Dynamic Mesh Compression With Static-Motion Path Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing mesh compression techniques do not effectively consider the impact of geometrical and attribute data encoding on overall distortion and bitrate, leading to inefficient compression of dynamic meshes.
Innovation Solution
A multipath encoding approach that optimizes rate-distortion cost functions by considering both geometrical and textural distortions, using a static path and a motion path, to select the most efficient encoding method for mesh data, including base mesh, displacement vectors, and attribute maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If direct encoding of geometrical data is used, then encoding simplicity is improved, but overall mesh compression efficiency deteriorates due to increased distortion
Solution Approach 1:
The patent implements dynamic path selection between static and motion encoding approaches based on rate-distortion optimization. The encoder adapts its encoding strategy frame-by-frame or group-of-pictures-by-group-of-pictures, switching between direct encoding and motion-compensated encoding depending on which path yields lower distortion for the given bitrate constraint.
Solution Approach 2:
The patent changes the encoding parameters dynamically by selecting different encoding paths (static vs. motion) and adjusting motion vector precision, reference frame selection, and quantization parameters based on the optimized rate-distortion cost function, thereby improving compression efficiency without excessive complexity.
2Loss of information
If motion path encoding is used, then compression efficiency is improved, but computational complexity increases due to multiple encoding paths
Solution Approach 1:
The patent segments the encoding process into distinct static and motion paths, each handling specific types of mesh data with appropriate techniques. The static path handles frames better encoded with direct methods, while the motion path handles frames benefiting from temporal prediction, reducing overall computational complexity compared to applying motion compensation to all frames.
Solution Approach 2:
The patent applies motion compensation only partially - only to frames where rate-distortion optimization determines it provides sufficient benefit. This avoids the excessive computational cost of motion encoding for all frames while still achieving improved compression efficiency where needed.
3Manufacturing precision
If relative encoding of geometrical data is used, then distortion is reduced, but encoding complexity increases due to reference mesh requirements
Solution Approach 1:
The patent dynamically selects between direct and relative encoding based on rate-distortion optimization. When relative encoding provides sufficient distortion reduction for the given bitrate, it is selected; otherwise, direct encoding is used. This adaptive approach balances distortion reduction benefits against the increased encoding complexity of maintaining and using reference meshes.
Data Source
AI summary
Apparatuses and methods are disclosed for encoding mesh data. Techniques disclosed include receiving a sequence of frames, each of which includes mesh data. For a frame in the sequence, techniques disclosed for encoding the mesh data of the frame according to a static path and according to a motion path of a multipath encoder, computing a static path cost of the encoding according to the static path and a motion path cost of the encoding according to the motion path, where the costs are computed by optimizing a rate-distortion cost function, and selecting, based on the computed motion path cost and static path cost, a bitstream generated by the encoding according to the motion path or a bitstream generated by the encoding according to the static path.