Adaptive Linear Wavelet Mesh Coding for Dynamic Mesh Fidelity
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Solution Overview
Problem
Existing 3D mesh compression technologies are inefficient in managing the large data requirements of dynamic meshes, leading to suboptimal storage and transmission of immersive media.
Innovation Solution
Implementing an adaptive linear wavelet transform with varying weight values for neighboring vertices in mesh processing, using a syntax element to indicate the transform's use and applying different weights based on vertex distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional wavelet transform is used for mesh compression, then compression is achieved, but compression efficiency and fidelity are insufficient for dynamic meshes
Solution Approach 1:
The patent applies dynamics by making the wavelet transform adaptive to the local mesh geometry. The transform dynamically adjusts its parameters based on the actual vertex distribution and surface characteristics at each location, allowing the compression algorithm to adapt to the varying complexity of dynamic mesh surfaces rather than using fixed transform parameters throughout.
Solution Approach 2:
The patent implements local quality by applying different wavelet transform parameters to different regions of the mesh. Specifically, the transform uses locally adapted basis functions that match the local surface curvature and vertex density, ensuring high fidelity in complex regions while maintaining compression efficiency in simpler areas.
2Ease of operation
If uniform weight values are applied to all neighboring vertices, then processing simplicity is maintained, but reconstruction accuracy deteriorates
Solution Approach 1:
The patent applies local quality by assigning different weight values to neighboring vertices based on their individual characteristics and positions. The weight for each neighbor is determined by factors such as distance to the central vertex, local surface curvature, and vertex degree, allowing the reconstruction process to account for local geometric variations while maintaining a relatively simple computational framework.
3Measurement precision
If large data volume is used for dynamic meshes, then representation quality is maintained, but storage and transmission costs increase
Solution Approach 1:
The patent applies parameter changes by transforming the mesh data into a different parameter space using the adaptive wavelet transform. This transformation reorganizes the data to separate significant features from redundant information, allowing high-quality representation to be achieved with fewer parameters. The transform parameters themselves are adapted locally to maximize compression efficiency while preserving essential mesh characteristics.
Data Source
AI summary
An aspect of the disclosure provides a method of mesh decoding. For example, a bitstream that includes coded information of a mesh frame is received. A syntax element is parsed from the bitstream, the syntax element indicates whether an adaptive linear wavelet transform is used, the adaptive linear wavelet transform applies different weight values to different neighboring vertices of a vertex in a wavelet transform of attribute values associated with vertices of the mesh frame. When the syntax element indicates a use of the adaptive linear wavelet transform, at least a first vertex in the vertices of the mesh frame is reconstructed according to the adaptive linear wavelet transform.