Flexible tree partition and representation for point cloud coding
A method of decoding encoded information of a point cloud may be performed by at least one processor and comprises: obtaining an encoded bitstream, the encoded bitstream including encoded information of a point cloud including a set of points in a three-dimensional space; and determining a type of partitioning used to encode the information of the point cloud by at least one of parsing signals of at least three binary syntaxes or inferring at least one syntax of the at least three binary syntaxes.
1. A method of compressing information of a point cloud, the method performed by at least one processor and comprising:
obtaining data of a point cloud including a set of points in a three-dimensional space;
partitioning the data using flexible tree partitioning and applying at least one of symmetric partitioning, asymmetric partitioning, and hybrid partitioning; and
encoding the flexible tree partitioning by representing splitting and occupancy information thereof in binary form.
2. The method of claim 1 , wherein the encoding the flexible tree partitioning includes representing the splitting and occupancy information using three binary syntaxes.
3. The method of claim 1 , wherein a type of partitioning applied using the flexible tree partitioning depends upon a node size.
4. The method of claim 1 , wherein when the partitioning of the data using the flexible tree partitioning includes applying the symmetric partitioning, and the symmetric partitioning includes partitioning applied to a cubic node, octree symmetric partitioning is applied.
5. The method of claim 1 , wherein the partitioning of the data using the flexible tree partitioning includes applying the asymmetric partitioning when at least one of the following conditions are met: a node size is below a threshold size or a specific partitioning depth is reached.
6. The method of claim 1 , wherein when the partitioning of the data using the flexible tree partitioning includes applying the hybrid partitioning, signaling of the hybrid partitioning is unified by a single look-up table.
7. The method of claim 1 , wherein when the partitioning of the data using the flexible tree partitioning includes applying the symmetric partitioning, identical splitting syntaxes are applied to a current node, child nodes of the current node, grandchild nodes of the current node, and leaf nodes of the current node.
8. The method of claim 1 , wherein the partitioning of the data using the flexible tree partitioning includes applying the asymmetric partitioning when a node is cubic.
9. The method of claim 1 , wherein when the partitioning of the data using the flexible tree partitioning includes applying the hybrid partitioning, identical splitting syntaxes are applied to a current node, child nodes of the current node, grandchild nodes of the current node, and leaf nodes of the current node.
10. The method of claim 1 , wherein the partitioning of the data using the flexible tree partitioning includes applying the at least one of the symmetric partitioning, the asymmetric partitioning, and the hybrid partitioning according to the following formula:
p
^
=
arg
min
p
{
D
(
p
)
+
λ
·
R
(
p
)
}
wherein p indicates a tree partition mode, D(p) is a distortion function, R(p) is a rate function, λ is a Laplacian coefficient, and {circumflex over (p)} is a tree partition mode.
11. An apparatus for compressing 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 data of a point cloud including a set of points in a three-dimensional space;
partitioning code configured to partition the data using flexible tree partitioning and apply at least one of symmetric partitioning, asymmetric partitioning, and hybrid partitioning; and
encoding code configured to encode the flexible tree partitioning by representing splitting and occupancy information thereof in binary form.
12. The apparatus of claim 11 , wherein the encoding code is configured to encode the flexible tree partitioning by representing the splitting and occupancy information using three binary syntaxes.
13. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning and apply the at least one of the symmetric partitioning, the asymmetric partitioning, and the hybrid partitioning depending upon a node size.
14. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning by applying the symmetric partitioning such that octree symmetric partitioning is applied to a cubic node.
15. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning by applying the asymmetric partitioning when at least one of the following conditions are met: a node size is below a threshold size or a specific partitioning depth is reached.
16. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning by applying the hybrid partitioning such that signaling of the hybrid partitioning is unified by a single look-up table.
17. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning by applying the symmetric partitioning such that identical splitting syntaxes are applied to a current node, child nodes of the current node, grandchild nodes of the current node, and leaf nodes of the current node.
18. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning by applying the asymmetric partitioning when a node is cubic.
19. The apparatus of claim 11 , wherein the partitioning code is configured to partition the data using the flexible tree partitioning by applying the at least one of the symmetric partitioning, the asymmetric partitioning, and the hybrid partitioning according to the following formula:
p
^
=
arg
min
p
{
D
(
p
)
+
λ
·
R
(
p
)
}
wherein p indicates a tree partition mode, D(p) is a distortion function, R(p) is a rate function, λ is a Laplacian coefficient, and {circumflex over (p)} is a tree partition mode.
20. A non-transitory computer-readable storage medium storing instructions that cause at least one processor to:
obtain data of a point cloud including a set of points in a three-dimensional space;
partition the data using flexible tree partitioning and applying at least one of symmetric partitioning, asymmetric partitioning, and hybrid partitioning; and
encode the flexible tree partitioning by representing splitting and occupancy information thereof in binary form.