Node-based geometry and attribute coding for a point cloud
A method and apparatus for coding information of a point cloud may be performed by at least one processor and comprises: obtaining the point cloud including a set of points in a three-dimensional space; partitioning the point cloud into a tree structure comprising a plurality of nodes at different depths; encoding geometry information of the nodes; and encoding attribute information of the nodes before the entire point cloud is partitioned.
1. A method for decoding information of a point cloud, the method performed by at least one processor and comprising:
decoding attribute information of a plurality of nodes of the point cloud;
decoding geometry information of the plurality of nodes;
de-partitioning a tree structure of the point cloud at different depths; and
obtaining the point cloud including a set of points in a three-dimensional space,
receiving generated bitstreams for both of the geometry information and the attribute information of the plurality of nodes, and
wherein decoding of the geometry information of all of the nodes of the plurality of nodes of the point cloud begins prior to receipt of the entire generated bitstreams.
2. The method of claim 1 , wherein for each node at a given depth, of the plurality of nodes,
the attribute information of the nodes at the given depth is decoded before the geometry information of the nodes at the given depth is decoded; and
both the attribute information and the geometry information of the nodes at the given depth are decoded before attribute information and geometry information of nodes at a different depth are decoded.
3. The method of claim 1 , wherein the geometry information and the attribute information are alternatively and iteratively decoded.
4. The method of claim 1 , wherein at least one of the geometry information of the plurality of nodes and the attribute information of the plurality of nodes is decoded without considering respective geometry information and attribute information of neighboring nodes of the plurality of nodes.
5. The method of claim 1 , wherein at least one of the geometry information of the plurality of nodes and the attribute information of the plurality of nodes is decoded considering respective geometry information and attribute information of neighboring nodes of the plurality of nodes.
6. The method of claim 1 , further comprising determining a size of the plurality of nodes following de-partitioning the tree structure of the point cloud.
7. The method of claim 1 , wherein the geometry information of the plurality of nodes is decoded using at least one of the following methods: octree decoding with breadth-first traversal, octree decoding with depth-first traversal, predictive tree-based decoding, and tri-soup decoding.
8. The method of claim 1 , wherein the attribute information of the nodes is decoded using at least one of the following methods: prediction-based attribute decoding, lifting-based attribute decoding, and region-based adaptive hierarchical transform (RAHT) decoding.
9. The method of claim 1 , wherein at least one of the decoding of the geometry information and the decoding of the attribute information is signaled at a sequence level, frame level or slice level.
10. An apparatus for decoding 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 computer program code, the computer program code configured to cause the at least one processor to:
decode attribute information of a plurality of nodes of the point cloud;
decode geometry information of the plurality of nodes;
de-partition a tree structure of the point cloud at different depths; and
obtain the point cloud including a set of points in a three-dimensional space,
wherein the computer program code is configured to cause the at least one processor to:
receive generated bitstreams for both of the geometry information and the attribute information of the plurality of nodes; and
begin decoding of the geometry information of all of the nodes of the plurality of nodes of the point cloud prior to receipt of the entire generated bitstreams.
11. The apparatus of claim 10 , wherein the computer program code is configured to cause the at least one processor to, for each node at a given depth, of the plurality of nodes,
decode the attribute information of the nodes at the given depth before decoding the geometry information of the nodes at the given depth; and
decode both the attribute information and the geometry information of the nodes at the given depth before decoding attribute information and geometry information of nodes at a different depth.
12. The apparatus of claim 10 , wherein the computer program code is configured to cause the at least processor to alternatively and iteratively decode the geometry information and the attribute information.
13. The apparatus of claim 10 , wherein the computer program code is further configured to cause the at least one processor to decode the respective geometry information and attribute information without considering respective geometry information and attribute information of neighboring nodes of the plurality of nodes.
14. The apparatus of claim 10 , wherein the computer program code is further configured to cause the at least one processor to decode the respective geometry information and attribute information considering respective geometry information and attribute information of neighboring nodes of the plurality of nodes.
15. The apparatus of claim 10 , wherein the computer program code is further configured to cause the at least one processor to determine a size of the plurality of nodes following de-partitioning the tree structure of the point cloud.
16. The apparatus of claim 10 , wherein the computer program code is further configured to cause the at least one processor to decode the geometry information using at least one of the following methods: octree decoding with breadth-first traversal, octree decoding with depth-first traversal, predictive tree-based decoding, and tri-soup decoding.
17. The apparatus of claim 10 , wherein the computer program code is further configured to cause the at least one processor to decode the attribute information using at least one of the following methods: prediction-based attribute decoding, lifting-based attribute decoding, and region-based adaptive hierarchical transform (RAHT) decoding.
18. A non-transitory computer-readable storage medium storing instructions that cause at least one processor to decode information of a point cloud by:
decoding attribute information of a plurality of nodes of the point cloud;
decoding geometry information of the plurality of nodes;
de-partitioning the tree structure of the point cloud at different depths; and
obtaining the point cloud including a set of points in a three-dimensional space,
receiving generated bitstreams for both of the geometry information and the attribute information of the plurality of nodes, and
wherein decoding of the geometry information of all of the nodes of the plurality of nodes of the point cloud begins prior to receipt of the entire generated bitstreams.