Dynamic Point Cloud Attribute Coding With Joint Motion Search
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Solution Overview
Problem
Current G-PCC standard does not effectively utilize temporal prediction tools for dynamic point clouds, leading to inefficient compression.
Innovation Solution
An attribute inter-prediction framework using motion search criterion, proper reference, attribute projection, and in-loop filter, incorporating color distance into motion search to jointly estimate geometry and attribute motion, with methods like two-pass motion search and in-loop filtering to enhance compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If G-PCC standard uses only intra prediction for compressing dynamic point clouds, then the implementation is simple, but compression efficiency is poor
Solution Approach 1:
The patent introduces dynamic motion estimation and compensation mechanisms into G-PCC, transitioning from static intra-prediction to dynamic inter-prediction. Motion vectors are calculated between reference frames and current frames, enabling adaptive prediction that follows temporal changes in point cloud data, thereby improving compression efficiency for dynamic scenes.
Solution Approach 2:
The patent performs preliminary motion estimation by calculating motion vectors between reference frames and current frames before actual attribute coding. This preliminary action identifies temporal redundancies and establishes prediction modes, which are then used to guide the attribute coding process, reducing the amount of data that needs to be encoded.
2Productivity
If G-PCC extends to dynamic point clouds with inter-frame coding tools, then compression efficiency improves, but device complexity increases
Solution Approach 1:
The patent segments the attribute coding process into distinct phases: geometry-based motion estimation, attribute motion compensation, and residual coding. This segmentation allows each component to be optimized independently and facilitates selective implementation, reducing overall system complexity while maintaining compression efficiency.
Solution Approach 2:
The patent introduces motion vectors as intermediary elements that bridge reference frames and current frames. These motion vectors serve as mediators that carry temporal prediction information, enabling efficient inter-frame attribute coding without requiring direct comparison of all attribute values between frames.
3Measurement precision
If joint motion estimation using composed distance is used, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent changes the parameter used for motion estimation from pure geometry distance to a composed distance metric that incorporates both geometry and attribute information. This parameter change improves motion estimation accuracy by considering multiple aspects of point cloud data, but requires additional computations to calculate the composed distance.
Solution Approach 2:
The patent implements a two-pass motion estimation approach where the first pass uses simplified geometry-based estimation and the second pass refines it with attribute-based composed distance. This partial action strategy achieves high accuracy for critical regions while using less computational energy for less important areas.
Data Source
AI summary
An attribute inter-prediction framework using motion search criterion, proper reference, attribute projection and in-loop filter is described herein. An alternative motion estimation strategy incorporates color distance into the motion search criterion where geometry and attribute motion are jointly searched which leads to a single motion vector associated with each predicted block. The composed distance is the weighted sum of color and geometry distance. With the composed distance, two new types of search criterion are used to estimate the motion vectors: using the nearest neighbor composed distance, using the minimum composed distance based on the search of composed distances associated with each reference point within the search window. A dedicated attribute coding scheme using a two-pass motion search scheme, where the first pass is based on geometry only, and the second pass targets on eliminating temporal attribute redundancy. An in-loop filter can be applied to the projected attributes.