Parallel Octree Coding for Point Cloud Compression
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Solution Overview
Problem
Existing point cloud compression technologies face inefficiencies in data transmission and storage due to the large volume of data required to represent 3D scenes, particularly in applications like autonomous driving and geographic information systems, where sequential octree coding processes are slow and dependent on previous node statuses.
Innovation Solution
The implementation of parallel octree coding, which allows for simultaneous encoding and decoding of certain octree partition depths, reducing dependency on previous node statuses and accelerating the coding process by signaling control parameters and bitstream offsets in the syntax information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sequential octree coding is used, then the coding process is simple to implement, but the encoding and decoding times are slow
Solution Approach 1:
The patent segments the octree coding process by introducing syntax information that divides the bounding box into multiple depth ranges. Each range can be independently decoded in parallel, transforming a single sequential process into multiple concurrent segments. This segmentation enables parallel processing while maintaining the hierarchical structure of octree coding.
Solution Approach 2:
The patent performs preliminary action by encoding and signaling syntax information about the octree partitioning structure before actual decoding begins. This includes pre-defining depth ranges and bitstream offsets, allowing the decoder to prepare multiple decoding streams in advance and execute them simultaneously without waiting for sequential completion of previous depths.
2Productivity
If parallel decoding is performed on occupancy codes, then the coding efficiency is improved, but the syntax information and control parameters increase
Solution Approach 1:
The patent applies partial action by selectively enabling parallel decoding only for specific depth ranges within the octree structure, rather than forcing parallel processing across all depths. The syntax information allows the decoder to choose which depth ranges to process in parallel based on available resources and requirements, avoiding the overhead of managing complete parallelism throughout the entire tree.
3Productivity
If parallel decoding is performed, then the dependency on previous node statuses is reduced, but the bitstream structure becomes more complex
Solution Approach 1:
The patent introduces syntax information as an intermediary layer between the compressed bitstream and the octree decoding process. This syntax information contains pre-encoded partitioning structures and bitstream offset information that mediate the complex parallel decoding requirements, allowing multiple decoders to independently access and process different depth ranges without direct dependency on each other's processing state.
Data Source
AI summary
Aspects of the disclosure provide methods, apparatuses, and a non-transitory computer-readable medium for point cloud coding. In a method, when parallel octree coding is enabled for occupancy codes of nodes in an octree partitioning structure of the point cloud, syntax information of the point cloud is decoded from a coded bitstream and a bitstream offset of an octree depth is determined. The syntax information indicates a bitstream length of the octree depth at which the parallel octree coding is enabled. Parallel decoding is performed on the occupancy codes of the nodes of the octree depth based on the bitstream offset and the bitstream length of the octree depth. Further, the point cloud is reconstructed based on the occupancy codes of the nodes.