G-PCC Planar Mode Inter Prediction Context Coding
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Solution Overview
Problem
Existing point cloud compression technologies face challenges in efficiently encoding and decoding point cloud data, particularly in utilizing the geometry information of reference blocks to improve coding performance.
Innovation Solution
The proposed solution involves a Geometry Point Cloud Compression (G-PCC) coder that obtains planar information from a reference block, determines a context based on this information, and uses context-adaptive coding to encode syntax elements indicating whether a current node is coded using a planar mode, thereby improving coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inter prediction using motion compensation is applied to derive reference blocks, then the correlation in geometry structure between current node and reference node is improved, but the complexity of the coding process increases due to additional motion estimation and context determination steps
Solution Approach 1:
The patent applies preliminary action by pre-determining motion information and deriving reference blocks before actual coding operations. Motion compensation is performed in advance to create reference blocks that capture geometry correlations, allowing the coding process to leverage these pre-computed relationships without adding complexity during the main encoding/decoding phases.
Solution Approach 2:
The patent introduces an intermediary mechanism through context determination that mediates between the reference block and current node coding. The context acts as an intermediate representation that captures the correlation information from reference blocks, enabling efficient transmission of geometric relationships without directly transmitting all reference block data.
2Productivity
If planar information from reference blocks is used to determine coding contexts, then the compression efficiency is improved through better prediction, but the computational overhead increases due to additional information processing
Solution Approach 1:
The patent applies the extraction principle by selectively taking out only the essential planar information from reference blocks that is needed for context determination. Instead of processing all reference block data, the method extracts specific geometric characteristics (planar flags, plane indices) that are sufficient for improving compression efficiency while minimizing computational overhead.
Solution Approach 2:
The patent implements partial action by applying planar mode coding only to nodes where it provides significant benefit, rather than uniformly applying it to all nodes. The context-adaptive approach allows the encoder to selectively use planar information from reference blocks based on local geometry characteristics, achieving good compression efficiency without the full computational cost of processing every node with the same level of detail.
Data Source
AI summary
An example device for processing a point cloud includes: a memory configured to store at least a portion of the point cloud; and one or more processors implemented in circuitry and configured to: obtain planar information of a reference block of the point cloud; determine, based on the planar information of the reference block, a context; context-adaptive code, based on the context, a syntax element that indicates whether a current node is coded using a planar mode; code, based on the current node being coded using the planar mode, the current node using the planar mode.