US-20260127775-A1 - POINT CLOUD DATA TRANSMISSION DEVICE, POINT CLOUD DATA TRANSMISSION METHOD, POINT CLOUD DATA RECEPTION DEVICE, AND POINT CLOUD DATA RECEPTION METHOD

US20260127775A1US 20260127775 A1US20260127775 A1US 20260127775A1US-20260127775-A1

Abstract

A point cloud data transmission method according to embodiments may comprise the steps of encoding point cloud data, and transmitting a bitstream including the point cloud data. A point cloud data reception method according to embodiments may comprise the steps of receiving a bitstream comprising point cloud data, and decoding the point cloud data.

Inventors

Hyunmook Oh
Sejin Oh

Assignees

LG ELECTRONICS INC.

Dates

Publication Date: 20260507
Application Date: 20260105
Priority Date: 20201030

Claims (15)

1 . A method comprising: decoding geometry data for a slice of point cloud data in a bitstream based on an octree, wherein the slice is mapped to a subgroup of a layer group including tree levels of the octree; and decoding attribute data for the slice of the point cloud data, wherein the decoding the attribute data for the slice includes generating Levels of Detail (LoDs), wherein the generating the LoDs includes: obtaining a point of a node in a second level of the LoDs based on sampling a point in child nodes for the node in a first level of the LoDs, wherein the point in the child nodes is a point with a lowest point index in the child nodes or a point with a greatest point index in the child nodes.
2 . The method of claim 1 , wherein the bitstream includes information for representing that the attribute data is reconstructed based on a part of the octree, information related to a number of octree levels in the octree, and information for representing that the geometry data is partially decoded in the octree.
3 . The method of claim 1 , wherein the generating the LoDs further includes: obtaining a point of a parent node in a third level of the LoDs based on sampling a point in child nodes for the parent node in the second level, and wherein the node in the second level is included in the child nodes for the parent node in the second level, wherein the point in the child nodes for the node in the first level is the point with the lowest index in the child nodes for the node in the first level, and wherein the point in the child nodes for the parent node in the second level is the point with the greatest index in the child nodes for the parent node in the second level.
4 . The method of claim 1 , wherein the bitstream includes information indicating a sampling position for each level of the LoDs for the attribute data, wherein the sampling position is a node having a point with a lowest point index or a point with a greatest point index.
5 . The method of claim 1 , wherein the bitstream includes information indicating a sampling position for a level having a lower node of a root node of the LoDs for the attribute data.
6 . A method comprising: encoding geometry data for a slice of point cloud data based on an octree wherein the slice is mapped to a subgroup of a layer group including tree levels of the octree; and encoding attribute data for the slice of the point cloud data, wherein the encoding the attribute data for the slice includes generating Levels of Detail (LoDs), wherein the generating the LoDs includes: obtaining a point of a node in a second level of the LoDs based on sampling a point in child nodes for the node in a first level of the LoDs, wherein the point in the child nodes is a point with a lowest point index in the child nodes or a point with a greatest point index in the child nodes.
7 . The method of claim 6 , wherein the encoded geometry data for the slice and the encoded attribute data for the slice are included in a bitstream, wherein the bitstream includes information for representing that the attribute data is reconstructed based on a part of the octree, information related to a number of octree levels in the octree, and information for representing that the geometry data is partially decoded in the octree.
8 . The method of claim 6 , wherein the generating the LoDs further includes: obtaining a point of a parent node in a third level of the LoDs based on sampling a point in child nodes for the parent node in the second level, and wherein the node in the second level is included in the child nodes for the parent node in the second level, wherein the point in the child nodes for the node in the first level is the point with the lowest index in the child nodes for the node in the first level, and wherein the point in the child nodes for the parent node in the second level is the point with the greatest index in the child nodes for the parent node in the second level.
9 . The method of claim 6 , wherein the encoded geometry data for the slice and the encoded attribute data for the slice are included in a bitstream, and wherein the bitstream includes information indicating a sampling position for each level of the LoDs for the attribute data, wherein the sampling position is a node having a point with a lowest point index or a point with a greatest point index.
10 . The method of claim 6 , further comprising: wherein the encoded geometry data for the slice and the encoded attribute data for the slice are included in a bitstream, wherein the bitstream includes information indicating a sampling position for a level having a lower node of a root node of the LoDs for the attribute data.
11 . A method comprising: obtaining a bitstream generated by: encoding geometry data for a slice of point cloud data based on an octree wherein the slice is mapped to a subgroup of a layer group including tree levels of the octree; and encoding attribute data for the slice of the point cloud data, wherein the encoding the attribute data for the slice includes generating Levels of Detail (LoDs), wherein the generating the LoDs includes: obtaining a point of a node in a second level of the LoDs based on sampling a point in child nodes for the node in a first level of the LoDs, wherein the point in the child nodes is a point with a lowest point index in the child nodes or a point with a greatest point index in the child nodes; and transmitting data for the point cloud data including the bitstream.
12 . The method of claim 11 , wherein the bitstream includes information for representing that the attribute data is reconstructed based on a part of the octree, information related to a number of octree levels in the octree, and information for representing that the geometry data is partially decoded in the octree.
13 . The method of claim 11 , wherein the generating the LoDs further includes: obtaining a point of a parent node in a third level of the LoDs based on sampling a point in child nodes for the parent node in the second level, and wherein the node in the second level is included in the child nodes for the parent node in the second level, wherein the point in the child nodes for the node in the first level is the point with the lowest index in the child nodes for the node in the first level, and wherein the point in the child nodes for the parent node in the second level is the point with the greatest index in the child nodes for the parent node in the second level.
14 . The method of claim 11 , wherein the bitstream includes information indicating a sampling position for each level of the LoDs for the attribute data, wherein the sampling position is a node having a point with a lowest point index or a point with a greatest point index.
15 . The method of claim 11 , wherein the bitstream includes information indicating a sampling position for a level having a lower node of a root node of the LoDs for the attribute data.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a Continuation of U.S. patent application Ser. No. 18/029,563, filed on Mar. 30, 2023, which is a National Stage Application of International Application No. PCT/KR2021/015306, filed on Oct. 28, 2021, which claims the benefit of and priority to Korean Application No. 10-2020-0143675, filed on Oct. 30, 2020, which are hereby incorporated by reference in their entirety for all purposes as if fully set forth herein. TECHNICAL FIELD Embodiments relate to a method and device for processing point cloud content. BACKGROUND Point cloud content is content represented by a point cloud, which is a set of points belonging to a coordinate system representing a three-dimensional space. The point cloud content may express media configured in three dimensions, and is used to provide various services such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and self-driving services. However, tens of thousands to hundreds of thousands of point data are required to represent point cloud content. Therefore, there is a need for a method for efficiently processing a large amount of point data. SUMMARY Embodiments provide a device and method for efficiently processing point cloud data. Embodiments provide a point cloud data processing method and device for addressing latency and encoding/decoding complexity. The technical scope of the embodiments is not limited to the aforementioned technical objects, and may be extended to other technical objects that may be inferred by those skilled in the art based on the entire contents disclosed herein. To achieve these objects and other advantages and in accordance with the purpose of the disclosure, as embodied and broadly described herein, a method of transmitting point cloud data may include encoding the point cloud data, and transmitting a bitstream containing the point cloud data. A method of receiving point cloud data according to embodiments may include receiving a bitstream containing point cloud data and decoding the point cloud data. Devices and methods according to embodiments may process point cloud data with high efficiency. The devices and methods according to the embodiments may provide a high-quality point cloud service. The devices and methods according to the embodiments may provide point cloud content for providing general-purpose services such as a VR service and a self-driving service. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the disclosure and together with the description serve to explain the principle of the disclosure. For a better understanding of various embodiments described below, reference should be made to the description of the following embodiments in connection with the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts. In the drawings: FIG. 1 shows an exemplary point cloud content providing system according to embodiments; FIG. 2 is a block diagram illustrating a point cloud content providing operation according to embodiments; FIG. 3 illustrates an exemplary process of capturing a point cloud video according to embodiments; FIG. 4 illustrates an exemplary point cloud encoder according to embodiments; FIG. 5 shows an example of voxels according to embodiments; FIG. 6 shows an example of an octree and occupancy code according to embodiments; FIG. 7 shows an example of a neighbor node pattern according to embodiments; FIG. 8 illustrates an example of point configuration in each LOD according to embodiments; FIG. 9 illustrates an example of point configuration in each LOD according to embodiments; FIG. 10 illustrates a point cloud decoder according to embodiments; FIG. 11 illustrates a point cloud decoder according to embodiments; FIG. 12 illustrates a transmission device according to embodiments; FIG. 13 illustrates a reception device according to embodiments; FIG. 14 illustrates an exemplary structure operable in connection with point cloud data transmission/reception methods/devices according to embodiments; FIG. 15 illustrates scalable transmission according to embodiments; FIG. 16 illustrates a partial bitstream transmission procedure according to embodiments; FIG. 17 illustrates an LOD generation method according to embodiments; FIG. 18 shows layer groups for scalable transmission according to embodiments; FIG. 19 illustrates a mismatch between an encoder and a decoder according to embodiments; FIG. 20 illustrates a method to address a mismatch between the encoder and the decoder according to embodiments; FIG. 21 illustrates a method to address a mismatch between the encoder and the decoder according to embodiments; FIG. 22 illustrates a method to address a mismatch between the encoder and the decoder according to embodimen