Granted Patent B2

US 12,380,604 · App. 17/924,503 · Granted Aug 5, 2025

Inventors: Sooyeon Lee (Seoul, KR); Sejin Oh (Seoul, KR)

Assignee: LG ELECTRONICS INC.

G06T9/001

Abstract

Claims (65)

1. A method of encoding point cloud data, the method comprising:

encoding geometry data of point cloud data,

wherein the geometry data is encoded based on inter prediction,

wherein motion compensation is applied to a reference frame for the inter prediction,

wherein points for the reference frame are determined based on a threshold;

encoding attribute data of the point cloud data; and

transmitting a bitstream including the point cloud data,

wherein the bitstream includes parameter information to determine the points for the inter prediction.

2. The method of claim 1 , wherein the encoding of the point cloud data comprises:

splitting the point cloud data based on a prediction unit (PU);

generating a target point from a current frame and a reference frame for the point cloud data based on the PU; and

generating a searching pattern.

3. The method of claim 2 , wherein the target point is determined based on distances to points included in the PU.

4. The method of claim 2 , further comprising:

generating the searching pattern based on at least one of an azimuth, an elevation, or a region for the point cloud data; and

generating a best motion vector for the target point based on the searching pattern and performing motion estimation.

5. A device for encoding point cloud data, the device comprising:

an encoder configured to encode geometry data of point cloud data,

wherein the geometry data is encoded based on inter prediction,

wherein motion compensation is applied to a reference frame for the inter prediction,

wherein points for the reference frame are determined based on a threshold;

encode attribute data of the point cloud data; and

a transmitter configured to transmit a bitstream including the point cloud data,

wherein the bitstream includes parameter information to determine the points for the inter prediction.

6. The device of claim 5 , wherein the encoder configured to encode the point cloud data is configured to:

split the point cloud data based on a prediction unit (PU);

generate a target point from a current frame and a reference frame for the point cloud data based on the PU; and

generate a searching pattern.

7. The device of claim 6 , wherein the target point is determined based on distances to points included in the PU.

8. The device of claim 6 , wherein the device is configured to:

generate the searching pattern based on at least one of an azimuth, an elevation, or a region for the point cloud data; and

generate a best motion vector for the target point based on the searching pattern and perform motion estimation.

9. A method of decoding point cloud data, the method comprising:

receiving a bitstream including point cloud data;

decoding geometry data of the point cloud data,

wherein the geometry data is decoded based on inter prediction,

wherein motion compensation is applied to a reference frame for the inter prediction,

wherein points for the reference frame are determined based on a threshold;

decoding attribute data of the point cloud data,

wherein the bitstream includes parameter information to determine the points for the inter prediction.

10. The method of claim 9 , wherein the decoding of the point cloud data comprises:

splitting the point cloud data based on a prediction unit (PU);

generating a target point from a current frame and a reference frame for the point cloud data based on the PU; and

generating a searching pattern.

11. The method of claim 10 , wherein the target point is determined based on distances to points included in the PU.

12. The method of claim 10 , further comprising:

generating the searching pattern based on at least one of an azimuth, an elevation, or a region for the point cloud data; and

generating a best motion vector for the target point based on the searching pattern and performing motion estimation.

13. A device for decoding point cloud data, the device comprising:

a receiver configured to receive a bitstream including point cloud data; and

a decoder configured to

decode geometry data of the point cloud data,

wherein the geometry data is decoded based on inter prediction,

wherein motion compensation is applied to a reference frame for the inter prediction,

wherein points for the reference frame are determined based on a threshold;

decode attribute data of the point cloud data,

wherein the bitstream includes parameter information to determine the points for the inter prediction.

14. The device of claim 13 , wherein the decoder configured to decode the point cloud data is configured to:

split the point cloud data based on a prediction unit (PU);

generate a target point from a current frame and a reference frame for the point cloud data based on the PU; and

generate a searching pattern.

15. The device of claim 14 , wherein the target point is determined based on distances to points included in the PU.

16. The device of claim 14 , wherein the device is configured to:

generate the searching pattern based on at least one of an azimuth, an elevation, or a region for the point cloud data; and

generate a best motion vector for the target point based on the searching pattern and perform motion estimation.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (13)

Cited By (1)

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