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

1 . A method comprising:

encoding geometry data of point cloud data based on an octree; and

encoding attribute data of the point cloud data,

wherein the encoding attribute data includes:

generating Levels of Detail (LoDs) for the geometry data; and

generating a set of closest neighbor points for a point in a level of the LoDs based on an overall distance between the point and a closest neighbor point of the set of closest neighbor points,

wherein the overall distance is generated based on:

a geometry distance generated based on a difference between a reconstructed position of the point and a reconstructed position of the closest neighbor point; and

an attribute distance generated based on a sum of absolute differences, wherein each of the absolute differences is generated between a reconstructed attribute value for the point and a reconstructed attribute value of the closest neighbor point for each of a plurality of attributes for the point.

2 . The method of claim 1 ,

wherein the overall distance is generated based on a weighted sum of the geometry distance multiplied by a first weight and the attribute distance multiplied by a second weight.

3 . The method of claim 1 ,

wherein the set of closest neighbor points is generated based on:

whether the overall distance is within a threshold; or

whether the attribute distance is within the threshold.

4 . The method of claim 1 ,

wherein the reconstructed attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is generated based on:

an attribute value of a parent node of the point in the octree;

an attribute value of a previously reconstructed point having a minimum geometry distance to the point; or

an average of attribute values of a plurality of previously reconstructed points adjacent to the point.

5 . The method of claim 1 ,

wherein the reconstructed attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is generated based on an attribute value of a parent node of the point in the octree, and

wherein the attribute distance is generated between the attribute value of the parent node of the point and an attribute value of the parent node of the closest neighbor point.

6 . A method comprising:

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

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

wherein the decoding attribute data includes:

generating Levels of Detail (LoDs) for the geometry data; and

obtaining a set of closest neighbor points for a point in a level of the LoDs, based on an overall distance between the point and a closest neighbor point of the set of closest neighbor points,

wherein the overall distance is obtained based on:

a geometry distance obtained based on a difference between a decoded position of the point and a decoded position of the closest neighbor point; and

an attribute distance obtained based on a sum of absolute differences, wherein each of the absolute differences is obtained between a decoded attribute value for the point and a decoded attribute value of the closest neighbor point for each of a plurality of attributes for the point.

7 . The method of claim 6 ,

wherein the overall distance is obtained based on a weighted sum of the geometry distance multiplied by a first weight and the attribute distance multiplied by a second weight.

8 . The method of claim 6 ,

wherein the set of closest neighbor points is obtained from the neighbor points based on:

whether the overall distance is within a threshold; or

whether the attribute distance is within the threshold.

9 . The method of claim 6 ,

wherein the decoded attribute value for the point is an attribute of a correlated point, and wherein the attribute value of the correlated point is generated based on:

an attribute value of a parent node of the point in the octree;

an attribute value of a previously decoded point having a minimum geometry distance to the point; or

an average of attribute values of a plurality of previously decoded points adjacent to the point.

10 . The method of claim 6 ,

wherein the decoded attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is obtained based on an attribute value of a parent node of the point in the octree, and

wherein the attribute distance is generated between the attribute value of the parent node of the point and an attribute value of the parent node of the closest neighbor point.

11 . A device comprising:

a memory; and

at least one processor connected to the memory, wherein the at least one processor is configured to:

encode geometry data of point cloud data based on an octree;

encode attribute data of the point cloud data,

wherein the to encode attribute data, the at least one processor is further configured to:

generate Levels of Detail (LoDs) for the geometry data; and

generate a set of closest neighbor points for a point in a level of the LoDs based on an overall distance between the point and a closest neighbor point of the set of closest neighbor points,

wherein the overall distance is generated based on:

a geometry distance generated based on a difference between a reconstructed position of the point and a reconstructed position of the closest neighbor point; and

an attribute distance generated based on a sum of absolute differences, wherein each of the absolute differences is generated between a reconstructed attribute value for the point and a reconstructed attribute value of the closest neighbor point for each of a plurality of attributes for the point.

12 . The device of claim 11 ,

wherein the overall distance is generated based on a weighted sum of the geometry distance multiplied by a first weight and the attribute distance multiplied by a second weight.

13 . The device of claim 11 ,

wherein the set of closest neighbor points is generated based on:

whether the overall distance is within a threshold; or

whether the attribute distance is within the threshold.

14 . The device of claim 11 ,

wherein the reconstructed attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is generated based on:

an attribute value of a parent node of the point in the octree;

an attribute value of a previously reconstructed point having a minimum geometry distance to the point; or

an average of attribute values of a plurality of previously reconstructed points adjacent to the point.

15 . The device of claim 11 ,

wherein the reconstructed attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is generated based on an attribute value of a parent node of the point in the octree, and

wherein the attribute distance is generated between the attribute value of the parent node of the point and an attribute value of the parent node of the closest neighbor point.

16 . A device comprising:

a memory; and

at least one processor connected to the memory, wherein the at least one processor is configured to:

decode geometry data of the point cloud data in a bitstream based on an octree; and

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

wherein, the to decode attribute data, the at least one processor is further configured to:

generate Levels of Detail (LoDs) for the geometry data; and

obtain a set of closest neighbor points for a point in a level of the LoDs based on an overall distance between the point and a closest neighbor point of the set of closest neighbor points,

wherein the overall distance is obtained based on:

a geometry distance obtained based on a difference between a decoded position of the point and a reconstructed position of the closest neighbor point; and

an attribute distance obtained based on a sum of absolute differences, wherein each of the absolute differences is obtained between a decoded attribute value for the point and a decoded attribute value of the closest neighbor point for each of a plurality of attributes for the point.

17 . The device of claim 16 ,

wherein the overall distance is obtained based on a weighted sum of the geometry distance multiplied by a first weight and the attribute distance multiplied by a second weight.

18 . The device of claim 16 ,

wherein the set of closest neighbor points is obtained from the neighbor points based on:

whether the overall distance is within a threshold; or

whether the attribute distance is within the threshold.

19 . The device of claim 16 ,

wherein the decoded attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is generated based on:

an attribute value of a parent node of the point in the octree;

an attribute value of a previously decoded point having a minimum geometry distance to the point; or

an average of attribute values of a plurality of previously decoded points adjacent to the point.

20 . The device of claim 16 ,

wherein the decoded attribute value for the point is an attribute value of a correlated point, and wherein the attribute value of the correlated point is generated based on an attribute value of a parent node of the point in the octree, and

wherein the attribute distance is generated between the attribute value of the parent node of the point and an attribute value of the parent node of the closest neighbor point.