Middle Point Position Coding for Dynamic 3D Mesh Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing 3D mesh compression standards do not effectively handle dynamic meshes with time-varying connectivity information and attribute maps, particularly challenging for real-time applications and volumetric acquisition techniques.
Innovation Solution
A method involving partitioning mesh vertices into groups, encoding volumetric data by deriving a residual vector based on forward prediction from a middle point, and implementing symmetry encoding with dummy vertices and dual traversal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing 3D mesh compression standards are used, then connectivity information can be compressed, but they cannot handle dynamic meshes with time-varying connectivity information and attribute maps
Solution Approach 1:
The patent introduces dynamic mesh representation where connectivity information can change over time, allowing the mesh structure to adapt to time-varying geometries. This is achieved through time-dependent connectivity matrices and dynamic vertex indexing that enable the mesh to represent moving deformable objects effectively.
Solution Approach 2:
The patent segments the mesh into multiple patches or elements, each with its own connectivity information. This segmentation allows independent handling of different mesh regions, enabling time-varying connectivity changes in specific areas without affecting the entire mesh structure.
2Loss of information
If vertex position data is encoded for all vertices, then complete mesh information is preserved, but data volume becomes excessively large
Solution Approach 1:
The patent transforms vertex position encoding by changing the parameter representation from absolute coordinates to relative offsets or differences. This parameter transformation reduces the bit depth required for each vertex position while maintaining the essential geometric information, thereby reducing overall data volume.
Solution Approach 2:
The patent applies partial encoding strategies where not all vertex positions are fully encoded with maximum precision. Instead, selective encoding is used based on vertex importance, curvature, or other geometric features, encoding only the necessary precision for each vertex to maintain visual quality while reducing data volume.
Data Source
AI summary
A method and apparatus comprising computer code configured to cause a processor or processors to obtain a mesh representing volumetric data of at least one three-dimensional (3D) visual content, partition a plurality of vertices of the mesh into a plurality of groups, and encode the volumetric data based on encoding a middle point of an edge of at least one of the groups and then at least one of deriving a residual vector, based on forward prediction at least one of the vertices based on the middle point, and symmetry encoding.