Point Cloud Position Coding With Interleaved Octree Trisoup Data
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Solution Overview
Problem
Existing point cloud compression methods, such as G-PCC and V-PCC, face challenges in efficiently compressing dense point clouds with complex geometry, leading to high latency and inefficient bitstream transmission, particularly when using a single transmission channel.
Innovation Solution
The method interleaves occupancy and Trisoup information within a data unit to reduce transmission latency by encoding and decoding occupancy and Trisoup information alternately, allowing simultaneous transmission over a single channel without introducing delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If occupancy and Trisoup information are transmitted sequentially over a single channel, then transmission simplicity is maintained, but transmission latency increases
Solution Approach 1:
The bitstream is segmented into multiple data units, each containing both occupancy information and Trisoup information for different subsets of cuboid volumes. This segmentation allows parallel processing and interleaved transmission of different information types, reducing overall transmission latency while maintaining manageable complexity through structured organization.
Solution Approach 2:
The encoding and decoding process uses periodic action by alternating between encoding occupancy information and Trisoup information in an interleaved manner across different data units. This periodic interleaving allows the single transmission channel to efficiently carry both information types without excessive latency, as the pattern repeats systematically across the bitstream.
2Productivity
If occupancy information is fully encoded before Trisoup information, then decoding dependency is simplified, but overall encoding time increases
Solution Approach 1:
The point cloud data is divided into multiple subsets of cuboid volumes, with each subset processed independently in separate data units. This segmentation allows the encoder to interleave occupancy and Trisoup information encoding across different subsets, improving encoding throughput by utilizing parallel processing capabilities while keeping individual data unit complexity manageable.
Solution Approach 2:
The encoder performs preliminary organization of cuboid volumes into subsets and prepares encoding schedules before actual encoding begins. This preliminary action enables the interleaved encoding of occupancy and Trisoup information to proceed efficiently, as the structure and dependencies are pre-established, reducing overall encoding time without unduly complicating the decoding process.
3Productivity
If all cuboid volumes are processed in sequence, then processing simplicity is maintained, but compression throughput decreases
Solution Approach 1:
Cuboid volumes are segmented into multiple subsets, with each subset assigned to a separate data unit containing both occupancy and Trisoup information. This segmentation enables parallel processing of different subsets, significantly improving compression throughput while maintaining reasonable data unit structure complexity through systematic organization and clear boundaries between subsets.
Data Source
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AI summary
There is provided methods and apparatus of encoding/decoding, into/from a bitstream comprising at least one data unit, position information of points of a point cloud. Said points are comprised in cuboid volumes associated with leaf nodes of an octree structure. The method comprises encoding occupancy information of nodes of the octree structure, said occupancy information being representative of presence of points of the point cloud comprised in said cuboid volumes and for each current cuboid volume comprising at least one point of the point cloud, encoding Trisoup information representative of presence of vertices on edges of the current cuboid volume, and vertices positions along said edges. According to the present invention, occupancy information of a leaf node and Trisoup information of another leaf node are encoded in the data unit in an interleaved way.