Temporal Vertex Position Compression Using Neighbor Error Prediction
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Solution Overview
Problem
Existing mesh compression standards struggle to efficiently handle dynamic meshes with time-varying connectivity and attribute maps, particularly under real-time constraints, and do not support constant connectivity dynamic meshes effectively.
Innovation Solution
A method for mesh processing that involves determining neighboring vertices, calculating estimation errors, and using temporal prediction to generate prediction residues for vertex position compression, utilizing an Edgebreaker algorithm for ordering and inter-frame prediction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing mesh compression standards are used, then mesh data can be compressed, but they struggle to efficiently handle dynamic meshes with time-varying connectivity and attribute maps under real-time constraints
Solution Approach 1:
The patent segments the mesh processing into distinct components: vertex position data, attribute map data, and connectivity information. By separating these elements and applying specialized compression techniques to each, the system achieves efficient handling of dynamic meshes while reducing overall processing complexity.
Solution Approach 2:
The patent implements dynamic prediction techniques that adapt to time-varying mesh characteristics. The prediction residue calculation dynamically adjusts based on neighboring vertex estimation errors, enabling efficient compression of dynamic meshes with changing connectivity and attribute maps across different time instances.
2Manufacturing precision
If more detailed mesh data is transmitted to achieve realism, then immersive experience quality improves, but data transmission requirements increase
Solution Approach 1:
The patent employs feedback mechanisms where prediction residues are calculated based on neighboring vertex estimation errors. This feedback loop allows the system to transmit only the necessary correction data rather than complete mesh information, maintaining high precision while reducing data volume for realistic immersive experiences.
Solution Approach 2:
The patent transforms the mesh data representation by changing from absolute vertex positions to prediction residues relative to reference frames. This parameter transformation enables high-fidelity mesh reconstruction from compressed data, achieving detailed realism with reduced transmission requirements.
3Productivity
If temporal prediction based on neighboring vertices is used, then vertex position compression efficiency improves, but calculation complexity increases
Solution Approach 1:
The patent performs preliminary ordering of neighboring vertices using the Edgebreaker algorithm before compression. This preliminary organization of vertex data structures enables more efficient prediction calculations by establishing a systematic traversal order, improving compression rates while managing calculation complexity through structured preprocessing.
Data Source
AI summary
A plurality of neighboring vertices of a current vertex in a current frame of a mesh is determined. The current frame corresponds to the mesh at a first time instance. Each of the plurality of neighboring vertices is connected to the current vertex through a respective edge in the mesh. A plurality of neighboring estimation errors of the plurality of neighboring vertices is determined. Each of the plurality of neighboring estimation errors indicates a difference between a reference vertex of a corresponding one of the plurality of neighboring vertices in a reference frame and the corresponding one of the plurality of neighboring vertices in the current frame. The reference frame corresponds to the mesh at a second time instance. A prediction residue of the current vertex is determined based on the plurality of neighboring estimation errors. Prediction information of the current vertex is generated based on the determined prediction residue.