WO2023181872A1 - 情報処理装置および方法 - Google Patents

情報処理装置および方法 Download PDF

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Publication number
WO2023181872A1
WO2023181872A1 PCT/JP2023/008228 JP2023008228W WO2023181872A1 WO 2023181872 A1 WO2023181872 A1 WO 2023181872A1 JP 2023008228 W JP2023008228 W JP 2023008228W WO 2023181872 A1 WO2023181872 A1 WO 2023181872A1
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Prior art keywords
inversion
geometry
range
bit
processing
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English (en)
French (fr)
Japanese (ja)
Inventor
朋哉 長沼
幸司 矢野
航 河合
智 隈
央二 中神
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Sony Group Corp
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Sony Group Corp
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Priority to US18/847,128 priority patent/US20250227216A1/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/10—Processing, recording or transmission of stereoscopic or multi-view image signals
    • H04N13/106—Processing image signals
    • H04N13/161—Encoding, multiplexing or demultiplexing different image signal components
    • 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
    • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/96—Tree coding, e.g. quad-tree coding
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/40—Tree coding, e.g. quadtree, octree

Definitions

  • the present disclosure relates to an information processing device and method, and particularly relates to an information processing device and method that can suppress reduction in encoding efficiency.
  • Non-Patent Document 1 discloses a mode and a flag for controlling the resolution of point cloud data expressed in Octree.
  • nodes can be deleted for areas where points do not exist, but up to leaf nodes (highest resolution) are generated for areas where points exist. Therefore, when the points are dense, the encoding efficiency may be lower than when the points are sparse.
  • the present disclosure has been made in view of this situation, and is intended to suppress reduction in encoding efficiency.
  • An information processing device includes an inversion processing unit that performs inversion processing on an inversion range in a tree structure expressing the geometry of a point cloud, and geometry data having the tree structure on which the inversion processing has been performed.
  • an encoding unit that encodes the inversion range, the inversion range is a node range that is made up of an inversion root node and descendant nodes of the inversion root node, and is the target of the inversion process, and the inversion process is a node range that is a target of the inversion process.
  • the information processing apparatus performs processing that inverts the bit patterns of leaf nodes included in the range and makes the bit patterns of non-leaf nodes included in the inverted range correspond to the bit patterns of child nodes.
  • An information processing method includes performing an inversion process on an inversion range in a tree structure expressing the geometry of a point cloud, and encoding geometry data having the tree structure subjected to the inversion process,
  • the inversion range is configured by an inversion root node and descendant nodes of the inversion root node, and is a node range to be subjected to the inversion process, and the inversion process inverts the bit patterns of leaf nodes included in the inversion range.
  • the information processing method is a process of making the bit pattern of a non-leaf node included in the inversion range correspond to the bit pattern of a child node.
  • An information processing device includes a decoding unit that decodes encoded data of geometry data of a point cloud, and a tree structure expressing the geometry of the point cloud, which the geometry data obtained by decoding has. and an inversion processing unit that performs inversion processing on an inversion range, the inversion range being a node range that is made up of an inversion root node and descendant nodes of the inversion root node and that is the target of the inversion processing,
  • the inversion process is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • An information processing method includes decoding encoded data of geometry data of a point cloud, and inverting a tree structure representing the geometry of the point cloud, which the geometry data obtained by decoding has.
  • An inversion process is performed on the range, the inversion range is a node range that is made up of an inversion root node and descendant nodes of the inversion root node, and is the target of the inversion process, and the inversion process is performed on the inversion range.
  • This information processing method is a process of inverting the bit patterns of included leaf nodes and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • an inversion process is performed on an inversion range in a tree structure expressing the geometry of a point cloud, and geometry data having the tree structure subjected to the inversion process is encoded.
  • the inversion range is composed of the inversion root node and the descendant nodes of the inversion root node. This is the node range that is the target of the inversion process, and the inversion process is such that the bit patterns of leaf nodes included in the inversion range are inverted, and the bit patterns of non-leaf nodes included in the inversion range are changed to the bit patterns of child nodes.
  • encoded data of geometry data of a point cloud is decoded, and the geometry data obtained by decoding has a tree structure representing the geometry of the point cloud.
  • the inversion process is performed on the inversion range.
  • the inversion range is composed of an inversion root node and descendant nodes of the inversion root node, and is a node range to be subjected to the inversion process.
  • the inversion process is a process in which the bit patterns of leaf nodes included in the inversion range are inverted, and the bit patterns of non-leaf nodes included in the inversion range are made to correspond to the bit patterns of child nodes.
  • FIG. 3 is a diagram illustrating an example of voxel representation of geometry.
  • FIG. 2 is a diagram illustrating an example of Octree.
  • FIG. 6 is a diagram illustrating a case where points are dense.
  • FIG. 3 is a diagram illustrating various methods of bit inversion.
  • FIG. 3 is a diagram illustrating an example of reversal processing.
  • FIG. 3 is a diagram illustrating an example of a reversal area.
  • FIG. 3 is a diagram illustrating an example of a bit inversion flag.
  • FIG. 3 is a diagram illustrating an example of a reversal area.
  • FIG. 6 is a diagram illustrating an example of a method for estimating the number of deletions.
  • FIG. 6 is a diagram illustrating an example of a method for estimating the number of deletions.
  • FIG. 2 is a block diagram showing an example of the main configuration of a geometry encoding device.
  • 3 is a flowchart illustrating an example of the flow of geometry encoding processing.
  • 3 is a flowchart illustrating an example of the flow of bit reversal processing.
  • 13 is a flowchart following FIG. 12 illustrating an example of the flow of bit inversion processing.
  • FIG. 2 is a block diagram showing an example of the main configuration of a geometry decoding device.
  • 3 is a flowchart illustrating an example of the flow of geometry decoding processing.
  • 12 is a flowchart illustrating another example of the flow of geometry encoding processing.
  • 12 is a flowchart illustrating another example of the flow of geometry decoding processing.
  • FIG. 2 is a block diagram showing a main configuration example of a point cloud encoding device.
  • 12 is a flowchart illustrating an example of the flow of point cloud encoding processing.
  • FIG. 2 is a block diagram showing a main configuration example of a point cloud decoding device.
  • 12 is a flowchart illustrating an example of the flow of point cloud decoding processing.
  • FIG. 3 is a diagram illustrating point cloud formation of a 3D Occupancy Grid map.
  • FIG. 3 is a diagram illustrating generation of a 3D Occupancy Grid map.
  • FIG. 3 is a diagram illustrating generation of a 3D Occupancy Grid map.
  • FIG. 3 is a diagram illustrating generation of a 3D Occupancy Grid map.
  • FIG. 3 is a diagram illustrating generation of a 3D Occupancy Grid map.
  • FIG. 3 is a diagram illustrating generation of a 3D Occupancy Grid map.
  • FIG. 3 is a diagram illustrating generation
  • FIG. 3 is a diagram illustrating an example of a point cloud.
  • FIG. 3 is a diagram illustrating an example of a point cloud.
  • FIG. 2 is a block diagram showing a main configuration example of a 3D Occupancy Grid map encoding device.
  • 12 is a flowchart illustrating an example of the flow of 3D Occupancy Grid map encoding processing.
  • FIG. 2 is a block diagram showing a main configuration example of a 3D Occupancy Grid map decoding device.
  • 12 is a flowchart illustrating an example of the flow of 3D Occupancy Grid map decoding processing.
  • 1 is a block diagram showing an example of the main configuration of a computer.
  • FIG. 1 is a block diagram showing an example of the main configuration of a computer.
  • Non-patent document 1 (mentioned above)
  • the contents described in the above-mentioned non-patent documents and the contents of other documents referred to in the above-mentioned non-patent documents are also the basis for determining support requirements.
  • Point cloud data (also referred to as point cloud data) is composed of the geometry (position information) and attributes (attribute information) of each point that makes up the point cloud. Geometry indicates the location of that point in three-dimensional space. Attribute indicates the attribute of the point. This attribute can contain arbitrary information. For example, the attributes may include color information, reflectance information, normal line information, etc. of each point. In this way, the point cloud has a relatively simple data structure, and by using a sufficiently large number of points, any three-dimensional structure can be expressed with sufficient accuracy.
  • a voxel is a region obtained by dividing a three-dimensional spatial region containing an object.
  • the position of each point of the point cloud is such that it is located at a predetermined location (eg, the center) within such a voxel. In other words, it represents whether or not a point exists within each voxel.
  • this method of expressing geometry using voxels is also referred to as voxel expression.
  • One voxel can be divided into multiple voxels. In other words, by recursively and repeatedly dividing voxels, the size of each voxel can be made smaller. The smaller the voxel size, the higher the resolution. In other words, the position of each point can be expressed more accurately. In other words, the effect of reducing the amount of geometry data due to the quantization described above is suppressed.
  • voxels shown in gray indicate voxels that include points. That is, points exist in voxel 12 and voxel 13 among the eight voxels in three-dimensional region 11.
  • Voxel 12 can be further divided into eight voxels (2x2x2). Among the eight voxels, a point exists in voxel 14. Voxel 14 can be further divided into eight voxels (2x2x2). Among the eight voxels, points exist in voxel 15, voxel 16, and voxel 17.
  • voxel 13 can be further divided into eight voxels (2x2x2). Of the eight voxels, points exist in voxel 18 and voxel 19. Voxel 18 can be further divided into eight voxels (2x2x2). Among the eight voxels, points exist in voxel 20 and voxel 21. Voxel 19 can be further divided into eight voxels (2x2x2). Among the eight voxels, a point exists in voxel 22.
  • each voxel is shown with the same size in FIG. 1, but in reality, the voxel on the right side of the figure (that is, the more the division is repeated), the smaller the voxel becomes. In this way, with voxel representation, geometry can be represented using a hierarchical structure.
  • the voxel representation indicates whether a point exists in each voxel.
  • the geometry can be expressed in a tree structure as shown in Figure 2 by using voxels in each layer as nodes and expressing whether or not a point exists for each divided voxel using 0 and 1. .
  • one voxel is divided into eight parts, so in FIG. 2, the presence or absence of a point in the voxel one layer below in each node is indicated by an 8-bit bit pattern.
  • the geometry is expressed by an octree.
  • this method of representing geometry using Octree is also referred to as Octree representation.
  • the bit patterns of each node are arranged in a predetermined order and encoded.
  • a tree structure expressing such geometry is also referred to as a geometry tree structure.
  • This geometry tree structure is also referred to as a voxel tree structure because it corresponds to voxel expression.
  • bit reversal of geometry > Therefore, as shown in the top row of the table in FIG. 4, some or all nodes of the voxel tree structure (geometry tree structure) can be set to a bit-inverted state (method 1).
  • a bit inversion state refers to a state in which inversion processing has been performed.
  • conversion processing refers to inverting the bit pattern of a leaf node, and converting the bit pattern of the ancestor node of that leaf node (a node higher than that to which the leaf node belongs (also referred to as a non-leaf node)) to the bit pattern of a child node. Indicates processing that corresponds to a pattern.
  • bit pattern refers to a bit pattern that indicates whether a point exists in each voxel in the next lower layer of a node in the geometry tree structure.
  • conversion refers to a process of converting a bit with a value of "0" in a bit pattern to a value of "1", and converting a bit with a value of "1” to a value of "0". That is, for example, if the bit pattern of "00110011" is inverted, it becomes "11001100".
  • corresponding to the bit pattern of a child node means to correspond to a child node (that is, a voxel where a point exists) whose bit pattern includes the value "1" among the bit patterns of the processing target node.
  • This is a process in which the value of a bit is set to "1" and the value of a bit corresponding to a child node where all bits of the bit pattern have a value of "0" (that is, a voxel where no point exists) is set to "0". That is, such inversion processing can be performed on some or all nodes of the geometry tree structure.
  • an information processing device includes an inversion processing unit that performs an inversion process on an inversion range in a tree structure expressing the geometry of a point cloud, and a code that encodes geometry data having a tree structure that has undergone the inversion process. It should be equipped with a conversion section.
  • the "inversion range” is configured by an inversion root node and descendant nodes of the inversion root node, and is a node range to be subjected to inversion processing.
  • the "inversion process” is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • an inversion process is performed on an inversion range in a tree structure expressing the geometry of a point cloud, and geometry data having the tree structure subjected to the inversion process is encoded.
  • the "inversion range” is configured by an inversion root node and descendant nodes of the inversion root node, and is a node range to be subjected to inversion processing.
  • the "inversion process” is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • an information processing device may use a decoding unit that decodes encoded data of geometry data of a point cloud, and a tree structure representing the geometry of the point cloud, which the geometry data obtained by decoding has, in an inversion range. and an inversion processing section that performs inversion processing on the image.
  • the "inversion range” is configured by an inversion root node and descendant nodes of the inversion root node, and is a node range to be subjected to inversion processing.
  • the "inversion process” is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • encoded data of point cloud geometry data is decoded, and the tree structure representing the geometry of the point cloud, which is included in the decoded geometry data, is inverted with respect to the inversion range.
  • the "inversion range” is configured by an inversion root node and descendant nodes of the inversion root node, and is a node range to be subjected to inversion processing.
  • the "inversion process” is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • an intermediate node (a node other than the root node and a leaf node) is set as an inverted root node 52-1, and a descendant node of the inverted root node is
  • the node range including the leaf node 53, that is, a part of the geometry tree structure 51 may be set as the inverted range 54-1.
  • a plurality of inversion ranges may be set in one geometry tree structure.
  • an inverted range 54-1 including an inverted root node 52-1 and an inverted range 54-2 including an inverted root node 52-2 are set for the geometry tree structure 51. .
  • the description is given assuming that the geometry tree structure 51 is a binary tree.
  • the geometry tree structure 51 is a binary tree.
  • FIG. 6A and FIG. 6B only one leaf node is marked with a numeral (53), but all the lowest nodes of the geometry tree structure 51 indicated by white circles in the figures are leaves. This is node 53.
  • bit reversal flag For example, if the value of the bit reversal flag is "0", it may indicate that the reversal process will not be performed for the reversal range in which the node corresponding to the flag is the reversal root node. Further, when the value of the bit inversion flag is "1", it may be indicated that the inversion process is to be performed on the inversion range with the node corresponding to the flag as the inversion root node.
  • the information processing device further includes an inversion control unit that controls whether to perform inversion processing on an inversion range having the processing target node as an inversion root node based on a bit inversion flag corresponding to the processing target node. Good too.
  • bit pattern of a node whose points become “sparse” as a result of the inversion may be set to all 0s.
  • nodes with "sparse” points may be deleted.
  • the reversal processing unit may delete a node with a bit pattern indicating that points are sparse.
  • the inversion processing unit may delete nodes with a bit pattern of all 0s after performing the inversion process.
  • encoding and decoding are irreversible.
  • the definition of whether points are "sparse” or "dense” (also referred to as a sparse/dense condition) is arbitrary.
  • the case where only one point exists may be defined as “sparse", or the case where the ratio of the number of voxels including the point to the total number of voxels is less than or equal to a predetermined value may be defined as “sparse”.
  • only conditions indicating a "sparse” state may be set, only conditions indicating a "dense” state may be set, or conditions indicating a "sparse” state and a “dense” state may be set. Both conditions may be set.
  • a state that is not "sparse” may be a "dense” state, or a state that is neither "sparse” nor “dense” may exist.
  • the node to which the bit inversion flag is set is arbitrary. For example, when “Method 1-2" is applied, bit inversion flags that can be set independently of each other are set for all non-leaf nodes, as shown in the fifth row from the top of the table in Figure 4. (Method 1-2-1).
  • the flag setting unit may set bit inversion flags independently of each other for all nodes of the geometry tree structure.
  • the inversion control unit may control whether to perform inversion processing based on a bit inversion flag that is set for all nodes in the geometry tree structure and indicates whether to perform inversion processing for the inversion range. good.
  • one bit inversion flag may be set for a group of direct nodes as shown in the sixth row from the top of the table in FIG. 4 (Method 1-2). -2-2).
  • a lineal node group is a node group (node range) that is composed of nodes that are in a lineal relationship (parent-child relationship) with each other in the geometry tree structure.
  • the inversion ranges can be made non-overlapping.
  • the node that sets the bit inversion flag may be the first node to process, the Nth node to process (predetermined N, specified N), or the last node to process. Good too.
  • a single bit inversion flag may be set for the entire voxel tree structure as shown in the seventh row from the top of the table in FIG. 1-2-3). That is, in this case, the entire geometry tree structure can be the inversion range, as in the example of A in FIG. By doing so, the reversal process can be facilitated.
  • the flag setting unit may set one bit inversion flag for the entire geometry tree structure.
  • the inversion control unit may control whether to perform the inversion process based on a bit inversion flag that is set for the entire geometry tree structure.
  • bit inversion may be controlled based on encoding efficiency as shown in the ninth row from the top of the table in FIG. 4 (Method 1-2-4) .
  • the inversion control unit may control whether to perform the inversion process based on the encoding efficiency of the geometry encoded data.
  • the encoding efficiency may be derived for all patterns by combining cases in which inversion processing is performed and cases in which no inversion processing is performed for all settable inversion ranges, and the pattern with the highest encoding efficiency may be applied. By doing so, encoding can be performed with the highest encoding efficiency.
  • bit reversal may be controlled based on the existence ratio of points as shown in the 10th row from the top of the table in FIG. 4 (Method 1-2-5 ).
  • the existence ratio of points indicates the ratio of voxels in which points exist to all voxels in the processing target region.
  • the number of points included in the processing target area may be applied instead of the existence ratio of points.
  • the reversal control unit may control whether to perform the reversal process based on the number of points (or the proportion of points) within the reversal range. That is, in this case, it is estimated whether the points are "sparse" or "dense” based on the number of points (or the percentage of points existing).
  • child nodes (leaf nodes) 72-1 to 72-6 of the processing target node 71 have the bit pattern "11111111", and the child node 72-7 has the bit pattern "11111111”. It has a bit pattern "00001111”, and the child node 72-8 has a bit pattern "00000000”. Therefore, the processing target node 71 has the bit pattern "11111110".
  • the bit patterns of child nodes 72-1 to 72-6 become (00000000).
  • the bit pattern of child node 72-7 is (11110000).
  • the bit pattern of child node 72-8 is (11111111). Therefore, the bit pattern of the processing target node 71 is (00000011).
  • the number of deletions for each is [1]. Since the child node 72-7 is not deleted even after the inversion process, the number of deletions is [0]. Since the child node 72-8 is added after the reversal process (it is a node deleted in the state before the reversal process), the number of deletions is [-1].
  • This threshold value is arbitrary. It may be common to all nodes, it may be set for each hierarchy, it may be set for each area, or it may be set for each node. By doing so, reduction in encoding efficiency can be more easily suppressed.
  • the inversion process may be performed after generating nodes in areas where no points exist in the inversion range.
  • the inversion processing unit may perform the inversion process after generating nodes in areas where no points exist in the inversion range.
  • the geometry construction unit may construct the geometry of the three-dimensional space using the tree structure that has been subjected to the inversion process.
  • FIG. 10 is a block diagram illustrating an example of the configuration of a geometry encoding device that is one aspect of an information processing device to which the present technology is applied.
  • a geometry encoding device 100 shown in FIG. 10 is a device that encodes point cloud geometry data.
  • the geometry encoding device 100 performs ⁇ 2.
  • Geometry Bit Reversal>, the present technology described above is applied to encode geometry data.
  • FIG. 10 shows the main things such as the processing unit and the flow of data, and not all of the things shown in FIG. 10 are shown. That is, in the geometry encoding device 100, there may be processing units that are not shown as blocks in FIG. 10, or processes or data flows that are not shown as arrows or the like in FIG.
  • the geometry encoding device 100 includes an Octree generation section 101, an initialization section 102, a bit inversion control section 103, a flag setting section 104, an inversion processing section 105, and an encoding section 106.
  • the Octree generation unit 101 Based on the geometry data input to the geometry encoding device 100, the Octree generation unit 101 generates an Octree (geometry tree structure) of the geometry. The Octree generation unit 101 supplies the generated Octree (geometry tree structure) data to the initialization unit 102 .
  • the initialization unit 102 acquires Octree (geometry tree structure) data supplied from the Octree generation unit 101.
  • the initialization unit 102 performs processing related to initialization. For example, the initialization unit 102 initializes the bit inversion flag set for Octree (geometry tree structure) (set it to an initial value (for example, "0")).
  • the initialization unit 102 also initializes the processing target node (sets it as the node to be processed first).
  • the initialization unit 102 supplies the data of the Octree (geometry tree structure) and the initialized information to the bit inversion control unit 103.
  • the flag setting unit 104 performs processing related to flag setting. For example, the flag setting unit 104 acquires information regarding the processing target node supplied from the bit inversion control unit 103. The flag setting unit 104 appropriately sets a bit inversion flag for the processing target node. The flag setting unit 104 supplies information regarding the processing target node and the set bit determination flag to the inversion processing unit 105.
  • the inversion processing unit 105 obtains information regarding the processing target node, the set bit determination flag, etc. supplied from the flag setting unit 104.
  • the reversal processing unit 105 performs reversal processing on the processing target node. At this time, the reversal processing unit 105 performs the process of ⁇ 2. Inversion processing is performed by applying the above-described present technique in the section ⁇ Bit Inversion of Geometry''.
  • the inversion processing unit 105 supplies information such as inversion processing results and bit determination flags to the encoding unit 106.
  • each of these processing units (Octree generation unit 101 to encoding unit 106) of the geometry encoding device 100 has an arbitrary configuration.
  • each processing section may be configured with a logic circuit that implements the above-described processing.
  • each processing unit has, for example, a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), etc., and by executing a program using these, the above processing is realized. You can do it like this.
  • each processing unit may have both configurations, and may implement some of the above-mentioned processing by a logic circuit and the others by executing a program.
  • each processing unit may be independent of each other; for example, some processing units may implement part of the above processing using logic circuits, and other processing units may implement the above processing by executing a program.
  • the above-described processing may be realized by another processing unit using both a logic circuit and a program execution.
  • FIG. 11 An example of the flow of geometry encoding processing executed by this geometry encoding apparatus 100 will be described with reference to the flowchart of FIG. 11. Note that the example in FIG. 11 is an example in which method 1-2-1 is applied to set bit inversion flags that can be set independently of each other for all non-leaf nodes.
  • the Octree generation unit 101 When the geometry encoding process is started, the Octree generation unit 101 generates an Octree pattern (geometry tree structure) based on the supplied geometry data in step S101.
  • step S102 the initialization unit 102 initializes the bit inversion flags of all nodes (for example, sets them to OFF).
  • step S103 the initialization unit 102 initializes the processing target node.
  • step S106 the flag setting unit 104 turns on the bit determination flag of the processing target node.
  • step S107 the inversion processing unit 105 executes inversion processing with the processing target node as the inversion root node.
  • the process proceeds to step S108. Further, if it is determined in step S104 that the bits of the processing target node are not to be inverted, the bit inversion control unit 103 advances the process in step S105 to step S108.
  • step S108 the bit inversion control unit 103 determines whether all nodes of the geometry tree structure have been processed. If there are unprocessed nodes, the process advances to step S109.
  • step S109 the bit inversion control unit 103 updates the processing target node to the next node.
  • the process in step S109 ends, the process returns to step S104. That is, the processes from step S104 to step S109 are repeatedly executed, and each node of the geometry tree structure is processed as a processing target. If it is determined in step S108 that all nodes of the geometry tree structure have been processed, the process proceeds to step S110.
  • step S110 the encoding unit 106 encodes the geometry data and generates geometry encoded data.
  • the reversal processing unit 105 When the bit reversal process is started, the reversal processing unit 105 generates a node in an area where no point exists in step S131 of FIG. In step S132, the reversal processing unit 105 stores the processing target node in the stack.
  • step S133 the reversal processing unit 105 determines whether the stack is not empty. If it is determined that the stack is not empty, the process proceeds to step S134. In step S134, the reversal processing unit 105 takes out the node from the stack.
  • step S135 the reversal processing unit 105 determines whether the extracted node is a leaf node. If it is determined that the node is a leaf node, the process proceeds to step S135. In step S136, the inversion processing unit 105 inverts the bit pattern of the extracted node.
  • step S137 if the bit pattern after inversion is all 0, the inversion processing unit 105 deletes that node.
  • step S138 the reversal processing unit 105 marks the extracted node as processed. When the process in step S138 ends, the process returns to step S133.
  • step S135 if it is determined in step S135 that the extracted node is a non-leaf node, the process proceeds to FIG. 13.
  • step S141 of FIG. 13 the reversal processing unit 105 determines whether all descendant nodes of the extracted node have been processed. If it is determined that there are unprocessed nodes, the process proceeds to step S142. In step S142, the reversal processing unit 105 stores the extracted node and its child nodes in the stack in this order. When the process in step S142 ends, the process returns to step S133 in FIG. 12.
  • step S141 of FIG. 13 if it is determined that all descendant nodes of the extracted node have been processed, the process proceeds to step S143.
  • step S143 the inversion processing unit 105 updates the bit pattern of the processing target node to correspond to the bit pattern of the child node.
  • the process in step S143 ends, the process returns to step S137 in FIG. 12.
  • the geometry encoding device 100 can suppress a reduction in the encoding efficiency of geometry encoded data.
  • FIG. 14 is a block diagram illustrating an example of the configuration of a geometry decoding device that is one aspect of an information processing device to which the present technology is applied.
  • a geometry decoding device 200 shown in FIG. 14 is a decoding device corresponding to the geometry encoding device 100, and decodes geometry encoded data to generate geometry data.
  • the geometry decoding device 200 performs ⁇ 2.
  • Geometry encoded data is decoded by applying the above-described present technique in the section ⁇ Bit inversion of geometry''.
  • the geometry decoding device 200 includes a decoding section 201, an initialization section 202, a bit inversion control section 203, an inversion processing section 204, and a geometry construction section 205.
  • the decoding unit 201 acquires geometry encoded data.
  • the decoding unit 201 decodes the geometry data and obtains Octree (geometry tree structure) data that has been appropriately inverted.
  • the decoding unit 201 supplies the data to the initialization unit 202.
  • the initialization unit 202 acquires Octree (geometry tree structure) data supplied from the decoding unit 201 and subjected to appropriate inversion processing.
  • the initialization unit 202 performs processing related to initialization. For example, the initialization unit 202 initializes the processing target node (sets it as the first node to be processed). When the initialization process is completed, the initialization unit 202 supplies the data of the Octree (geometry tree structure) and the initialized information to the bit inversion control unit 203.
  • the bit inversion control unit 203 acquires Octree (geometry tree structure) data and initialized information supplied from the initialization unit 202.
  • the bit inversion control unit 203 uses them to perform processing related to control of inversion processing. For example, the bit reversal control unit 203 determines whether or not to perform reversal processing (bit reversal) on the processing target node, and performs control. Further, the bit inversion control unit 203 controls updating of the processing target node.
  • the bit inversion control unit 203 supplies information regarding the processing target node to the inversion processing unit 204.
  • FIG. 15 An example of the flow of geometry decoding processing executed by this geometry decoding device 200 will be described with reference to the flowchart of FIG. 15. Note that the example in FIG. 15 is an example in which method 1-2-1 is applied to set bit inversion flags that can be set independently of each other for all non-leaf nodes.
  • the decoding unit 201 decodes the supplied geometry encoded data in step S201.
  • the decoding unit 201 constructs an Octree using the decoding result based on step S202, and generates Octree (geometry tree structure) data that has been appropriately inverted.
  • step S205 the inversion processing unit 204 executes inversion processing with the processing target node as the inversion root node.
  • the flow of this reversal process is the same as that described with reference to the flowcharts of FIGS. 12 and 13.
  • step S206 the process advances to step S206. Furthermore, if it is determined in step S204 that the bit inversion flag of the processing target node is off, the process proceeds to step S206.
  • step S207 the bit inversion control unit 203 updates the processing target node to the next node.
  • the process in step S207 ends, the process returns to step S204. That is, the processes from step S204 to step S209 are repeatedly executed, and each node of the geometry tree structure is processed as a processing target. If it is determined in step S206 that all nodes of the geometry tree structure have been processed, the process proceeds to step S208.
  • the geometry decoding device 200 can correctly decode the geometry encoded data generated by the geometry encoding device 100. That is, geometry decoding device 200 can suppress a reduction in the encoding efficiency of geometry encoded data.
  • step S405 the bit reversal control unit 203 deletes the bit determination flag of the descendant node of the processing target node.
  • step S405 ends, the process advances to step S406.
  • Second embodiment> ⁇ Point cloud encoding device> ⁇ 2.
  • the present technique described above in ⁇ Geometry Bit Inversion'' is not limited to the example of the first embodiment, but can be applied to any device.
  • the present technology can also be applied to a point cloud encoding device that encodes point cloud data.
  • FIG. 18 shows the main things such as the processing unit and the flow of data, and not all of the things shown in FIG. 18 are shown. That is, in the point cloud encoding device 500, there may be a processing unit that is not shown as a block in FIG. 18, or there may be a process or a data flow that is not shown as an arrow or the like in FIG.
  • the geometry encoding unit 501 performs processing related to encoding geometry data. For example, the geometry encoding unit 501 acquires geometry data of point cloud data input to the point cloud encoding device 500. Geometry encoding section 501 encodes the geometry data to generate encoded data. At this time, the geometry encoding unit 501 performs the following steps: ⁇ 2. Geometry Bit Reversal>, the present technique described above is applied to encode geometry data. That is, the geometry encoding unit 501 has the same configuration as the geometry encoding device 100 (FIG. 10) and performs the same processing. Geometry encoding section 501 supplies generated geometry encoded data to geometry decoding section 502 and bitstream generation section 505.
  • Geometry data may change due to processing such as encoding or decoding (for example, points may increase/decrease or move). That is, the geometry data supplied from the geometry decoding section 502 may be different from the geometry data before being encoded by the geometry encoding section 501.
  • the point cloud generation unit 503 performs processing (also referred to as recolor processing) to match the attribute data with the geometry data (decoding result). That is, the point cloud generation unit 503 updates the attribute data to correspond to the update of the geometry data.
  • Point cloud generation section 503 supplies updated attribute data (attribute data corresponding to geometry data (decoding result)) to attribute encoding section 504.
  • the point cloud encoding device 500 can suppress a reduction in the encoding efficiency of geometry encoded data.
  • each of these processing units (geometry encoding unit 501 to bitstream generation unit 505) of the point cloud encoding device 500 has an arbitrary configuration.
  • each processing section may be configured with a logic circuit that implements the above-described processing.
  • each processing unit may have, for example, a CPU, ROM, RAM, etc., and the above-described processing may be realized by using these to execute a program.
  • each processing unit may have both configurations, and may implement some of the above-mentioned processing by a logic circuit and the others by executing a program.
  • each processing unit may be independent of each other; for example, some processing units may implement part of the above processing using logic circuits, and other processing units may implement the above processing by executing a program.
  • the above-described processing may be realized by another processing unit using both a logic circuit and a program execution.
  • the geometry encoding unit 501 When the point cloud encoding process is started, the geometry encoding unit 501 performs a geometry encoding process in step S501, encodes geometry data, and generates geometry encoded data.
  • the flow of this geometry encoding process is similar to the flow described with reference to the flowchart of FIG. 11 or FIG. 16.
  • step S502 the geometry decoding unit 502 performs geometry decoding processing, decodes the geometry encoded data generated in step S501, and generates (restores) geometry data.
  • the flow of this geometry decoding process is similar to the flow described with reference to the flowchart of FIG. 15 or FIG. 17.
  • step S503 the point cloud generation unit 503 performs recolor processing to make the attribute data correspond to the geometry data generated in step S502.
  • the point cloud encoding device 500 can suppress a reduction in the encoding efficiency of geometry encoded data.
  • FIG. 20 is a block diagram illustrating an example of the configuration of a point cloud decoding device that is one aspect of an information processing device to which the present technology is applied.
  • Point cloud decoding device 600 shown in FIG. 20 is a decoding device corresponding to point cloud encoding device 500, and decodes a point cloud bitstream to generate point cloud data.
  • the point cloud decoding device 600 performs ⁇ 2. Bit inversion of geometry>, the present technique described above is applied to decode the bit stream of the point cloud.
  • FIG. 20 shows the main things such as the processing unit and the flow of data, and not all of the things shown in FIG. 20 are shown. That is, in the point cloud decoding device 600, there may be a processing unit that is not shown as a block in FIG. 20, or there may be a process or a data flow that is not shown as an arrow or the like in FIG.
  • the point cloud decoding device 600 includes an extraction section 601, a geometry decoding section 602, an attribute decoding section 603, and a point cloud generation section 604.
  • the extraction unit 601 extracts geometry encoded data from the bitstream and supplies it to the geometry decoding unit 602. Further, the extraction unit 601 extracts attribute encoded data from the bitstream and supplies it to the attribute decoding unit 603.
  • the geometry decoding unit 602 performs processing related to decoding geometry encoded data. For example, the geometry decoding unit 602 acquires and decodes geometry encoded data supplied from the extraction unit 601 to generate (restore) geometry data. At this time, the geometry decoding unit 602 performs ⁇ 2. Geometry data is decoded by applying the above-described present technique in the section ⁇ Bit inversion of geometry''. That is, the geometry decoding unit 602 has the same configuration as the geometry decoding device 200 (FIG. 14) and performs the same processing. The geometry decoding unit 602 supplies the generated geometry data to the attribute decoding unit 603 and the point cloud generation unit 604.
  • the attribute decoding unit 603 performs processing related to decoding attribute encoded data. For example, the attribute decoding unit 603 acquires attribute encoded data supplied from the extraction unit 601. Further, the attribute decoding unit 603 acquires geometry data supplied from the geometry decoding unit 602. The attribute decoding unit 603 decodes the encoded attribute data using the geometry data to generate (restore) attribute data.
  • the attribute decoding unit 603 performs this decoding using a decoding method corresponding to the encoding method applied by the attribute encoding unit 504 (FIG. 18).
  • the attribute decoding unit 603 supplies the generated attribute data to the point cloud generation unit 604.
  • the point cloud generation unit 604 performs processing related to point cloud generation. For example, the point cloud generation unit 604 obtains geometry data supplied from the geometry decoding unit 602. Further, the point cloud generation unit 604 acquires attribute data supplied from the attribute decoding unit 603. Then, the point cloud generation unit 604 associates the geometry data with the attribute data to generate point cloud data. The point cloud generation unit 604 outputs the generated point cloud data to the outside of the point cloud decoding device 600.
  • the point cloud decoding device 600 can correctly decode the bitstream generated by the point cloud encoding device 500. That is, point cloud decoding device 600 can suppress a reduction in encoding efficiency.
  • each of these processing units extraction unit 601 to point cloud generation unit 604 of the point cloud decoding device 600 has an arbitrary configuration.
  • each processing section may be configured with a logic circuit that implements the above-described processing.
  • each processing unit may have, for example, a CPU, ROM, RAM, etc., and the above-described processing may be realized by using these to execute a program.
  • each processing unit may have both configurations, and may implement some of the above-mentioned processing by a logic circuit and the others by executing a program.
  • the configurations of each processing unit may be independent of each other; for example, some processing units may implement part of the above processing using logic circuits, and other processing units may implement the above processing by executing a program.
  • the above-described processing may be realized by another processing unit using both a logic circuit and a program execution.
  • This point cloud decoding device 600 decodes a bitstream by executing point cloud decoding processing. An example of the flow of this point cloud decoding process will be explained with reference to the flowchart of FIG. 21.
  • the extraction unit 601 extracts geometry encoded data and attribute encoded data from the bitstream in step S601.
  • step S602 the geometry decoding unit 602 performs geometry decoding processing, decodes the geometry encoded data, and generates (restores) geometry data.
  • the flow of this geometry decoding process is similar to the flow described with reference to the flowchart of FIG. 15 or FIG. 17.
  • step S603 the attribute decoding unit 603 decodes the encoded attribute data to generate (restore) attribute data.
  • step S604 the point cloud generation unit 604 generates point cloud data by associating the geometry data generated in step S602 with the attribute data generated in step S603.
  • step S604 ends, the point cloud decoding process ends.
  • Japanese Patent Application Laid-Open No. 2021-071814 discloses a method of representing point cloud data representing a three-dimensional space as a three-dimensional occupancy grid map (for example, number [0003 ] or paragraph [0073]).
  • a three-dimensional space 700 is divided into predetermined grids, and an occupancy state (discrete occupancy state) is given to each grid. That is, for each grid, it is identified whether it is observed ( known / unknown) and whether it is occupied ( Occupied / Free).
  • the observed grids (known) are classified into Occupied 701, which is a grid occupied by an object, and Free 702, which is a grid in which no object exists. That is, each grid is identified as shown in FIG. 22B.
  • the robot 731 identifies the portions of the wall 721 and wall 722 shown in bold lines within the measurable range 734 as the Occupied 741, and identifies the area shown in gray in the space 723 as the free 742. . Other parts are identified as unknown. By self-propelling, the robot 731 recognizes the wall 721 and the wall 722 as an occupied space 741 and the space 723 as a free space 742, as shown in FIG.
  • the known grid may be a point cloud 770, and attributes may be used to identify occupied 771 and free 772.
  • a point cloud 780 with the Occupied 781 as a point and a point cloud 790 with the Free 791 as a point may be created.
  • a point cloud with Known as a point and a point cloud with Occupied as a point may be generated.
  • a point cloud with free points as points and a point cloud with Unknown points may be generated. Other combinations may also be used.
  • FIG. 28 is a block diagram showing a main configuration example of a 3D Occupancy Grid map encoding device that converts a 3D Occupancy Grid map into a point cloud and encodes it.
  • the 3D Occupancy Grid map encoding device 800 includes a 3D Occupancy Grid map generation section 801, a conversion section 802, and a point cloud encoding section 803.
  • the 3D Occupancy Grid map generation unit 801 generates a 3D Occupancy Grid map and supplies it to the conversion unit 802.
  • the conversion unit 802 converts the 3D Occupancy Grid map into a point cloud and supplies it to the point cloud encoding unit 803.
  • the point cloud encoding unit 803 encodes the point cloud and generates a bitstream. At this time, the point cloud encoding unit 803 performs ⁇ 2. Bit reversal of geometry>, the present technique described above is applied to encode the point cloud. That is, point cloud encoding section 803 has the same configuration as point cloud encoding device 500 (FIG. 18) and performs similar processing. Point cloud encoding section 803 outputs the generated bitstream to the outside of 3D Occupancy Grid map encoding device 800 .
  • the 3D Occupancy Grid map encoding device 800 can suppress reduction in encoding efficiency of geometry encoded data for the point cloud obtained by converting the 3D Occupancy Grid map.
  • each of these processing units (3D Occupancy Grid map generation unit 801 to point cloud encoding unit 803) of the 3D Occupancy Grid map encoding device 800 has an arbitrary configuration.
  • each processing section may be configured with a logic circuit that implements the above-described processing.
  • each processing unit may have, for example, a CPU, ROM, RAM, etc., and the above-described processing may be realized by using these to execute a program.
  • each processing unit may have both configurations, and may implement some of the above-mentioned processing by a logic circuit and the others by executing a program.
  • each processing unit may be independent of each other; for example, some processing units may implement part of the above processing using logic circuits, and other processing units may implement the above processing by executing a program.
  • the above-described processing may be realized by another processing unit using both a logic circuit and a program execution.
  • the 3D Occupancy Grid map encoding device 800 converts the 3D Occupancy Grid map into a point cloud and encodes it by executing a 3D Occupancy Grid map encoding process.
  • An example of the flow of this 3D Occupancy Grid map encoding process will be explained with reference to the flowchart of FIG. 29.
  • the 3D Occupancy Grid map generation unit 801 When the 3D Occupancy Grid map encoding process is started, the 3D Occupancy Grid map generation unit 801 generates a 3D Occupancy Grid map in step S801. In step S802, the conversion unit 802 converts the 3D Occupancy Grid map into a point cloud. In step S803, the point cloud encoding unit 803 executes point cloud encoding processing, encodes the point cloud data, and generates a bitstream. The flow of this point cloud encoding process is similar to the flow described with reference to the flowchart of FIG. 19. Once the bitstream is generated, the 3D Occupancy Grid map encoding process ends.
  • the 3D Occupancy Grid map encoding device 800 can suppress a reduction in the encoding efficiency of geometry encoded data for the point cloud obtained by converting the 3D Occupancy Grid map.
  • Figure 30 shows the main components of a 3D Occupancy Grid map decoding device that generates (restores) a 3D Occupancy Grid map by decoding and inversely converting a bitstream of a 3D Occupancy Grid map that has been converted into a point cloud and encoded.
  • FIG. 2 is a block diagram showing a configuration example.
  • the 3D Occupancy Grid map decoding device 850 includes a point cloud decoding section 851 and an inverse transformation section 852.
  • the point cloud decoding unit 851 decodes the supplied bitstream and generates (restores) point cloud data into which the 3D Occupancy Grid map has been converted. Point cloud decoding section 851 supplies the point cloud data to inverse transformation section 852.
  • the inverse transformation unit 852 obtains the point cloud data.
  • the inverse conversion unit 852 converts the acquired point cloud data into a 3D Occupancy Grid map. This conversion process is also called inverse conversion.
  • the inverse transform unit 852 outputs the 3D Occupancy Grid map obtained by the inverse transform to the outside of the 3D Occupancy Grid map decoding device 850 .
  • each processing unit may be independent of each other; for example, some processing units may implement part of the above processing using logic circuits, and other processing units may implement the above processing by executing a program.
  • the above-described processing may be realized by another processing unit using both a logic circuit and a program execution.
  • the 3D Occupancy Grid map decoding device 850 decodes the bitstream by executing 3D Occupancy Grid map decoding processing. An example of the flow of this 3D Occupancy Grid map decoding process will be explained with reference to the flowchart of FIG. 31.
  • the point cloud decoding unit 851 decodes the bitstream by executing the point cloud decoding process in step S851, and converts the 3D Occupancy Grid map into converted point cloud data. Generate (restore). The flow of this point cloud decoding process is similar to the flow described with reference to the flowchart of FIG. 21.
  • step S852 the inverse transformation unit 852 transforms the point cloud data into a 3D Occupancy Grid map.
  • the 3D Occupancy Grid map decoding process ends.
  • the 3D Occupancy Grid map decoding device 850 can correctly decode the bitstream generated by the 3D Occupancy Grid map encoding device 800. That is, the D Occupancy Grid map decoding device 850 can suppress reduction in the coding efficiency of geometry encoded data for the point cloud obtained by converting the 3D Occupancy Grid map.
  • the series of processes described above can be executed by hardware or software.
  • the programs that make up the software are installed on the computer.
  • the computer includes a computer built into dedicated hardware and, for example, a general-purpose personal computer that can execute various functions by installing various programs.
  • FIG. 32 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processes using a program.
  • An input/output interface 910 is also connected to the bus 904.
  • An input section 911 , an output section 912 , a storage section 913 , a communication section 914 , and a drive 915 are connected to the input/output interface 910 .
  • the CPU 901 executes the above-described series by, for example, loading a program stored in the storage unit 913 into the RAM 903 via the input/output interface 910 and the bus 904 and executing it. processing is performed.
  • the RAM 903 also appropriately stores data necessary for the CPU 901 to execute various processes.
  • a program executed by a computer can be applied by being recorded on a removable medium 921 such as a package medium, for example.
  • the program can be installed in the storage unit 913 via the input/output interface 910 by attaching the removable medium 921 to the drive 915.
  • the program may also be provided via wired or wireless transmission media, such as a local area network, the Internet, or digital satellite broadcasting.
  • the program can be received by the communication unit 914 and installed in the storage unit 913.
  • this program can also be installed in the ROM 902 or storage unit 913 in advance.
  • the present technology can be applied to any configuration.
  • the present technology can be applied to various electronic devices.
  • the present technology can be applied to a processor (e.g., video processor) as a system LSI (Large Scale Integration), a module (e.g., video module) that uses multiple processors, etc., a unit (e.g., video unit) that uses multiple modules, etc.
  • a processor e.g., video processor
  • the present invention can be implemented as a part of a device, such as a set (for example, a video set), which is a unit with additional functions.
  • the present technology can also be applied to a network system configured by a plurality of devices.
  • the present technology may be implemented as cloud computing in which multiple devices share and jointly perform processing via a network.
  • this technology will be implemented in a cloud service that provides services related to images (moving images) to any terminal such as a computer, AV (Audio Visual) equipment, mobile information processing terminal, IoT (Internet of Things) device, etc. You may also do so.
  • a system refers to a collection of multiple components (devices, modules (components), etc.), and it does not matter whether all the components are in the same housing or not. Therefore, multiple devices housed in separate casings and connected via a network, and one device with multiple modules housed in one casing are both systems. .
  • the term “flag” refers to information for identifying multiple states, and includes not only information used to identify two states, true (1) or false (0), but also information for identifying three or more states. Information that can identify the state is also included. Therefore, the value that this "flag” can take may be, for example, a binary value of 1/0, or a value of three or more. That is, the number of bits constituting this "flag" is arbitrary, and may be 1 bit or multiple bits.
  • embodiments of the present technology are not limited to the embodiments described above, and various changes can be made without departing from the gist of the present technology.
  • the above-mentioned program may be executed on any device.
  • the device has the necessary functions (functional blocks, etc.) and can obtain the necessary information.
  • each step of one flowchart may be executed by one device, or may be executed by multiple devices.
  • the multiple processes may be executed by one device, or may be shared and executed by multiple devices.
  • multiple processes included in one step can be executed as multiple steps.
  • processes described as multiple steps can also be executed together as one step.
  • the processing of the steps described in the program may be executed chronologically in the order described in this specification, or may be executed in parallel, or may be executed in parallel. It may also be configured to be executed individually at necessary timings, such as when a request is made. In other words, the processing of each step may be executed in a different order from the order described above, unless a contradiction occurs. Furthermore, the processing of the step of writing this program may be executed in parallel with the processing of other programs, or may be executed in combination with the processing of other programs.
  • the inversion range is a node range that is made up of an inversion root node and descendant nodes of the inversion root node, and is the target of the inversion process
  • the inversion process is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.
  • a decoding unit that decodes the encoded data of the geometry data of the point cloud; and in a tree structure representing the geometry of the point cloud, which the geometry data obtained by decoding has, performs inversion processing on the inversion range. Equipped with an inversion processing section that performs The inversion range is a node range that is made up of an inversion root node and descendant nodes of the inversion root node, and is the target of the inversion process,
  • the inversion process is a process in which bit patterns of leaf nodes included in the inversion range are inverted, and bit patterns of non-leaf nodes included in the inversion range are made to correspond to bit patterns of child nodes.
  • the information processing device further comprising an inversion control unit that controls whether to perform the inversion process.
  • the inversion control unit performs the inversion process based on a bit inversion flag that is set for all nodes of the tree structure and indicates whether to perform the inversion process on the inversion range.
  • the information processing device according to (15).
  • the reversal control unit performs the reversal process based on a bit reversal flag, which is set for a group of direct nodes of the tree structure and indicates whether the reversal process is performed on the reversal range.
  • the information processing device according to (15).
  • the inversion range is a node range that is made up of an inversion root node and descendant nodes of the inversion root node, and is the target of the inversion process
  • the inversion process is a process of inverting the bit patterns of leaf nodes included in the inversion range and making the bit patterns of non-leaf nodes included in the inversion range correspond to the bit patterns of child nodes.

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