IP Library Granted Patent US 12684163
Granted Patent B2
US 12684163 · App. 18/290,599 · Granted Jul 14, 2026

Point cloud data transmission device, point cloud data transmission method, point cloud data reception device, and point cloud data reception method

Inventor: Hyunmook Oh (Seoul, KR)
Assignee: LG Electronics Inc.
H04N19/54H04N19/105H04N19/167H04N19/172H04N19/196H04N19/597
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Quick Facts
Patent No.
US 12684163
App. No.
18/290,599
Granted
Jul 14, 2026
Kind
B2
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 including point cloud data; and decoding the point cloud data.

Claims (31)

1 . A method comprising:

encoding geometry data of point cloud data based on an occupancy tree; and

encoding attribute data of the point cloud data,

wherein the encoding geometry data includes:

predicting an occupancy for a node of the octree based on a reference frame; and

obtaining an occupied neighborhood pattern for a child node of the node based on an occupancy of three neighboring child nodes for the child node, and

wherein the encoded geometry data and the encoded attribute data are included in a bitstream,

wherein the bitstream includes information for specifying whether or not neighbor prediction is enabled for the occupancy tree.

2 . The method of claim 1 , wherein the geometry data is predicted for a prediction unit (PU) based on a search window from the reference frame.

3 . The method of claim 2 , the encoding the geometry data comprises:

generating a predicted value for the PU based on a predictor included in the search window, neighbors of the predictor, point cloud data contained in the PU, and neighbors of the point cloud data; and

generating a motion vector based on the predicted value and the PU.

4 . The method of claim 3 , wherein the encoding the geometry data comprises:

generating the motion vector at a depth of a tree containing the point cloud data; or generating a motion vector at a lower depth of the depth,

wherein the motion vector for the lower depth is generated based on a split and occupancy for the lower depth.

5 . The method of claim 3 , wherein the encoding the geometry data comprises:

predicting, based on the motion vector, the point cloud data in the PU.

6 . A method comprising:

obtaining a bitstream generated by:

encoding geometry data of point cloud data based on an occupancy tree; and

encoding attribute data of the point cloud data, wherein the encoding geometry data includes:

predicting an occupancy for a node of the octree based on a reference frame; and

obtaining an occupied neighborhood pattern for a child node of the node based on an occupancy of three neighboring child nodes for the child node, and wherein the encoded geometry data and the encoded attribute data are included in a bitstream, wherein the bitstream includes information for specifying whether or not neighbor prediction is enabled for the occupancy tree; and

transmitting data for the point cloud data including the bitstream.

7 . A method comprising:

decoding geometry data of point cloud data in a bitstream based on an occupancy tree; and

decoding attribute data of the point cloud data in the bitstream,

wherein the decoding the geometry data includes:

predicting an occupancy for a node of the occupancy tree based on a reference frame; and

obtaining an occupied neighborhood pattern for a child node of the node based on an occupancy of three neighboring child nodes for the child node, and

wherein the bitstream includes information for specifying whether or not neighbor prediction is enabled for the occupancy tree.