Adaptive Mesh Geometry Filtering for Dynamic Connectivity Compression
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Solution Overview
Problem
Existing mesh compression standards fail to efficiently handle dynamic meshes with time varying connectivity and attribute maps, particularly under real-time constraints, leading to degraded visual quality due to artifacts in reconstructed meshes.
Innovation Solution
Implement adaptive geometry filtering by grouping vertices based on topological distance and applying filtering coefficients to refine the reconstructed mesh, using methods like Adaptive Laplacian and Wiener filters to minimize error functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mesh compression standards (IC, MESHGRID, FAMC) are used for dynamic meshes, then compression is achieved for constant connectivity meshes, but they fail to handle time-varying connectivity information and attribute maps effectively
Solution Approach 1:
The patent applies dynamics by making the connectivity information time-varying rather than constant. The mesh structure allows connectivity to change over time, enabling the representation of dynamic meshes where topology evolves, thus resolving the limitation of existing standards that assume fixed connectivity.
Solution Approach 2:
The patent changes parameters by introducing time-varying connectivity information and attribute maps as dynamic parameters. Instead of treating connectivity as a fixed parameter, the system allows it to vary with time, enabling more flexible and accurate representation of dynamic mesh structures.
2Speed
If volumetric acquisition techniques are used under real-time constraints, then real-time processing is achieved, but constant connectivity dynamic mesh generation becomes challenging
Solution Approach 1:
The patent applies preliminary action by pre-defining the mesh structure and connectivity patterns that can adapt to time-varying conditions. Rather than generating complex connectivity in real-time, the system prepares a framework that naturally accommodates dynamic changes, reducing the computational complexity during real-time operation.
3Quantity of substance
If existing mesh compression standards are used, then compression is achieved, but data inefficiencies occur for dynamic meshes with time-varying geometry and attributes
Solution Approach 1:
The patent applies segmentation by dividing the mesh data into distinct components: geometry information, connectivity information, and attribute maps. Each component is encoded separately with appropriate compression techniques, allowing efficient representation of time-varying attributes while maintaining overall data compression.
4Quantity of substance
If glTF with Draco technology is used, then 3D asset size is reduced, but runtime processing and unpacking overhead remains significant
Solution Approach 1:
The patent changes parameters by optimizing the balance between compression ratio and decompression speed. By adjusting encoding parameters and using more efficient data structures for time-varying mesh data, the system reduces both file size and runtime processing requirements compared to existing solutions.
Data Source
AI summary
A method and apparatus comprising computer code configured to cause a processor or processors to determine more than one vertices in an input mesh, and group the more than one vertices in more than one group of vertices. The grouping of a respective vertex in a respective group may be based on a topological distance of the respective vertex. In embodiments, the processor or processors may also determine a set of filter coefficients for the more than one group of vertices; and signal the more than one group of vertices and the set of filter coefficients.