Qualcomm Patent | High-level syntax design for geometry-based point cloud compression

小编映维 | 分类：Qualcomm | 2021年10月15日

Patent: High-level syntax design for geometry-based point cloud compression

Publication Number: 20210321139

Publication Date: 20211014

Applicant: Qualcomm

Abstract

An example device for decoding point cloud data includes 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 are configured to determine dimensions of a region box and determine dimensions of a slice bounding box. The one or more processors are also configured to decode a slice of the point cloud data associated with the slice bounding box. The dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.

Claims

A method of decoding point cloud data, the method comprising: determining dimensions of a region box; determining dimensions of a slice bounding box; and decoding a slice of the point cloud data associated with the slice bounding box, wherein the dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.
The method of claim 1, wherein the dimensions of the region box are constrained such that no point in the region box is outside the slice bounding box.
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.
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.
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.
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.
A method of decoding point cloud data, the method comprising: determining a first slice identifier (ID) of a first geometry slice associated with a frame of the point cloud data; determining a second slice ID of a second geometry slice associated with the frame of the point cloud data; based on the second slice ID being equal to the first slice ID, determining the second slice to contain identical content to the first slice; and decoding the point cloud data based on the first slice ID.
The method of claim 7, 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.
The method of claim 7, 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.
The method of claim 7, 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.
The method of claim 7, 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.
A method of decoding point cloud data, the method comprising: determining whether an attribute dimension of an attribute is greater than 1; based on the attribute dimension being greater than 1, parsing an attribute slice header syntax element indicative of a delta quantization parameter; and decoding the point cloud data based on the delta quantization parameter.
The method of claim 12, wherein determining whether the attribute dimension is greater than 1 comprises parsing a syntax element in a sequence parameter set.
The method of claim 12, 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.
The method of claim 12, further comprising: parsing an attribute slice header syntax element indicative of a number of regions where the 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.
The method of claim 12, 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.
The method of claim 12, 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.
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 dimensions of a region box; determine dimensions of a slice bounding box; and decode a slice of the point cloud data associated with the slice bounding box, wherein the dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.
The device of claim 18, wherein the dimensions of the region box are constrained such that no point in the region box is outside the slice bounding box.
The device of claim 18, 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.
The device of claim 18, 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.
The device of claim 18, 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.
The device of claim 18, 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.
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 a first slice identifier (ID) of a first geometry slice associated with a frame of the point cloud data; determine a second slice ID of a second geometry slice associated with the frame of the point cloud data; based on the second slice ID being equal to the first slice ID, determine the second slice to contain identical content to the first slice; and decode the point cloud data based on the first slice ID.
The device of claim 24, 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.
The device of claim 24, 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.
The device of claim 24, 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.
The device of claim 24, 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.
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 whether an attribute dimension of an attribute is greater than 1; based on the attribute dimension being greater than 1, parse an attribute slice header syntax element indicative of a delta quantization parameter; and decode the point cloud data based on the delta quantization parameter.
The device of claim 29, wherein as part of determining whether the attribute dimension is greater than 1, the one or more processors are configured to parse a syntax element in a sequence parameter set.
The device of claim 29, 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.
The device of claim 29, 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.
The device of claim 29, 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.
The device of claim 29, 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.

Description

[0001] This application claims priority to U.S. Provisional Patent Application No. 63/006,660, filed on Apr. 7, 2020, U.S. Provisional Patent Application No. 63/010,550, filed on Apr. 15, 2020, and U.S. Provisional Patent Application No. 63/013,971, filed on Apr. 22, 2020, the entire contents of each of which is incorporated by reference.

TECHNICAL FIELD

[0002] This disclosure relates to point cloud encoding and decoding.

SUMMARY

[0003] In general, this disclosure describes several techniques for high-level syntax design for geometry-based point cloud compression (G-PCC). These techniques may address a number of potential issues in G-PCC coding.

[0004] In one example, this disclosure describes a method of decoding point cloud data including determining dimensions of a region box, determining dimensions of a slice bounding box, and decoding a slice of the point cloud data associated with the slice bounding box, wherein the dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.

[0005] In another example, this disclosure describes a method of decoding point cloud data determining a first slice identifier (ID) of a first geometry slice associated with a frame of the point cloud data, determining a second slice ID of a second geometry slice associated with the frame of the point cloud data, based on the second slice ID being equal to the first slice ID, determining the second slice to contain identical content to the first slice, and decoding the point cloud data based on the first slice ID.

[0006] In another example, this disclosure describes a method of decoding point cloud data determining whether an attribute dimension of an attribute is greater than 1, based on the attribute dimension being greater than 1, parsing an attribute slice header syntax element indicative of a delta quantization parameter, and decoding the point cloud data based on the delta quantization parameter.

[0007] In another example, this disclosure describes a device comprising memory configured to store point cloud data and one or more processors implemented in circuitry and communicatively coupled to the memory, the one or more processors being configured to determine dimensions of a region box, determine dimensions of a slice bounding box, and decode a slice of the point cloud data associated with the slice bounding box, wherein the dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.

[0008] In another example, this disclosure describes a device comprising memory configured to store point cloud data and one or more processors implemented in circuitry and communicatively coupled to the memory, the one or more processors being configured to determine a first slice identifier (ID) of a first geometry slice associated with a frame of the point cloud data, determine a second slice ID of a second geometry slice associated with the frame of the point cloud data, based on the second slice ID being equal to the first slice ID, determine the second slice to contain identical content to the first slice, and decode the point cloud data based on the first slice ID.

[0009] In another example, this disclosure describes a device comprising memory configured to store point cloud data and one or more processors implemented in circuitry and communicatively coupled to the memory, the one or more processors being configured to determine whether an attribute dimension of an attribute is greater than 1, based on the attribute dimension being greater than 1, parse an attribute slice header syntax element indicative of a delta quantization parameter, and decode the point cloud data based on the delta quantization parameter.

[0010] The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description, drawings, and claims.

BRIEF DESCRIPTION OF DRAWINGS

[0011] FIG. 1 is a block diagram illustrating an example encoding and decoding system that may perform the techniques of this disclosure.

[0012] FIG. 2 is a block diagram illustrating an example Geometry Point Cloud Compression (G-PCC) encoder.

[0013] FIG. 3 is a block diagram illustrating an example G-PCC decoder.

[0014] FIG. 4 is a conceptual diagram illustrating an example Level of Details (LoD) generation process.

[0015] FIG. 5 is a conceptual diagram illustrating example possible point prediction using LoD.

[0016] FIG. 6 is a conceptual diagram illustrating an example of G-PCC decoding with different LoD.

[0017] FIG. 7 is a flow diagram of example region box and slice bounding box techniques according to this disclosure.

[0018] FIG. 8 is a flow diagram of an example slice identifier techniques according to this disclosure.

[0019] FIG. 9 is a flow diagram illustrating an example of delta quantization parameter techniques according to this disclosure.

DETAILED DESCRIPTION

[0020] In certain draft standards for geometry-based point cloud compression (G-PCC), issues may exist with high-level syntax. For example, dimensions of a region box may exceed the dimensions of a slice that contains the region. In such a case, signaling the region width, height, and depth that may exceed the dimensions of the slice may not add value because there are no points in the slice that exceed the slice bounding box. This may unnecessarily increase signaling overhead and waste processing power on both a G-PCC encoder and G-PCC decoder.

[0021] In another example, there may be no restriction on the range of a syntax element indicative of the size of a trisoup node. When this syntax element exceeds the dimensions of a slice, this may lead to the generation of negative values of a variable indicative of the maximum geometry octree depth, which may be undesirable as this condition may lead to decoding errors.

[0022] In another 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.

[0023] In another example, some parameters are not applicable to a one-dimensional attribute. However, the parameters may still be present and may still need to be signaled. This may lead to an unnecessary increase in signaling overhead and waste processing power on both a G-PCC encoder and G-PCC decoder.

[0024] In another example, each slice may only be able to specify one region where a delta quantization parameter may be applied. It may be more desirable to enable the flexibility of having a plurality of regions where the delta quantization parameter may be applied. Only having the ability to specify one single region where a delta quantization parameter may be applied may constrain the choice of coding the point cloud in an efficient manner and/or in a manner that is takes into consideration a perceptual quality of the point cloud.

[0025] In another example, there may be no restriction on the value range of a geometry parameter set ID in a geometry slice header, while there may be a restriction on the value range of a geometry parameter set ID in a geometry parameter set. This condition may lead to an unnecessary increase in signaling overhead and waste processing power on both a G-PCC encoder and G-PCC decoder in the case where the value of the geometry parameter set ID in the geometry slice header is larger than that of the geometry parameter set ID in the geometry parameter set. This condition may also lead to ambiguities that may cause decoding errors.

[0026] In yet another example, there may be no restriction on the value range of a attribute parameter set ID in an attribute slice header, while there may be a restriction on the value range of an attribute parameter set ID in an attribute parameter set. This condition may lead to an unnecessary increase in signaling overhead and waste processing power on both a G-PCC encoder and G-PCC decoder in the case where the value of the attribute parameter set ID in the attribute slice header is larger than that of the attribute parameter set ID in the attribute parameter set. This condition may also lead to ambiguities that may cause decoding errors.

[0027] According to the techniques of this disclosure, the above 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, signaling overhead may be reduced, processing power may be saved, decoding errors may be reduced, and/or better reproduction of the point cloud at a decoder may be achieved.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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 that performs coding (encoding and/or decoding) of data. Thus, G-PCC encoder 200 and G-PCC decoder 300 represent examples of coding devices, in particular, an encoder and a decoder, respectively. In some examples, source device 102 and destination device 116 may operate in a substantially symmetrical manner such that each of source device 102 and destination device 116 includes encoding and decoding components. Hence, system 100 may support one-way or two-way transmission between source device 102 and destination device 116, e.g., for streaming, playback, broadcasting, telephony, navigation, and other applications.

[0032] In general, data source 104 represents a source of data (i.e., raw, unencoded point cloud data) and may provide a sequential series of “frames”) of the data to G-PCC encoder 200, which encodes data for the frames. Data source 104 of source device 102 may include a point cloud capture device, such as any of a variety of cameras or sensors, e.g., a 3D scanner or a light detection and ranging (LIDAR) device, one or more video cameras, an archive containing previously captured data, and/or a data feed interface to receive data from a data content provider. Alternatively or additionally, point cloud data may be computer-generated from scanner, camera, sensor or other data. For example, data source 104 may generate computer graphics-based data as the source data, or produce a combination of live data, archived data, and computer-generated data. In each case, G-PCC encoder 200 encodes the captured, pre-captured, or computer-generated data. G-PCC encoder 200 may rearrange the frames from the received order (sometimes referred to as “display order”) into a coding order for coding. G-PCC encoder 200 may generate one or more bitstreams including encoded data. Source device 102 may then output the encoded data via output interface 108 onto computer-readable medium 110 for reception and/or retrieval by, e.g., input interface 122 of destination device 116.

[0033] Memory 106 of source device 102 and memory 120 of destination device 116 may represent general purpose memories. In some examples, memory 106 and memory 120 may store raw data, e.g., raw data from data source 104 and raw, decoded data from G-PCC decoder 300. Additionally or alternatively, memory 106 and memory 120 may store software instructions executable by, e.g., G-PCC encoder 200 and G-PCC decoder 300, respectively. Although memory 106 and memory 120 are shown separately from G-PCC encoder 200 and G-PCC decoder 300 in this example, it should be understood that G-PCC encoder 200 and G-PCC decoder 300 may also include internal memories for functionally similar or equivalent purposes. Furthermore, memory 106 and memory 120 may store encoded data, e.g., output from G-PCC encoder 200 and input to G-PCC decoder 300. In some examples, portions of memory 106 and memory 120 may be allocated as one or more buffers, e.g., to store raw, decoded, and/or encoded data. For instance, memory 106 and memory 120 may store data representing a point cloud.

[0034] Computer-readable medium 110 may represent any type of medium or device capable of transporting the encoded data from source device 102 to destination device 116. In one example, computer-readable medium 110 represents a communication medium to enable source device 102 to transmit encoded data directly to destination device 116 in real-time, e.g., via a radio frequency network or computer-based network. Output interface 108 may modulate a transmission signal including the encoded data, and input interface 122 may demodulate the received transmission signal, according to a communication standard, such as a wireless communication protocol. The communication medium may comprise any wireless or wired communication medium, such as a radio frequency (RF) spectrum or one or more physical transmission lines. The communication medium may form part of a packet-based network, such as a local area network, a wide-area network, or a global network such as the Internet. The communication medium may include routers, switches, base stations, or any other equipment that may be useful to facilitate communication from source device 102 to destination device 116.

[0035] In some examples, source device 102 may output encoded data from output interface 108 to storage device 112. Similarly, destination device 116 may access encoded data from storage device 112 via input interface 122. Storage device 112 may include any of a variety of distributed or locally accessed data storage media such as a hard drive, Blu-ray discs, DVDs, CD-ROMs, flash memory, volatile or non-volatile memory, or any other suitable digital storage media for storing encoded data.

[0036] In some examples, source device 102 may output encoded data to file server 114 or another intermediate storage device that may store the encoded data generated by source device 102. Destination device 116 may access stored data from file server 114 via streaming or download. File server 114 may be any type of server device capable of storing encoded data and transmitting that encoded data to the destination device 116. File server 114 may represent a web server (e.g., for a website), a File Transfer Protocol (FTP) server, a content delivery network device, or a network attached storage (NAS) device. Destination device 116 may access encoded data from file server 114 through any standard data connection, including an Internet connection. This may include a wireless channel (e.g., a Wi-Fi connection), a wired connection (e.g., digital subscriber line (DSL), cable modem, etc.), or a combination of both that is suitable for accessing encoded data stored on file server 114. File server 114 and input interface 122 may be configured to operate according to a streaming transmission protocol, a download transmission protocol, or a combination thereof.

[0037] Output interface 108 and input interface 122 may represent wireless transmitters/receivers, modems, wired networking components (e.g., Ethernet cards), wireless communication components that operate according to any of a variety of IEEE 802.11 standards, or other physical components. In examples where output interface 108 and input interface 122 comprise wireless components, output interface 108 and input interface 122 may be configured to transfer data, such as encoded data, according to a cellular communication standard, such as 4G, 4G-LTE (Long-Term Evolution), LTE Advanced, 5G, or the like. In some examples where output interface 108 comprises a wireless transmitter, output interface 108 and input interface 122 may be configured to transfer data, such as encoded data, according to other wireless standards, such as an IEEE 802.11 specification, an IEEE 802.15 specification (e.g., ZigBee.TM.), a Bluetooth.TM. standard, or the like. In some examples, source device 102 and/or destination device 116 may include respective system-on-a-chip (SoC) devices. For example, source device 102 may include an SoC device to perform the functionality attributed to G-PCC encoder 200 and/or output interface 108, and destination device 116 may include an SoC device to perform the functionality attributed to G-PCC decoder 300 and/or input interface 122.

[0038] The techniques of this disclosure may be applied to encoding and decoding in support of any of a variety of applications, such as communication between autonomous vehicles, communication between scanners, cameras, sensors and processing devices such as local or remote servers, geographic mapping, or other applications.

[0039] Input interface 122 of destination device 116 receives an encoded bitstream from computer-readable medium 110 (e.g., a communication medium, storage device 112, file server 114, or the like). The encoded bitstream may include signaling information defined by G-PCC encoder 200, which is also used by G-PCC decoder 300, such as syntax elements having values that describe characteristics and/or processing of coded units (e.g., slices, pictures, groups of pictures, sequences, or the like). Data consumer 118 uses the decoded data. For example, data consumer 118 may use the decoded data to determine the locations of physical objects. In some examples, data consumer 118 may comprise a display to present imagery based on a point cloud.

[0040] G-PCC encoder 200 and G-PCC decoder 300 each may be implemented as any of a variety of suitable encoder and/or decoder circuitry, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic, software, hardware, firmware or any combinations thereof. When the techniques are implemented partially in software, a device may store instructions for the software in a suitable, non-transitory computer-readable medium and execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Each of G-PCC encoder 200 and G-PCC decoder 300 may be included in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (CODEC) in a respective device. A device including G-PCC encoder 200 and/or G-PCC decoder 300 may comprise one or more integrated circuits, microprocessors, and/or other types of devices.

[0041] G-PCC encoder 200 and G-PCC decoder 300 may operate according to a coding standard, such as video point cloud compression (V-PCC) standard of a geometry point cloud compression (G-PCC) standard. This disclosure may generally refer to coding (e.g., encoding and decoding) of pictures to include the process of encoding or decoding data. An encoded bitstream generally includes a series of values for syntax elements representative of coding decisions (e.g., coding modes).

[0042] This disclosure may generally refer to “signaling” certain information, such as syntax elements. The term “signaling” may generally refer to the communication of values for syntax elements and/or other data used to decode encoded data. That is, G-PCC encoder 200 may signal values for syntax elements in the bitstream. In general, signaling refers to generating a value in the bitstream. As noted above, source device 102 may transport the bitstream to destination device 116 substantially in real time, or not in real time, such as might occur when storing syntax elements to storage device 112 for later retrieval by destination device 116.

[0043] ISO/IEC MPEG (JTC 1/SC 29/WG 11) is studying the potential need for standardization of point cloud coding technology with a compression capability that significantly exceeds that of the current approaches and will target to create the standard. The group is working together on this exploration activity in a collaborative effort known as the 3-Dimensional Graphics Team (3DG) to evaluate compression technology designs proposed by their experts in this area.

[0044] Point cloud compression activities are categorized in two different approaches. The first approach is “Video point cloud compression” (V-PCC), which segments the 3D object, and project the segments in multiple 2D planes (which are represented as “patches” in the 2D frame), which are further coded by a legacy 2D video codec such as a High Efficiency Video Coding (HEVC) (ITU-T H.265) codec. The second approach is “Geometry-based point cloud compression” (G-PCC), which directly compresses 3D geometry i.e., position of a set of points in 3D space, and associated attribute values (for each point associated with the 3D geometry). G-PCC addresses the compression of point clouds in both Category 1 (static point clouds) and Category 3 (dynamically acquired point clouds). A recent draft of the G-PCC standard is available in G-PCC DIS, ISO/IEC JTC1/SC29/WG11 w19088, Brussels, Belgium, January 2020, and a description of the codec is available in G-PCC Codec Description v6, ISO/IEC JTC1/SC29/WG11 w19091, Brussels, Belgium, January 2020.

[0045] A point cloud contains a set of points in a 3D space and may have attributes associated with the point. The attributes may be color information such as R, G, B or Y, Cb, Cr, or reflectance information, or other attributes. Point clouds may be captured by a variety of cameras or sensors such as LIDAR sensors and 3D scanners and may also be computer-generated. Point cloud data are used in a variety of applications including, but not limited to, construction (modeling), graphics (3D models for visualizing and animation), and the automotive industry (LIDAR sensors used to help in navigation).

[0046] The 3D space occupied by a point cloud data may be enclosed by a virtual bounding box. The position of the points in the bounding box may be represented by a certain precision; therefore, the positions of one or more points may be quantized based on the precision. At the smallest level, the bounding box is split into voxels which are the smallest unit of space represented by a unit cube. A voxel in the bounding box may be associated with zero, one, or more than one point. The bounding box may be split into multiple cube/cuboid regions, which may be called tiles. Each tile may be coded into one or more slices. The partitioning of the bounding box into slices and tiles may be based on number of points in each partition, or based on other considerations (e.g., a particular region may be coded as tiles). The slice regions may be further partitioned using splitting decisions similar to those in video codecs.

[0047] FIG. 2 provides an overview of G-PCC encoder 200. FIG. 3 provides an overview of G-PCC decoder 300. The modules shown are logical, and do not necessarily correspond one-to-one to implemented code in the reference implementation of G-PCC codec, i.e., TMC13 test model software studied by ISO/IEC MPEG (JTC 1/SC 29/WG 11).

[0048] In both G-PCC encoder 200 and G-PCC decoder 300, point cloud positions are coded first. Attribute coding depends on the decoded geometry. In FIG. 2 and FIG. 3, the gray-shaded modules are options typically used for Category 1 data. Diagonal-crosshatched modules are options typically used for Category 3 data. All the other modules are common between Categories 1 and 3.

[0049] For Category 3 data, the compressed geometry is typically represented as an octree from the root all the way down to a leaf level of individual voxels. For Category 1 data, the compressed geometry is typically represented by a pruned octree (i.e., an octree from the root down to a leaf level of blocks larger than voxels) plus a model that approximates the surface within each leaf of the pruned octree. In this way, both Category 1 and 3 data share the octree coding mechanism, while Category 1 data may in addition approximate the voxels within each leaf with a surface model. The surface model used is a triangulation comprising 1-10 triangles per block, resulting in a triangle soup. The Category 1 geometry codec is therefore known as the Trisoup geometry codec, while the Category 3 geometry codec is known as the Octree geometry codec.

[0050] At each node of an octree, an occupancy is signaled (when not inferred) for one or more of its child nodes (up to eight nodes). Multiple neighborhoods are specified including (a) nodes that share a face with a current octree node, (b) nodes that share a face, edge or a vertex with the current octree node, etc. Within each neighborhood, the occupancy of a node and/or its children may be used to predict the occupancy of the current node or its children. For points that are sparsely populated in certain nodes of the octree, the codec also supports a direct coding mode where the 3D position of the point is encoded directly. A flag may be signaled to indicate that a direct mode is signaled. At the lowest level, the number of points associated with the octree node/leaf node may also be coded.

[0051] Once the geometry is coded, the attributes corresponding to the geometry points are coded. When there are multiple attribute points corresponding to one reconstructed/decoded geometry point, an attribute value may be derived that is representative of the reconstructed point.

[0052] There are three attribute coding methods in G-PCC: Region Adaptive Hierarchical Transform (RAHT) coding, interpolation-based hierarchical nearest-neighbour prediction (Predicting Transform), and interpolation-based hierarchical nearest-neighbour prediction with an update/lifting step (Lifting Transform). RAHT and lifting are typically used for Category 1 data, while Predicting is typically used for Category 3 data. However, either method may be used for any data, and, just like with the geometry codecs in G-PCC, the attribute coding method used to code the point cloud is specified in the bitstream.

[0053] The coding of the attributes may be conducted in a level-of-detail (LOD), where with each level of detail a finer representation of the point cloud attribute may be obtained. Each level of detail may be specified based on distance metric from the neighboring nodes or based on a sampling distance.

[0054] At G-PCC encoder 200, the residual obtained as the output of the coding methods for the attributes are quantized. The quantized residual may be coded using context adaptive arithmetic coding.

[0055] In the example of FIG. 2, G-PCC encoder 200 may include a coordinate transform unit 202, a color transform unit 204, a voxelization unit 206, an attribute transfer unit 208, an octree analysis unit 210, a surface approximation analysis unit 212, an arithmetic encoding unit 214, a geometry reconstruction unit 216, an RAHT unit 218, a LOD generation unit 220, a lifting unit 222, a coefficient quantization unit 224, and an arithmetic encoding unit 226.

[0056] As shown in the example of FIG. 2, G-PCC encoder 200 may receive a set of positions and a set of attributes. The positions may include coordinates of points in a point cloud. The attributes may include information about points in the point cloud, such as colors associated with points in the point cloud.

[0057] Coordinate transform unit 202 may apply a transform to the coordinates of the points to transform the coordinates from an initial domain to a transform domain. This disclosure may refer to the transformed coordinates as transform coordinates. Color transform unit 204 may apply a transform to transform color information of the attributes to a different domain. For example, color transform unit 204 may transform color information from an RGB color space to a YCbCr color space.

[0058] Furthermore, in the example of FIG. 2, voxelization unit 206 may voxelize the transform coordinates. Voxelization of the transform coordinates may include quantization and removing some points of the point cloud. In other words, multiple points of the point cloud may be subsumed within a single “voxel,” which may thereafter be treated in some respects as one point. Furthermore, octree analysis unit 210 may generate an octree based on the voxelized transform coordinates. Additionally, in the example of FIG. 2, surface approximation analysis unit 212 may analyze the points to potentially determine a surface representation of sets of the points. Arithmetic encoding unit 214 may entropy encode syntax elements representing the information of the octree and/or surfaces determined by surface approximation analysis unit 212. G-PCC encoder 200 may output these syntax elements in a geometry bitstream.

[0059] Geometry reconstruction unit 216 may reconstruct transform coordinates of points in the point cloud based on the octree, data indicating the surfaces determined by surface approximation analysis unit 212, and/or other information. The number of transform coordinates reconstructed by geometry reconstruction unit 216 may be different from the original number of points of the point cloud because of voxelization and surface approximation. This disclosure may refer to the resulting points as reconstructed points. Attribute transfer unit 208 may transfer attributes of the original points of the point cloud to reconstructed points of the point cloud.

[0060] Furthermore, RAHT unit 218 may apply RAHT coding to the attributes of the reconstructed points. Alternatively or additionally, LOD generation unit 220 and lifting unit 222 may apply LOD processing and lifting, respectively, to the attributes of the reconstructed points. RAHT unit 218 and lifting unit 222 may generate coefficients based on the attributes. Coefficient quantization unit 224 may quantize the coefficients generated by RAHT unit 218 or lifting unit 222. Arithmetic encoding unit 226 may apply arithmetic coding to syntax elements representing the quantized coefficients. G-PCC encoder 200 may output these syntax elements in an attribute bitstream.

[0061] In the example of FIG. 3, G-PCC decoder 300 may include a geometry arithmetic decoding unit 302, an attribute arithmetic decoding unit 304, an octree synthesis unit 306, an inverse quantization unit 308, a surface approximation synthesis unit 310, a geometry reconstruction unit 312, a RAHT unit 314, a LoD generation unit 316, an inverse lifting unit 318, an inverse transform coordinate unit 320, and an inverse transform color unit 322.

[0062] G-PCC decoder 300 may obtain a geometry bitstream and an attribute bitstream. Geometry arithmetic decoding unit 302 of G-PCC decoder 300 may apply arithmetic decoding (e.g., Context-Adaptive Binary Arithmetic Coding (CABAC) or other type of arithmetic decoding) to syntax elements in the geometry bitstream. Similarly, attribute arithmetic decoding unit 304 may apply arithmetic decoding to syntax elements in the attribute bitstream.

[0063] Octree synthesis unit 306 may synthesize an octree based on syntax elements parsed from the geometry bitstream. In instances where surface approximation is used in the geometry bitstream, surface approximation synthesis unit 310 may determine a surface model based on syntax elements parsed from the geometry bitstream and based on the octree.

[0064] Furthermore, geometry reconstruction unit 312 may perform a reconstruction to determine coordinates of points in a point cloud. Inverse transform coordinate unit 320 may apply an inverse transform to the reconstructed coordinates to convert the reconstructed coordinates (positions) of the points in the point cloud from a transform domain back into an initial domain.

[0065] Additionally, in the example of FIG. 3, inverse quantization unit 308 may inverse quantize attribute values. The attribute values may be based on syntax elements obtained from the attribute bitstream (e.g., including syntax elements decoded by attribute arithmetic decoding unit 304).

[0066] Depending on how the attribute values are encoded, RAHT unit 314 may perform RAHT coding to determine, based on the inverse quantized attribute values, color values for points of the point cloud. Alternatively, LoD generation unit 316 and inverse lifting unit 318 may determine color values for points of the point cloud using a level of detail-based technique.

[0067] Furthermore, in the example of FIG. 3, inverse transform color unit 322 may apply an inverse color transform to the color values. The inverse color transform may be an inverse of a color transform applied by color transform unit 204 of G-PCC encoder 200. For example, color transform unit 204 may transform color information from an RGB color space to a YCbCr color space. Accordingly, inverse color transform unit 322 may transform color information from the YCbCr color space to the RGB color space.

[0068] The various units of FIG. 2 and FIG. 3 are illustrated to assist with understanding the operations performed by G-PCC encoder 200 and G-PCC decoder 300. The units may be implemented as fixed-function circuits, programmable circuits, or a combination thereof. Fixed-function circuits refer to circuits that provide particular functionality, and are preset on the operations that can be performed. Programmable circuits refer to circuits that can be programmed to perform various tasks, and provide flexible functionality in the operations that can be performed. For instance, programmable circuits may execute software or firmware that cause the programmable circuits to operate in the manner defined by instructions of the software or firmware. Fixed-function circuits may execute software instructions (e.g., to receive parameters or output parameters), but the types of operations that the fixed-function circuits perform are generally immutable. In some examples, one or more of the units may be distinct circuit blocks (fixed-function or programmable), and in some examples, one or more of the units may be integrated circuits.

[0069] Non-normative quantization and scaling in G-PCC is now described. An original point cloud may be represented in a floating-point format or at a very high bit depth. Voxelization unit 206 may quantize and voxelize the input point cloud at a certain bit depth. G-PCC encoder 200 may apply the quantization for the purpose of voxelization, and a scaling may be performed at the decoder side, e.g., by G-PCC decoder 300, mainly for the mapping of the decoded point cloud (e.g., in voxels unit) in an application specific physical space (e.g., in a physical dimension). G-PCC decoder 300 may use a scale value for this operation that is signaled by G-PCC encoder 200 using the syntax elements sps_source_scale_factor_numerator_minus1 and sps_source_scale_factor_denominator_minus1. The quantization process being a pre-processing step (prior to encoding) and the scaling process being a post-processing step (after decoding) does not impact the overall coding process. Rather, the quantization process and scaling process are non-normative in nature.

TABLE-US-00001 sps_source_scale_factor_numerator_minus1 ue(v) sps_source_scale_factor_denominator_minus1 ue(v)

[0070] For purposes of this disclosure, at the encoder side (e.g., G-PCC encoder 200), the point cloud before the non-normative quantization will be referred to as an “unquantized point cloud” and the point cloud after the non-normative quantization will be referred to as a “quantized point cloud.” This quantization is not related to the quantization that may be done by a G-PCC codec as part of the encoding or decoding process. Similarly, the output of the G-PCC decoder (e.g., G-PCC decoder 300) is referred to as a quantized point cloud; the output of any non-normative scaling at the decoder-side is referred to as an unquantized point cloud. It is again noted that the output of the G-PCC decoder (e.g., G-PCC decoder 300) may be the result of normative scaling operations.

[0071] Bounding boxes in G-PCC are now described. Similar to the notion of picture width and height in images and in video, point clouds also have a notion of a bounding box whereby all the points in a point cloud are considered to be present within the bounding box. In other words, a bounding box is defined such that it contains all the points in the point cloud.

[0072] A source bounding box is now described. At the time of capture or generation of a point cloud, a bounding box may be specified to capture all the points of a point cloud. For example, source device 102 may specify the bounding box. This bounding box may be referred to as the source bounding box. In G-PCC, a sequence parameter set (SPS) bounding box syntax element (e.g., seq_bounding_box_present_flag) is specified that may be indicative of the source bounding box. For the purpose of this disclosure, the SPS bounding box may be referred to as the source bounding box. The units used to describe the source bounding box are not defined in G-PCC. A given application may therefore determine these units. The syntax and semantics associated with the SPS bounding box are provided below.

[0073] It is presumed (because this behavior is not defined in the G-PCC standard) that the output of G-PCC decoder 300 will be scaled using a source scale factor (derived from sps_source_scale_factor_numerator_minus1 and sps_source_scale_factor_denominator_minus1) and the output of this (non-normative) scaling is contained within the SPS bounding box. For example, an application, a separate device, or a G-PCC decoder device itself may scale the output of G-PCC decoder 300. In some examples, G-PCC decoder 300 may parse the scale factor syntax elements. In other examples, the application or separate device may parse the scale factor syntax elements.

[0074] Source Bounding Box-Related Syntax

TABLE-US-00002 seq_parameter_set( ) { Descriptor main_profile_compatibility_flag u(1) reserved_profile_compatibility_2bits u(22) [Ed. assign bits from this when there is a profile defined] unique_point_positions_constraint_flag u(1) level_idc u(8) sps_seq_parameter_set_id ue(v) sps_bounding_box_present_flag u(1) if( sps_bounding_box_present_flag ) { sps_bounding_box_offset_x se(v) sps_bounding_box_offset_y se(v) sps_bounding_box_offset_z se(v) sps_bounding_box_offset_log2_scale ue(v) sps_bounding_box_size_width ue(v) sps_bounding_box_size_height ue(v) sps_bounding_box_size_depth ue(v) } sps_source_scale_factor_numerator_minus1 ue(v) sps_source_scale_factor_denominator_minus1 ue(v) sps_num_attribute_sets ue(v) for( i = 0; i< sps_num_attribute_sets; i++ ) {

[0075] Source bounding box-related semantics are as follows:

[0076] main_profile_compatibility_23bitsflag equal to 1 specifies that the bitstream conforms to the Main profile. main_profile_compatibility_flag equal to 0 specifies that the bitstream conforms to a profile other than the Main profile.

[0077] reserved_profile_compatibility_22 shall be equal to 0 in bitstreams conforming to this version of this Specification. Other values for reserved_profile_compatibility_22bits are reserved for future use by ISO/JEC. Decoders shall ignore the value of reserved_profile_compatibility_2bits.

[0078] unique_point_positions_constraint_flag equal to 1 indicates that in each point cloud frame that refers to the current SPS, all output points have unique positions. unique_point_positions_constraint_flag equal to 0 indicates that in any point cloud frame that refers to the current SPS, two and more output points may have the same position.

[0079] Note–For example, even if all points are unique in each slices [sic], the points from different slices in a frame may overlap. In that case, unique_point_positions_constraint_flag should be set to 0.

[0080] level_idc indicates a level to which the bitstream conforms as specified in Annex A. Bitstreams shall not contain values of level_idc other than those specified in Annex A. Other values of level_idc are reserved for future use by ISO/JEC.

[0081] sps_seq_parameter_set id provides an identifier for the SPS for reference by other syntax elements. The value of sps_seq_parameter_set_id shall be 0 in bitstreams conforming to this version of this Specification. The value other than 0 for sps_seq_parameter_set_id is reserved for future use by ISO/JEC.

[0082] sps_bounding_box_present_flag equal to 1 indicates that a bounding box. sps_bounding_box_present_flag equal to 0 indicates that the size of the bounding box is undefined.

[0083] sps_bounding_box_offset_x, sps_bounding_box_offset_y, and sps_bounding_box_offset_z indicate quantised x, y, and z offsets of the source bounding box in Cartesian coordinates. When not present, the values of sps_bounding_box_offset_x, sps_bounding box_offset_y, and sps_bounding_box_offset_z are each inferred to be 0.

[0084] sps_bounding_box_offset_log2_scale indicates the scaling factor to scale the quantised x, y, and z source bounding box offsets. When not present, the value of sps_bounding_box_offset_log2_scale is inferred to be 0.

[0085] sps_bounding_box_size_width, sps_bounding_box_size_height, and sps_bounding_box_size_depth indicate the width, height, and depth of the source bounding box in Cartesian coordinates.

[0086] sps_source_scale_factor_numerator_minus1 plus 1 indicates the scale factor numerator of the source point cloud.

[0087] sps_source_scale_factor_denominator_minus1 plus 1 indicates the scale factor denominator of the source point cloud.

[0088] Tile bounding boxes are now described. In addition to the source bounding box, G-PCC also specifies tile bounding boxes. Tile bounding boxes are associated with the points of a tile. The tile bounding boxes are signaled in the tile_inventory( ) syntax. Each tile_inventory( ) syntax structure is associated with a frame specified by tile_frame_idx.

[0089] Tile Inventory Syntax

TABLE-US-00003 tile_inventory( ) { Descriptor tile_frame_idx ? num_tiles_minus1 u(16) for( i = 0; i <= num_tiles_minus1; i++ ) { tile_bounding_box_offset_x[ i ] se(v) tile_bounding_box_offset_y[ i ] se(v) tile_bounding_box_offset_z[ i ] se(v) tile_bounding_box_size_width[ i ] ue(v) tile_bounding_box_size_height[ i ] ue(v) tile_bounding_box_size_depth[ i ] ue(v) } byte_alignment( ) }

[0090] Tile inventory semantics are as follows:

[0091] num_tiles_minus1 plus 1 specifies the number of tile bounding boxes present in the tile inventory.

[0092] tile_bounding_box_offset_x[i], tile_bounding_box_offset_y[i], and tile_bounding_box_offset_z[i] indicate the x, y, and z offsets of the i-th tile in cartesian coordinates.

[0093] tile_bounding_box_size_width[i], tile bounding_box_size_height[i], and tile_bounding_box_size_depth[i] indicate the width, height, and depth of the i-th tile in the Cartesian coordinates.

[0094] Slice bounding boxes are now described. Although a bounding box is not explicitly specified for slices, a box may be specified that includes the points in a slice. The specification of the slice bounding box includes a slice origin that specifies one corner of the slice bounding box and the width, height and depth of the slice bounding box.

[0095] The Geometry parameter set (GPS) includes an indication of whether an explicit slice origin is signaled for slices. If an explicit slice origin is present, G-PCC encoder 200 may signal an associated scale value at the GPS or at the Geometry slice header (GSH). When an explicit slice origin is not signaled, G-PCC decoder 300 infers the slice origin to be equal to (0, 0, 0). Slice bounding box syntax is shown below.

[0096] Slice (Bounding) Box-Related Syntax

TABLE-US-00004 geometry_parameter_set( ) { Descriptor gps_geom_parameter_set_id ue(v) gps_seq_parameter_set_id ue(v) gps_box_present_flag u(1) if( gps_box_present_flag ){ gps_gsh_box_log2_scale_present_flag u(1) if( gps_gsh_box_log2_scale_present_flag = = 0 ) gps_gsh_box_log2_scale ue(v) } unique_geometry_points_flag u(1)

TABLE-US-00005 geometry_slice_header( ) { Descriptor gsh_geometry_parameter_set_id ue(v) gsh_tile_id ue(v) gsh_slice_id ue(v) frame_idx u(n) gsh_num_points u(24) if( gps_box_present_flag ) { if( gps_gsh_box_log2_scale_present_flag ) gsh_box_log2_scale ue(v) gsh_box_origin_x ue(v) gsh_box_origin_y ue(v) gsh_box_origin_z ue(v) } if ( gps_implicit_geom_partition_flag ) { gsh_log2_max_nodesize_x ue(v) gsh_log2_max_nodesize_y_minus_x se(v) gsh_log2_max_nodesize_z_minus_y se(v) } else { gsh_log2_max_nodesize ue(v) } _minus1 if( geom_scaling_enabled_flag ) { [Ed: this should be last in the gsh?]

[0097] Slice (bounding) box-related semantics are now described. The following are the semantics of the relevant syntax elements in the Geometry parameter set:

[0098] gps_geom_parameter_set_id provides an identifier for the GPS for reference by other syntax elements. The value of gps_seq_parameter_set_id shall be in the range of 0 to 15, inclusive.

[0099] gps_seq_parameter_set_id specifies the value of sps_seq_parameter_set_id for the active SPS. The value of gps_seq_parameter_set_id shall be in the range of 0 to 15, inclusive.

[0100] gps_box_present_flag equal to 1 specifies an additional bounding box information is provided in a geometry header that references the current GPS.

[0101] gps_bounding_box_present_flag equal to 0 specifies that additional bounding box information is not signaled in the geometry header.

[0102] gps_gsh_box_log2_scale_present_flag equal to 1 specifies gsh_box_log2_scale is signaled in each geometry slice header that references the current GPS.

[0103] gps_gsh_box_log2_scale_present_flag equal to 0 specifies gsh_box_log2_scale is not signaled in each geometry slice header and common scale for all slices is signaled in gps_gsh_box_log2_scale of current GPS.

[0104] gps_gsh_box_log2_scale indicates the common scale factor of bounding box origin for all slices that references the current GPS.

[0105] The following are the semantics of the relevant syntax elements in the Geometry slice header:

[0106] gsh_geometry_parameter_set_id specifies the value of the gps_geom_parameter_set_id of the active GPS.

[0107] gsh_tile_id specifies the value of the tile id that is referred to by the GSH. The value of gsh_tile_id shall be in the range of 0 to XX, inclusive.

[0108] gsh_slice_id identifies the slice header for reference by other syntax elements. The value of gsh_slice_id shall be in the range of 0 to XX, inclusive.

[0109] frame_idx specifies the log2_max_frame_idx+1 least significant bits of a notional frame number counter. Consecutive slices with differing values of frame_idx form parts of different output point cloud frames. Consecutive slices with identical values of frame_idx without an intervening frame boundary marker data unit form parts of the same output point cloud frame.

[0110] gsh_num_points specifies the maximum number of coded points in the slice. It is a requirement of bitstream conformance that gsh_num_points is greater than or equal to the number of decoded points in the slice.

[0111] gsh_box_log2_scale specifies the scaling factor of bounding box origin for the slice.

[0112] gsh_box_origin_x specifies the x value of bounding box origin that scaled by gsh_box_log2_scale value.

[0113] gsh_box_origin_y specifies the y value of bounding box origin that scaled by gsh_box_log2_scale value

[0114] gsh_box_origin_z specifies the z value of bounding box origin that scaled by gsh_box_log2_scale value.

[0115] The variable slice_origin_x, slice_origin_y, and slice_origin_z are derived as follows:

TABLE-US-00006 If gps_gsh_box_log2_scale_present_flag is equal to 0, originScale is set equal to gsh_box_log2_scale Otherwise ( gps_gsh_box_log2_scale_present_flag is equal to 1), originScale is set equal to gps_gsh_box_log2_scale If gps_box_present flag is equal to 0, the value of slice_origin_x and slice_origin_y and slice_origin_z are inferred to be 0.

[0116] Otherwise (gps_box_present_flag is equal to 1), the following applies: [0117] slice_origin_x=gsh_box_origin_x<

[0120] gsh_log2_max_nodesize_x specifies the bounding box size in the x dimension, i.e., MaxNodesizeXLog2 that is used in the decoding process as follows. [0121] MaxNodeSizeXLog2=gsh_log2_max_nodesize_x [0122] MaxNodeSizeX=1<

[0123] gsh_log2_max_nodesize_y_minus_x specifies the bounding box size in the y dimension, i.e., MaxNodesizeYLog2 that is used in the decoding process as follows:

TABLE-US-00007 MaxNodeSizeYLog2 = gsh_log2_max_nodesize_y minus_x + MaxNodeSizeXLog2. MaxNodeSizeY = 1 << MaxNodeSizeYLog2.

[0124] gsh_log2_max_nodesize_z_minus_y specifies the bounding box size in the z dimension, i.e., MaxNodesizeZLog2 that is used in the decoding process as follows.

TABLE-US-00008 MaxNodeSizeZLog2 = gsh_log2_max_nodesize_z_minus_y + MaxNodeSizeYLog2 MaxNodeSizeZ =1 << MaxNodeSizeZLog2

[0125] If gps_implicit_geom_partition_flag equals to 1, gsh_log2_max_nodesize is derived as follows.

TABLE-US-00009 gsh_log2_max_nodesize = max{ MaxNodeSizeXLog2, MaxNodeSizeYLog2, MaxNodeSizeZLog2}

gsh_log2_max_nodesize specifies the size of the root geometry octree node when gps_implicit_geom_partition_flag is equal to 0. The variables MaxNodeSize, and MaxGeometryOctreeDepth are derived as follows.

TABLE-US-00010 MaxNodeSize = 1 << gsh_log2_max_nodesize MaxGeometryOctreeDepth = gsh_log2_max_nodesize - log2_trisoup_node_size

[0126] The variables K and M are then updated as follows.

TABLE-US-00011 gsh_log2_min_nodesize = min{MaxNodeSizeXLog2, MaxNodeSizeYLog2, MaxNodeSizeZLog2} if (K > (gsh_log2_max_nodesize - gsh_log2_min_nodesize)) K = gsh_log2_max_nodesize - gsh_log2_min_nodesize; if (M > gsh_log2_min_nodesize) M = gsh_log2_min_nodesize; if (gsh_log2_max_nodesize = = gsh_log2_min_nodesize) M = 0; if (log2_trisoup_node_size != 0) { K = gsh_log2_max_nodesize - gsh_log2_min_nodesize; M = 0; }

[0127] Region boxes are now described. In addition to the bounding boxes specified above, G-PCC also supports the signaling of a region box that is used to indicate a modified QP value to the attributes of a particular region of the point cloud. Typically, the QP value associated with an attribute may be specified in the attribute slice header (in addition to some syntax elements in the attribute parameter set). However, certain regions of the point cloud may have peculiar characteristics that may be different from the rest of the slice. For example, a more dense region of the slice may be coded using a finer representation (lower QP) or a more sparse region of the slice may be coded using a coarser representation (higher QP). The region box may be useful for specifying a different QP for attributes of a certain region of a slice. Region box-related syntax follows.

[0128] Region Box-Related Syntax

TABLE-US-00012 attribute_slice_header( ) { Descriptor ash_attr_parameter_set_id ue(v) ash_attr_sps_attr_idx ue(v) ash_attr_geom_slice_id ue(v) if ( aps_slice_qp_delta_present_flag ) { ash_attr_qp_delta_luma se(v) if( attribute_dimension_minus1[ ash_attr_sps_attr_idx ] > 0 ) ash_attr_qp_delta_chroma se(v) } ash_attr_layer_qp_delta_present_flag u(1) if ( ash_attr_layer_qp_delta_present_flag ) { ash_attr_num_layer_qp_minus1 ue(v) for( i = 0; i < NumLayerQp; i++ ){ ash_attr_layer_qp_delta_luma[i] se(v) if( attribute_dimension_minus1[ ash_attr_sps_attr_idx ] > 0 ) ash_attr_layer_qp_delta_chroma[i] se(v) } } ash_attr_region_qp_delta_present_flag u(1) if ( ash_attr_region_qp_delta_present_flag ) { ash_attr_qp_region_box_origin_x ue(v) ash_attr_qp_region_box_origin_y ue(v) ash_attr_qp_region_box_origin_z ue(v) ash_attr_qp_region_box_width ue(v) ash_attr_qp_region_box_height ue(v) ash_attr_qp_region_box_depth ue(v) ash_attr_region_qp_delta se(v) } byte_alignment( ) }

[0129] Region box-related semantics follow:

[0130] ash_attr_parameter_set_id specifies the value of the aps_attr_parameter_set_id of the active APS.

[0131] ash_attr_sps_attr_idx specifies the order of attribute set in the active SPS. The value of ash_attr_sps_attr_idx shall be in the range of 0 to sps_num_attribute_sets in the active SPS.

[0132] ash_attr_geom_slice_id specifies the value of the gsh_slice_id of the active Geometry Slice Header.

[0133] ash_attr_layer_qp_delta_present_flag equal to 1 specifies that the ash_attr_layer_qp_delta_luma and ash_attr_layer_qp_delta_chroma syntax elements are present in current ASH. ash_attr_layer_qp_delta_present_flag equal to 0 specifies that the ash_attr_layer_qp_delta_luma and ash_attr_layer_qp_delta_chroma syntax elements are not present in current ASH.

[0134] ash_attr_num_layer_qp_minus1 plus 1 specifies the number of layer in which ash_attr_qp_delta_luma and ash_attr_qp_delta_chroma are signaled. When ash_attr_num_layer_qp is not signaled, the value of ash_attr_num_layer_qp is inferred to be 0. The value of NumLayerQp is derived as follows: [0135] NumLayerQp=num_layer_qp_minus1+1

[0136] ash_attr_qp_delta_luma specifies the luma delta qp from the initial slice qp in the active attribute parameter set. When ash_attr_qp_delta luma is not signaled, the value of ash_attr_qp_delta_luma is inferred to be 0.

[0137] ash_attr_qp_delta_chroma specifies the chroma delta qp from the initial slice qp in the active attribute parameter set. When ash_attr_qp_delta_chroma is not signaled, the value of ash_attr_qp_delta_chroma is inferred to be 0.

[0138] The variables InitialSliceQpY and InitialSliceQpC are derived as follows:

TABLE-US-00013 InitialSliceQpY = aps_attrattr_initial_qp + ash_attr_qp_delta_luma InitialSliceQpC = aps_attrattr_initial_qp + aps_attr_chroma_qp_ offset + ash_attr_qp_delta_chroma

[0139] ash_attr_layer_qp_delta_luma specifies the luma delta qp from the InitialSliceQpY in each layer. When ash_attr_layer_qp_delta_luma is not signaled, the value of ash_attr_layer_qp_delta_luma of all layers are inferred to be 0.

[0140] ash_attr_layer_qp_delta_chroma specifies the chroma delta qp from the InitialSliceQpC in each layer. When ash_attr_layer_qp_delta_chroma is not signaled, the value of ash attr_layer_qp_delta_chroma of all layers are inferred to be 0.

TABLE-US-00014 The variables SliceQpY[ i ] and SliceQpC[ i ] with i = 0 … NumLayerQPNumQPLayer - 1 are derived as follows: for ( i = 0; i < NumLayerQPNumQPLayer; i++) { SliceQpY[ i ] = Initial SliceQpY + ash_attr_layer_qp_delta_luma[ i ] SliceQpC[ i ] = InitialSliceQpC + ash_attr_layer_qp_delta_chroma[ i ] }

[0141] ash_attr_region_qp_delta_present_flag equal to 1 indicates the ash_attr_region_qp_delta and region bounding box origin and size are present in current ASH. ash_attr_region_qp_delta_present_flag equal to 0 indicates the ash_attr_region_qp_delta and region bounding box origin and size are not present in current ASH.

[0142] ash_attr_qp_region_box_origin_x indicates the x offset of the region bounding box relative to slice_origin_x. When not present, the value of ash_attr_qp_region_box_origin_x is inferred to be 0.

[0143] ash_attr_qp_region_box_origin_y indicates the y offset of the region bounding box relative to slice_origin_y. When not present, the value of ash_attr_qp_region_box_origin_y is inferred to be 0.

[0144] ash_attr_qp_region_box_origin_z indicates the z offset of the region bounding box relative to slice_origin_z. When not present, the value of ash_attr_qp_region_box_origin_z is inferred to be 0.

[0145] The variable RegionboxX, RegionboxY and RegionboxZ specifying the region box origin are set equal to ash_attr_qp_region_box_origin_x, ash_attr_qp_region_box_origin_y and ash_attr_qp_region_box_origin_z respectively.

[0146] ash_attr_qp_region_box_size_width indicates the width of the region bounding box. When not present, the value of ash_attr_qp_region_box_size_width is inferred to be 0.

[0147] ash_attr_qp_region_box_size_height indicates the height of the region bounding box. When not present, the value of ash_attr_qp_region_box_size_height is inferred to be 0.

[0148] ash_attr_qp_region_box_size_depth indicates the depth of the region bounding box. When not present, the value of ash_attr_qp_region_box_size_depth is inferred to be 0.

[0149] The variable RegionboxWidth, RegionboxHeight and RegionboxDepth specifying the region box size are set equal to ash_attr_qp_region_box_size_width, ash_attr_qp_region_box_size_height and ash_attr_qp_region_box_size_depth respectively.

[0150] ash_attr_region_qp_delta specifies the delta qp from the SliceQpY[i] and SliceQpC[i] (with i=0 … NumLayerQPNumQPLayer-1) of the region specified by ash_attr_qp_region_box. When not present, the value of ash_attr_region_qp_delta is inferred to be 0.

[0151] The variable RegionboxDeltaQp specifying the region box delta quantization parameter is set equal to ash_attr_region_qp_delta.

[0152] Attribute specific parameter signaling in a sequency parameter set (SPS) is now described. G-PCC encoder 200 may signal the number of attributes associated with the point cloud in an SPS, with a syntax element named sps_num_attribute_sets. For each attribute, G-PCC encoder 200 may signal in the SPS a few attribute specific parameters, such as bit-depth, secondary bit-depth, attribute dimension, attribute type (color, reflectance, frameIndex etc.) and color space related information. The corresponding syntax and semantics are shown below.

TABLE-US-00015 sps_num_attribute_sets ue(v) for( i = 0; i< sps_num_attribute_sets; i++ ) { attribute_dimension_minus1[ i ] ue(v) attribute_instance_id[ i ] ue(v) attribute_bitdepth_minus1[i] ue(v) if(attribute_dimension_minus1[ i ] > 0 ) attribute_secondary_bitdepth_minus1[ i ] ue(v) attribute_cicp_colour_primaries[ i ] ue(v) attribute_cicp_transfer_characteristics[ i ] ue(v) attribute_cicp_matrix_coeffs[ i ] ue(v) attribute_cicp_video_full_range_flag[ i ] u(1) known_attribute_label_flag[ i ] u(1) if( known_attribute_label_flag[ i ] ) known_attribute_label[ i ] ue(v) else attribute_label_four_bytes[ i ] u(32) }

attribute_dimension_minus1[i] plus 1 specifies the number of components of the i-th attribute. attribute_instance_id[i] specifies the instance id for the i-th attribute. [0153] NOTE–The value of the attribute_instance_id identifies the attribute when two or more attribute having the attribute_label_four_bytes value is in the bitstream. For example, it is useful for the point cloud having multiple color from the different view point. attribute_bitdepth_minus1[i] plus 1 specifies the bitdepth for first component of the i-th attribute signal(s). attribute_secondary_bitdepth_minus1[i] plus 1 specifies the bitdepth for secondary component of the i-th attribute signal(s). attribute_cicp_colour_primaries[i] indicates the chromaticity coordinates of the colour attribute source primaries of the i-th attribute. The semantics are as specified for the code point ColourPrimaries in ISO/JEC 23091-2. attribute_cicp_transfer_characteristics[i] either indicates the reference opto-electronic transfer characteristic function of the colour attribute as a function of a source input linear optical intensity L.sub.c with a nominal real-valued range of 0 to 1 or indicates the inverse of the reference electro-optical transfer characteristic function as a function of an output linear optical intensity L.sub.o with a nominal real-valued range of 0 to 1. The semantics are as specified for the code point TransferCharacteristics in ISO/JEC 23091-2. attribute_cicp_matrix_coeffs[i] describes the matrix coefficients used in deriving luma and chroma signals from the green, blue, and red, or Y, Z, and X primaries. The semantics are as specified for the code point MatrixCoefficients in ISO/JEC 23091-2. attribute_cicp_video_full_range_flag[i] specifies indicates the black level and range of the luma and chroma signals as derived from E’Y, E’PB, and E’PR or E’R, E’G, and E’B real-valued component signals. The semantics are as specified for the code point VideoFullRangeFlag in ISO/JEC 23091-2. known_attribute_label_flag[i] equal to 1 specifies know_attribute_label is signaled for the i-th attribute. known_attribute_label_flag[i] equal to 0 specifies attribute_label_four_bytes is signaled for the i-th attribute. known_attribute_label[i] equal to 0 specifies the attribute is colour. known_attribute_label[i] equal to 1 specifies the attribute is reflectance. known_attribute_label[i] equal to 2 specifies the attribute is frame index. attribute_label_four_bytes[i] indicates the known attribute type with the 4 bytes code. 7.1 describes the list of supported attributes and their relationship with attribute_label_four_bytes[i].

TABLE-US-00016 [0153] TABLE 7.1 attribute_label_four_bytes attribute_label_four_bytes[ i ] Attribute type 0 Color 1 Reflectance 2 Frame index 3 Material ID 4 Transparency 5 Normals 6 … 255 Reserved 256 … 0xffffffff unspecified

[0154] The attribute parameter set (APS) is now described. G-PCC syntax allows signaling of a separate parameter set for each attribute. For example, if one point cloud has two different attributes associated with the point cloud, for example color and reflectance, each attribute may have their own APS. An APS contains information about attribute quantization parameters (initial qp, qp offsets etc.), level of detail (LoD) generation-specific parameters, and/or coding tools for attribute coding.

[0155] The level of detail (LoD) structure partitions the point cloud into non-overlapping subsets of points referred to as refinement levels (R.sub.l).sub.i=0 … L-1, according to a set of Euclidian distances (d.sub.l).sub.i=0 … L-1 specified by the user, in a way, that the entire point cloud is represented by the union of all the refinement levels. The level of detail (LoD) l, LoD.sub.l, is obtained by taking the union of the refinement levels R.sub.0, R.sub.1, … , R.sub.l: [0156] LOD.sub.0=R.sub.0 [0157] LOD.sub.1=LOD.sub.0.orgate.R.sub.1 … . [0158] LOD.sub.j=LOD.sub.j-1.orgate.R.sub.j … . [0159] LOD.sub.l+i=LOD.sub.l.orgate.R.sub.l represents the entire point cloud.

[0160] FIG. 4 is a conceptual diagram illustrating an example Level of Details (LoD) generation process. Original order 400 of the points in the point cloud is depicted in FIG. 4. With LoD, the order of the points may change as shown in LoD-based order 402. For example, LoD.sub.0 includes P0, P5, P4, and P2. LoD.sub.1 includes P0, P5, P4, P2, P1, P6, and P3. LOD.sub.2 includes P0, P5, P4, P2, P1, P6, P3, P9, P8, and P7, which is the entire point cloud of the example of FIG. 4.

[0161] Thus, LoD generation provides a scalable representation for the attribute information of a point cloud, where increasing the LoD level results in a progressive increase of the details of attribute information. Additionally, G-PCC decoder 300 performs attribute decoding in LoD order, e.g., first all the points in LoD.sub.0 (R0) are decoded, then the points corresponding to refinement level R.sub.1 are decoded in order to generate LoD.sub.1, and this process may continue further to progressively generate all the LoD. For this reason, a point in an LoD layer can be predicted either from the points in previous LoD layer(s) or, if applicable, from the already decoded points in the same refinement level (e.g., EnableReferringSameLoD=1) as shown in FIG. 5.

[0162] FIG. 5 is a conceptual diagram illustrating possible point prediction using LoD. Original order 500 of the points in the point cloud is depicted. Additionally, LoD-based order 502 is depicted. With LoD, point P4 may be used to predict point P6, as point P4 is in LoD.sub.0 which is decoded prior to point P6 which is in LoD.sub.1. If EnableReferringSameLoD=1, then point P1 may be used to predict point P6, as point P1 is decoded before point P6. However, if EnableReferringSameLoD=0, then point P1 may not be used to predict point P6.

[0163] By using LoD generation, such as with spatial scalability, it may be possible to access a lower resolution point cloud as a thumbnail with less decoder complexity and/or using less bandwidth. When spatial scalability is needed, it may be desirable to decode lower geometry and the corresponding attribute bitstream in a harmonized fashion.

[0164] FIG. 6 is a conceptual diagram depicting G-PCC decoding with different LoDs. For example, to generate full resolution point cloud 642, G-PCC decoder 300 may utilize a high LoD (e.g., LoD 606 and LoD 608) in both geometry bitstream 620 and the attribute bitstream 622. To generate low resolution point cloud 632, G-PCC decoder 300 may utilize a lower LoD (e.g., LoD 602 and LoD 604) in partial octree bitstream 610 and partial lifting bitstream 612.

[0165] To achieve the harmonized spatial scalability, the attribute decoder (e.g., attribute arithmetic decoding unit 304 of FIG. 3) may be extended to decode the lower resolution geometry point cloud (e.g., low resolution point cloud 632) from the partially decoded octree bitstream (e.g., partial octree bitstream 610), where the decoded position of a point in the lower resolution geometry point cloud is quantized as INT(pos/2k)*2k.

[0166] One or more examples disclosed in this document may be applied independently or combined.

[0167] Constraints on region box dimensions are now described. The semantics of the region box in the draft G-PCC standard allow the region box to exceed the dimensions of the slice that contains the region. G-PCC encoder 200, when signaling the region width, height and depth, may use exponential Golomb coding. G-PCC encoder 200 signaling values for these syntax elements that exceed the slice dimensions may not provide any benefit to G-PCC decoder 300 because there are no points that belong to the slice that are outside the slice bounding box. Furthermore, the shape of a slice bounding box is a regular cuboid/cube, and therefore there may be no benefit in G-PCC encoder 200 signaling a region that is larger than the slice bounding box. This also applies to the origin of the region box as the origin of the region box should also be contained within the slice.

[0168] Moreover, the signaling of region box dimensions allows the signaling of width, height, or depth to be equal to 0. However, if any of these elements are signaled as zero, the G-PCC draft standard considers the region to be empty.

[0169] According to the techniques of this disclosure, constraints may be added such that the region box does not exceed the slice dimensions, or more specifically, the slice bounding box dimensions. For example, G-PCC decoder 300 may determine dimensions of a region box. G-PCC decoder 300 may determine dimensions of a slice bounding box. G-PCC decoder 300 may decode a slice of the point cloud data associated with the slice bounding box. The dimensions of the region box may be constrained to not exceed the dimensions of the slice bounding box.

[0170] In some examples, constraints are added such that the origin region box is contained within the slice. In other examples, constraints are added such that no point in the region box is outside the slice, or specifically, outside the slice bounding box.

[0171] In some examples, the signaling of the region box width, height and depth are modified such that a value of 0 is disallowed for any of these region box attributes. In other words, G-PCC encoder 200 may not signal a value of 0 for region box width, height or depth.

[0172] In an example, the semantics of the syntax elements of the region box are updated so that the region box origin or the region box does not exceed the slice dimensions. The beginning of changes from the draft G-PCC standard ISO/IEC JTC 1/SC 29/WG 11 N18887, are marked and the end of changes are marked . The beginning of deletions from the draft G-PCC standard are marked and the end of deletions are marked .

[0173] ash_attr_region_qp_delta_present_flag equal to 1 indicates the ash_attr_region_qp_delta and region bounding box origin and size are present in current ASH. ash_attr_region_qp_delta_present_flag equal to 0 indicates the ash_attr_region_qp_delta and region bounding box origin and size are not present in current ASH.

[0174] ash_attr_qp_region_box_origin_x indicates the x offset of the region bounding box relative to slice_origin_x. When not present, the value of ash_attr_qp_region_box_origin_x is inferred to be 0.

[0175] ash_attr_qp_region_box_origin_y indicates the y offset of the region bounding box relative to slice_origin_y. When not present, the value of ash_attr_qp_region_box_origin_y is inferred to be 0.

[0176] ash_attr_qp_region_box_origin_z indicates the z offset of the region bounding box relative to slice_origin_z. When not present, the value of ash_attr_qp_region_box_origin_z is inferred to be 0.

[0177] The variable RegionboxX, RegionboxY and RegionboxZ specifying the region box origin are set equal to ash_attr_qp_region_box_origin_x, ash_attr_qp_region_box_origin_y and ash_attr_qp_region_box_origin_z respectively.

[0178] ash_attr_qp_region_box_size_width_minus1 plus 1 indicates the width of the region bounding box. When not present, the value of ash_attr_qp_region_box_size_width_minus1 is inferred to be -1 0 .

[0179] ash_attr_qp_region_box_size_height_minus1 plus 1 indicates the height of the region bounding box. When not present, the value of ash_attr_qp_region_box_size_height_minus1 is inferred to be -1 0 .

[0180] ash_attr_qp_region_box_size_depth_minus1 plus 1 indicates the depth of the region bounding box. When not present, the value of ash_attr_qp_region_box_size_depth_minus1 is inferred to be -1 0 .

[0181] The variable RegionboxWidth, RegionboxHeight and RegionboxDepth specifying the region box size are set equal to ash_attr_qp_region_box_size_width, ash_attr_qp_region_box_size_height and ash_attr_qp_region_box_size_depth respectively.

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Qualcomm Patent | High-level syntax design for geometry-based point cloud compression

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