Context modeling of occupancy coding for point cloud coding

1. A method for coding information of a point cloud, the method performed by at least one processor and comprising:

obtaining the point cloud including a set of points in a three-dimensional space;

partitioning the point cloud into a plurality of objects and generating occupancy information for each of the plurality of objects; and

encoding the occupancy information by taking into account a distance between the plurality of objects,

wherein the occupancy information is encoded using a context index defined by a look-up-table using the formula: LUT{ctxIdx}{ctxIdxChild}, wherein LUT is the look-up-table, ctxIdx is a node of the plurality of objects, and ctxIdxChild is a sub-node of the plurality of objects.

2. The method of claim 1 , wherein the encoding of the occupancy information is performed on an object-by-object basis such that a next piece of occupancy information to be encoded is encoded based on a classification of surrounding objects of the plurality of objects, which are classified based on the distance between the plurality of objects.

3. The method of claim 1 , wherein the partitioning of the point cloud uses flexible tree partitioning.

4. The method of claim 3 , wherein the plurality of objects includes objects of different sizes.

5. The method of claim 1 , wherein the partitioning of the point cloud uses a depth-first partitioning scheme.

6. The method of claim 4 , wherein the encoding of the occupancy information takes into account the different sizes of the objects of the plurality of objects.

7. The method of claim 1 , wherein the encoding of the occupancy information is performed on an object-by-object basis such that a next piece of occupancy information to be encoded is encoded based on a classification of surrounding objects, of the plurality of objects, which are already encoded, and which are classified based on the distance between the plurality of objects.

8. The method of claim 1 , wherein the encoding of the occupancy information is performed on an object-by-object basis such that a next piece of occupancy information to be encoded is encoded based on a classification of surrounding objects, of the plurality of objects, at least some of which have been already encoded or partially encoded, and which are classified based on the distance between the plurality of objects.

9. An apparatus for coding information of a point cloud, the apparatus comprising:

at least one memory configured to store program code; and

at least one processor configured to access the at least one memory and operate according to the program code, the program code comprising:

obtaining code configured to obtain the point cloud including a set of points in a three-dimensional space;

partitioning code configured to partition the point cloud into a plurality of objects and generate occupancy information for each of the plurality of objects; and

encoding code configured to encode the occupancy information by taking into account a distance between the plurality of objects,

wherein the encoding code is configured to encode the occupancy information using a context index defined by a look-up-table using the formula: LUT{ctxIdx}{ctxIdxChild}, wherein LUT is the look-up-table ctxIdx is a node of the plurality of objects, and ctxIdxChild is a sub-node of the plurality of objects.

10. The apparatus of claim 9 , wherein the encoding code is configured to encode the occupancy information on an object-by-object basis such that a next piece of occupancy information to be encoded is encoded based on a classification of surrounding objects of the plurality of objects, which are classified based on the distance between the plurality of objects.

11. The apparatus of claim 9 , wherein the partitioning code is configured to partition the point cloud using flexible tree partitioning.

12. The apparatus of claim 11 , wherein the plurality of objects includes objects of different sizes.

13. The apparatus of claim 9 , wherein the partitioning code is configured to partition the point cloud using a depth-first partitioning scheme.

14. The apparatus of claim 12 , wherein the encoding code is configured to encode the occupancy information by taking into account the different sizes of the objects of the plurality of objects.

15. The apparatus of claim 9 , wherein the encoding code is configured to encode the occupancy information on an object-by-object basis such that a next piece of occupancy information to be encoded is encoded based on a classification of surrounding objects, of the plurality of objects, which are already encoded, and which are classified based on the distance between the plurality of objects.

16. A non-transitory computer-readable storage medium storing instructions that cause at least one processor to:

obtain a point cloud including a set of points in a three-dimensional space;

partition the point cloud into a plurality of objects and generating occupancy information for each of the plurality of objects; and

encode the occupancy information by taking into account a distance between the plurality of objects

wherein the occupancy information is encoded using a context index defined by a look-up-table using the formula: LUT{ctxIdx} {ctxIdxChild}, wherein LUT is the look-up-table, ctxIdx is a node of the plurality of objects, and ctxIdxChild is a sub-node of the plurality of objects.