Mesh Attribute Prediction Switching for Non-Coplanar Face Angles
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Solution Overview
Problem
Existing polygon mesh compression methods using generalized parallelogram prediction are inaccurate when the 3D geometry positions of vertices are not in the same plane, leading to inefficiencies in attribute value prediction.
Innovation Solution
Adaptive switching between generalized parallelogram and linear parallelogram prediction modes based on the angle between faces in the mesh to determine a more accurate predictor for attribute values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generalized parallelogram prediction is used for attribute value prediction in mesh compression, then the prediction can be applied to various mesh configurations, but the prediction accuracy deteriorates when vertices are not in the same plane
Solution Approach 1:
The patent implements dynamic switching between generalized parallelogram prediction and linear parallelogram prediction based on the planarity of vertex configurations. The system adapts the prediction mode in real-time by evaluating geometric conditions (whether vertices lie on the same plane) to select the most appropriate prediction method, thereby maintaining both versatility and accuracy across different mesh scenarios
Solution Approach 2:
The patent changes the prediction mode parameter based on the geometric configuration of vertices. When vertices are determined to be coplanar, linear parallelogram prediction is applied; when they are not coplanar, generalized parallelogram prediction is used. This parameter switching resolves the contradiction by adapting the prediction approach to the specific geometric conditions
2Device complexity
If a single prediction mode is used for all mesh configurations, then the system complexity is reduced, but the prediction accuracy deteriorates for non-coplanar vertices
Solution Approach 1:
The patent segments the prediction space into two distinct regions: coplanar vertex configurations and non-coplanar vertex configurations. Each segment is handled by a specialized prediction mode optimized for its specific geometric characteristics, allowing high accuracy without requiring a single overly complex unified prediction system
3Measurement precision
If linear parallelogram prediction is used when vertices are coplanar, then the prediction accuracy is improved, but additional computational steps are required to determine coplanarity
Solution Approach 1:
The patent performs preliminary geometric analysis by calculating whether vertices are coplanar before applying the prediction mode. This preliminary action of determining spatial relationships allows the system to select the optimal prediction method in advance, ensuring high accuracy while managing complexity through structured pre-processing
Data Source
AI summary
A mesh coding method includes receiving a bitstream including coded information indicating that an attribute value of a current vertex in the mesh is predicted based on respective attribute values of a first vertex, a second vertex, and a third vertex in the mesh including a first face and a second face. The first face includes the first vertex, the second vertex, and the third vertex. The second face includes the first vertex, the second vertex, and the current vertex. A value is determined based on an angle between the first face and the second face. One of a plurality of prediction modes is determined based on the value. The plurality of the prediction modes includes a generalized parallelogram prediction mode and a linear parallelogram prediction mode. A predictor of the attribute value of the current vertex is determined based on the one of the plurality of prediction modes.