Granted Patent B2

US 12,256,096 · App. 18/623,198 · Granted Mar 18, 2025

Inventors: Luong Pham Van (San Diego, CA); Adarsh Krishnan Ramasubramonian (Irvine, CA); Bappaditya Ray (San Diego, CA); Geert Van der Auwera (Del Mar, CA); Marta Karczewicz (San Diego, CA)

Assignee: QUALCOMM Incorporated

H04N19/527H04N19/124H04N19/139H04N19/177H04N19/597

Abstract

Claims (58)

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

a memory configured to store data representing points of a point cloud; and

a processing system comprising one or more processors implemented in circuitry, the processing system configured to:

determine height values of points in a point cloud;

decode a data structure including data representing a top threshold and a bottom threshold;

classify points having height values between the top threshold and the bottom threshold into the set of ground points;

classify points having height values above the top threshold or below the bottom threshold into the set of object points;

decode the ground points and the object points according to the classifications; and

decode a geometry data unit header (GDH) that includes data that overrides or refines the data of the data structure for the at least one of (i) the top threshold or (ii) the bottom threshold.

2. The device of claim 1 , wherein to decode the object points, the processing system is configured to:

derive a set of global motion information for the object points; and

predict the object points using the set of global motion information.

3. The device of claim 2 , wherein to derive the set of global motion information, the processing system is configured to derive a rotation matrix and a translation vector, and wherein to decode the object points, the processing system is configured to apply the rotation matrix and the translation vector to reference points of a reference frame.

4. The device of claim 3 , wherein to decode the object points, the processing system is further configured to:

determine local node motion vectors of nodes of a prediction tree, the nodes including respective sets of reference points of the reference frame; and

apply the local node motion vectors to the nodes.

5. The device of claim 1 , wherein the processing system is configured to derive the set of global motion information only for the object points.

6. The device of claim 1 , wherein the set of global motion information comprises a first set of global motion information, and wherein to decode the ground points, the processing system is configured to:

derive a second set of global motion information for the ground points; and

predict the ground points using the second set of global motion information.

7. The device of claim 6 , wherein the processing system is configured to derive the second set of global motion information only for the ground points.

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

a memory configured to store data representing points of a point cloud; and

a processing system comprising one or more processors implemented in circuitry, the processing system configured to:

determine height values of points in a point cloud;

encode a data structure including data representing a top threshold and a bottom threshold;

classify points having height values between the top threshold and the bottom threshold into the set of ground points;

classify points having height values above the top threshold or below the bottom threshold into the set of object points; and

encode the ground points and the object points according to the classifications,

encode a geometry data unit header (GDH) that includes data that overrides or refines the data of the data structure for the at least one of (i) the top threshold or (ii) the bottom threshold.

9. The device of claim 8 , wherein to encode the object points, the processing system is configured to:

derive a set of global motion information for the object points; and

predict the object points using the set of global motion information.

10. The device of claim 9 , wherein to derive the set of global motion information, the processing system is configured to derive a rotation matrix and a translation vector, and wherein to encode the object points, the processing system is configured to apply the rotation matrix and the translation vector to reference points of a reference frame.

11. The device of claim 10 , wherein to encode the object points, the processing system is further configured to:

determine local node motion vectors of nodes of a prediction tree, the nodes including respective sets of reference points of the reference frame; and

apply the local node motion vectors to the nodes.

12. The device of claim 8 , wherein the processing system is configured to derive the set of global motion information only for the object points.

13. The device of claim 8 , wherein the set of global motion information comprises a first set of global motion information, and wherein to encode the ground points, the processing system is configured to:

derive a second set of global motion information for the ground points; and

predict the ground points using the second set of global motion information.

14. The device of claim 13 , wherein the processing system is configured to derive the second set of global motion information only for the ground points.

15. A method of coding point cloud data, the method comprising:

determining height values of points in a point cloud;

coding a data structure including data representing a top threshold and a bottom threshold;

classifying points having height values between the top threshold and the bottom threshold into the set of ground points;

classifying points having height values above the top threshold or below the bottom threshold into the set of object points;

coding the ground points and the object points according to the classifications; and

coding a geometry data unit header (GDH) that includes data that overrides or refines the data of the data structure for the at least one of (i) the top threshold or (ii) the bottom threshold.

16. The method of claim 15 , wherein coding the object points comprises:

deriving a set of global motion information for the object points; and

predicting the object points using the set of global motion information.

17. The method of claim 16 , wherein deriving the set of global motion information comprises deriving the set of global motion information only for the object points.

18. The method of claim 16 , wherein the set of global motion information comprises a first set of global motion information, and wherein coding the ground points comprises:

deriving a second set of global motion information for the ground points; and

predicting the ground points using the second set of global motion information.

19. The method of claim 15 , wherein the coding includes encoding.

20. The method of claim 15 , wherein the coding includes decoding.

Assignments (1)

Continuity (4)

References Cited (50)

Cited By (2)

US 12,671,837 US 12,739,395