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EP-4133733-B1 - HIGH-LEVEL SYNTAX DESIGN FOR GEOMETRY-BASED POINT CLOUD COMPRESSION

EP4133733B1EP 4133733 B1EP4133733 B1EP 4133733B1EP-4133733-B1

Inventors

  • RAMASUBRAMONIAN, Adarsh Krishnan
  • RAY, BAPPADITYA
  • VAN DER AUWERA, GEERT
  • KEROFSKY, LOUIS JOSEPH
  • KARCZEWICZ, MARTA

Dates

Publication Date
20260513
Application Date
20210407

Claims (11)

  1. A method of decoding point cloud data, the method comprising: determining (800) a first slice identifier of a first geometry slice associated with a frame of the point cloud data; determining (802) a second slice identifier of a second geometry slice associated with the frame of the point cloud data; based on the second slice identifier being equal to the first slice identifier, determining (804) the second slice to contain identical content to the first slice; and decoding (806) the point cloud data based on the first slice identifier.
  2. The method of claim 1, further comprising: determining a slice dimension; parsing a trisoup node size syntax element indicative of a size of a node coded with trisoup coding mode; and decoding the point cloud data based on the size of the node, wherein a value of the trisoup node size syntax element is constrained to not exceed the slice dimension.
  3. The method of claim 1, further comprising: parsing an attribute slice header syntax element indicative of a number of regions where a delta quantization parameter will be applied; and decoding the point cloud data based on the number of regions, wherein a value of the attribute slice header syntax element is constrained within a range of 0 to N, where N is a predetermined value.
  4. The method of claim 1, further comprising: parsing a geometry slice header syntax element indicative of a geometry parameter set identifier, wherein a value of the geometry slice header syntax element is restricted to be in a range of 0 to 15 inclusive, and wherein the decoding the point cloud data is further based on a geometry parameter set identified by the geometry parameter set identifier.
  5. The method of claim 1, further comprising: parsing an attribute slice header syntax element indicative of an attribute parameter set identifier, wherein a value of the attribute slice header syntax element is restricted to be in a range of 0 to 15 inclusive, and wherein the decoding the point cloud data is further based on an attribute parameter set identified by the attribute parameter set identifier.
  6. A device for decoding point cloud data, the device comprising: memory configured to store the point cloud data; and one or more processors implemented in circuitry and coupled to the memory, the one or more processors being configured to: determine (800) a first slice identifier of a first geometry slice associated with a frame of the point cloud data; determine (802) a second slice identifier of a second geometry slice associated with the frame of the point cloud data; based on the second slice identifier being equal to the first slice identifier, determine (804) the second slice to contain identical content to the first slice; and decode (806) the point cloud data based on the first slice identifier.
  7. The device of claim 6, wherein the one or more processors are further configured to: determine a slice dimension; parse a trisoup node size syntax element indicative of a size of a node coded with trisoup coding mode; and decode the point cloud data based on the size of the node, wherein a value of the trisoup node size syntax element is constrained to not exceed the slice dimension.
  8. The device of claim 6, wherein the one or more processors are further configured to: parse an attribute slice header syntax element indicative of a number of regions where a delta quantization parameter will be applied; and decode the point cloud data based on the number of regions, wherein a value of the attribute slice header syntax element is constrained within a range of 0 to N, where N is a predetermined value.
  9. The device of claim 6, wherein the one or more processors are further configured to: parse a geometry slice header syntax element indicative of a geometry parameter set identifier, wherein a value of the geometry slice header syntax element is restricted to be in a range of 0 to 15 inclusive, and wherein the one or more processors decode the point cloud data further based on a geometry parameter set identified by the geometry parameter set identifier.
  10. The device of claim 6, wherein the one or more processors are further configured to: parse an attribute slice header syntax element indicative of an attribute parameter set identifier, wherein a value of the attribute slice header syntax element is restricted to be in a range of 0 to 15 inclusive, and wherein the one or more processors decode the point cloud data further based on an attribute parameter set identified by the attribute parameter set identifier.
  11. A computer-readable medium having stored therein on instructions that, when executed by a hardware-based processing unit, cause the hardware-based processing unit to perform a method according to any of claims 1 to 5.

Description

TECHNICAL FIELD This disclosure relates to point cloud encoding and decoding. BACKGROUND The document titled "G-PCC Future Enhancements" (128th MPEG meeting, Geneva, MPEG document no. n18887 dated 23 December 2019) is a draft document in the development of G-PCC. Section 7.3.3.2 of the document presents geometry slice header syntax, including a syntax element named 'gsh_slice_id'. Section 7.4.4.2 of the document describes attribute slice header semantics, including a syntax element named 'ash_attr_geom_slice_id', which specifies the value of the gsh_slice_id of the active geometry slice header. SUMMARY The invention is defined by the independent claims. Features of some embodiments are recited in dependent claims. BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a block diagram illustrating an example encoding and decoding system that may perform the techniques of this disclosure.FIG. 2 is a block diagram illustrating an example Geometry Point Cloud Compression (G-PCC) encoder.FIG. 3 is a block diagram illustrating an example G-PCC decoder.FIG. 4 is a conceptual diagram illustrating an example Level of Details (LoD) generation process.FIG. 5 is a conceptual diagram illustrating example possible point prediction using LoD.FIG. 6 is a conceptual diagram illustrating an example of G-PCC decoding with different LoD.FIG. 7 is a flow diagram of example region box and slice bounding box techniques.FIG. 8 is a flow diagram of an example slice identifier techniques according to the invention.FIG. 9 is a flow diagram illustrating an example of delta quantization parameter techniques. DETAILED DESCRIPTION In certain draft standards for geometry-based point cloud compression (G-PCC), issues may exist with high-level syntax. In an example, there is no restriction on a slice ID that may be assigned to a geometry slice. For example, two different geometry slices in a point cloud frame may be assigned the same slice ID, even if they contain different content. This may be undesirable as this condition may lead to ambiguities that may cause decoding errors. Such issues and other issues in high-level syntax design with G-PCC coding may be addressed as discussed in more detail below. By addressing these issues, decoding errors may be reduced. FIG. 1 is a block diagram illustrating an example encoding and decoding system 100 that may perform the techniques of this disclosure. The techniques of this disclosure are generally directed to coding (encoding and/or decoding) point cloud data. In general, point cloud data includes any data for processing a point cloud. The coding may be effective in compressing and/or decompressing point cloud data. As shown in FIG. 1, system 100 includes a source device 102 and a destination device 116. Source device 102 provides encoded point cloud data to be decoded by a destination device 116. Particularly, in the example of FIG. 1, source device 102 provides the point cloud data to destination device 116 via a computer-readable medium 110. Source device 102 and destination device 116 may comprise any of a wide range of devices, including desktop computers, notebook (i.e., laptop) computers, tablet computers, set-top boxes, telephone handsets such as smartphones, televisions, cameras, display devices, digital media players, video gaming consoles, video streaming devices, terrestrial or marine vehicles, spacecraft, aircraft, robots, LIDAR devices, satellites, or the like. In some cases, source device 102 and destination device 116 may be equipped for wireless communication. In the example of FIG. 1, source device 102 includes a data source 104, a memory 106, a G-PCC encoder 200, and an output interface 108. Destination device 116 includes an input interface 122, a G-PCC decoder 300, a memory 120, and a data consumer 118. In accordance with this disclosure, G-PCC encoder 200 of source device 102 and G-PCC decoder 300 of destination device 116 may be configured to apply the techniques of this disclosure related to high level syntax for geometry-based point cloud compression. Thus, source device 102 represents an example of an encoding device, while destination device 116 represents an example of a decoding device. In other examples, source device 102 and destination device 116 may include other components or arrangements. For example, source device 102 may receive data (e.g., point cloud data) from an internal or external source. Likewise, destination device 116 may interface with an external data consumer, rather than include a data consumer in the same device. System 100 as shown in FIG. 1 is merely one example. In general, other digital encoding and/or decoding devices may perform of the techniques of this disclosure related to high level syntax for geometry point cloud compression. Source device 102 and destination device 116 are merely examples of such devices in which source device 102 generates coded data for transmission to destination device 116. This disclosure refers to a "coding" device as a device