsqu'une taille de nœud n'est pas la taille de nœud minimale, générer une position de sommet pour la taille de nœud minimale d'après le sommet décodé ; et lorsqu'une pluralité de sommets générés à partir de nœuds ayant différentes tailles de nœud et adjacents à un certain côté sont présents sur le certain côté, définir, en tant que position de sommet du certain côté, un sommet généré par un nœud ayant la plus grande taille de nœud parmi les différents nœuds adjacents.
PCT/JP2023/008642 2022-07-08 2023-03-07 Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme WO2024009562A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2022110163A JP2024008354A (ja) 2022-07-08 2022-07-08 点群復号装置、点群復号方法及びプログラム
JP2022-110163 2022-07-08

Publications (1)

Publication Number Publication Date
WO2024009562A1 true WO2024009562A1 (fr) 2024-01-11

Family

ID=89452974

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2023/008642 WO2024009562A1 (fr) 2022-07-08 2023-03-07 Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme

Country Status (2)

Country Link
JP (1) JP2024008354A (fr)
WO (1) WO2024009562A1 (fr)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021065536A1 (fr) * 2019-10-01 2021-04-08 ソニー株式会社 Dispositif et procédé de traitement d'informations
WO2021261142A1 (fr) * 2020-06-22 2021-12-30 Kddi株式会社 Dispositif de décodage de groupe de points, procédé de décodage de groupe de points, et programme
WO2022138046A1 (fr) * 2020-12-25 2022-06-30 Kddi株式会社 Dispositif de décodage de nuage de points, procédé de décodage de nuage de points, et programme

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021065536A1 (fr) * 2019-10-01 2021-04-08 ソニー株式会社 Dispositif et procédé de traitement d'informations
WO2021261142A1 (fr) * 2020-06-22 2021-12-30 Kddi株式会社 Dispositif de décodage de groupe de points, procédé de décodage de groupe de points, et programme
WO2022138046A1 (fr) * 2020-12-25 2022-06-30 Kddi株式会社 Dispositif de décodage de nuage de points, procédé de décodage de nuage de points, et programme

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
DRICOT, ANTOINE ET AL.: "Adaptive Multi-level Triangle Soup for Geometrybased Point Cloud Coding", 2019 IEEE 21ST INTERNATIONAL WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, September 2019 (2019-09-01), pages 1 - 6, XP033660072, DOI: 10.1109/MMSP.2019.8901791 *
WANG, CHAOFEI ET AL.: "Point-Voting based Point Cloud Geometry Compression", 2021 IEEE 23RD INTERNATIONAL WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, October 2021 (2021-10-01), pages 1 - 5, XP034102627, DOI: 10.1109/MMSP53017.2021.9733633 *

Also Published As

Publication number Publication date
JP2024008354A (ja) 2024-01-19

Similar Documents

Publication Publication Date Title
JP7257547B2 (ja) 点群圧縮のための方法及び装置、並びにコンピュータプログラム
CN113615181B (zh) 用于点云编解码的方法、装置
KR20210134049A (ko) 포인트 클라우드 데이터 송신 장치, 포인트 클라우드 데이터 송신 방법, 포인트 클라우드 데이터 수신 장치 및 포인트 클라우드 데이터 수신 방법
JP7233561B2 (ja) 点群圧縮のための方法並びにその、装置およびコンピュータプログラム
JP6178798B2 (ja) 終了可能な空間ツリー型位置符号化および復号
JP7263550B2 (ja) 点群の情報をコーディングする方法及び装置、及びコンピュータプログラム
WO2022070469A1 (fr) Dispositif de décodage de groupe de points, procédé de décodage de groupe de points, et programme
JP2024022620A (ja) 点群復号装置、点群復号方法及びプログラム
CN113179411A (zh) 点云属性编解码方法、装置、计算机设备及存储介质
WO2022071284A1 (fr) Dispositif de décodage de groupe de points, procédé de décodage de groupe de points, et programme
WO2024009562A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme
WO2024009561A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme
WO2024009675A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme
WO2024009676A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme
WO2023074673A1 (fr) Dispositif de codage, dispositif de décodage, procédé de codage, et procédé de décodage
WO2021256486A1 (fr) Dispositif de décodage de groupe de points, procédé de décodage de groupe de points et programme
WO2022071282A1 (fr) Dispositif de décodage de groupe de points, procédé de décodage de groupe de points, et programme
WO2022071285A1 (fr) Dispositif de décodage de groupe de points, procédé de décodage de groupe de points, et programme
WO2023277128A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme
JP2024058011A (ja) 点群復号装置、点群復号方法及びプログラム
JP2024058012A (ja) 点群復号装置、点群復号方法及びプログラム
WO2023132330A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points, et programme
WO2023132331A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points, et programme
WO2023132329A1 (fr) Dispositif de décodage de nuage de points, procédé de décodage de nuage de points et programme
WO2024075608A1 (fr) Dispositif de codage, dispositif de décodage, procédé de codage et procédé de décodage

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23835103

Country of ref document: EP

Kind code of ref document: A1