Symmetry Mesh Connectivity Coding for 3D Compression
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Solution Overview
Problem
Existing 3D mesh compression technologies face challenges in efficiently encoding dynamic meshes due to the large amount of data required, especially when dealing with reflection symmetry where one-to-one mapping is not available, leading to inefficiencies in storage and transmission.
Innovation Solution
A method is proposed to separate a polygon mesh into left and right side halves by a symmetry plane, remap faces to generate new vertices, compress the left side half mesh, predict the location of vertices on the right side using symmetry-based prediction, and connect the halves, utilizing codecs like Draco for efficient compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the entire polygon mesh is compressed using traditional codecs, then compression is achieved, but the data volume remains large due to lack of exploitation of symmetry properties
Solution Approach 1:
The polygon mesh is segmented into two halves by separating it along a symmetry plane. This segmentation allows each half to be encoded independently, exploiting the symmetry relationship between the two halves to reduce the overall data volume while maintaining the ability to reconstruct the complete mesh.
Solution Approach 2:
Instead of encoding the entire mesh, the method encodes one half of the mesh and uses symmetry-based prediction to generate the other half. This copying approach leverages the reflective symmetry property where one half is essentially a mirrored copy of the other, significantly reducing the amount of data that needs to be stored or transmitted.
2Productivity
If symmetry-based prediction is used to reduce data volume, then compression efficiency improves, but handling surfaces without one-to-one mapping becomes difficult
Solution Approach 1:
The method addresses the mapping difficulty by working with vertex indices in a transformed dimension space. Instead of directly mapping 3D surface points, the approach uses 2D face indices and vertex positions that can be systematically transformed and predicted, making the symmetry relationship more tractable even when perfect one-to-one mapping is not available.
Solution Approach 2:
The method changes the parameters being encoded from full 3D vertex coordinates to differential vertex positions and face indices. By encoding only the differences and using symmetry-based prediction for the base positions, the system achieves better compression efficiency while handling complex surface geometries that may not have perfect one-to-one symmetry mapping.
Data Source
AI summary
A method of encoding includes receiving a polygon mesh comprising a plurality of faces and a plurality vertices; separating the polygon mesh into a left side half mesh and a right side half mesh by a plane; extracting the left side half mesh comprising a first plurality of vertices in-plane and on a left side of the polygon mesh; remapping the plurality of faces to represent a new vertices order in order to generate a plurality of remapped faces; extracting the plurality of remapped faces; compressing the left side half mesh by a codec; predicting a location of a second plurality of vertices on the right side half mesh using a symmetry based prediction on the compressed left side half mesh; and connecting the left side half mesh and the right side half mesh.