Point Cloud Context Determination Using Laser Thresholds
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Solution Overview
Problem
Conventional techniques for determining contexts in arithmetic coding of syntax elements for point cloud compression, such as in Geometry-based Point Cloud Compression (G-PCC), are complex, leading to increased hardware costs and slower processing speeds.
Innovation Solution
The method involves determining a laser index and context index based on the intersection of a laser beam with a node in a point cloud octree, using thresholds to simplify the context determination process for encoding and decoding vertical plane and point position offsets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional techniques are used for determining contexts in arithmetic coding, then encoding accuracy is maintained, but device complexity and processing time increase
Solution Approach 1:
The patent changes the parameters for context determination by using simplified threshold-based rules instead of complex conventional techniques. Specifically, it determines context indices based on whether laser beam distances fall above a first threshold, between thresholds, or below a threshold, thereby reducing computational complexity while maintaining encoding accuracy.
2Measurement precision
If conventional techniques are used for determining contexts in arithmetic coding, then encoding accuracy is maintained, but processing speed decreases
Solution Approach 1:
The patent changes the computational parameters by replacing complex context determination algorithms with simple threshold comparisons. The processing speed is improved by using basic distance threshold checks (above first threshold, between thresholds, below threshold) instead of conventional complex techniques, while preserving encoding accuracy.
3Productivity
If simplified context determination is used, then processing speed improves, but encoding accuracy may deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where the context determination is based on feedback from laser beam distance measurements. The system continuously measures distances and uses threshold-based feedback to select appropriate context indices, ensuring that encoding accuracy is maintained while processing speed improves through simplified decision logic.
Data Source
AI summary
A method of decoding point cloud data comprises obtaining a bitstream that includes an arithmetically encoded syntax element indicating a vertical plane position of a planar mode of a node; and decoding the vertical plane position of the planar mode in the node, wherein decoding the vertical plane position of the planar mode comprises: determining a laser index of a laser candidate in a set of laser candidates, wherein the determined laser index indicates a laser beam that intersects the node; determining a context index based on whether the laser beam is above a first distance threshold, between the first distance threshold and a second distance threshold, between the second distance threshold and a third distance threshold, or below the third distance threshold; and arithmetically decoding the vertical plane position of the planar mode using a context indicated by the determined context index.