Vertex Correction for Rotated 3D Components
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Solution Overview
Problem
Existing 3D model compression methods face inefficiencies due to inconsistent reconstruction quality caused by rotation quantization errors, particularly affecting larger instances with varying vertex coordinate errors, leading to unnecessary precision in encoding and decoding.
Innovation Solution
Adaptive quantization of rotation information based on instance size and vertex distance from the rotation center, allowing for precise reconstruction by encoding only necessary vertex coordinate errors, thereby optimizing bitstream generation and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If uniform quantization precision is used for all instances, then encoding complexity is reduced, but reconstruction quality becomes inconsistent across instances of different sizes
Solution Approach 1:
The patent applies local quality by using different quantization precisions for different instances based on their sizes. Larger instances use finer quantization precision while smaller instances use coarser precision, allowing each instance to be encoded with appropriate quality rather than applying uniform precision to all instances.
Solution Approach 2:
The patent implements dynamic quantization precision adjustment based on instance characteristics. The quantization precision is adapted dynamically according to the size of each instance, enabling the encoding system to optimize between compression efficiency and reconstruction quality for each specific instance.
2Measurement precision
If high quantization precision is used for all vertices, then reconstruction accuracy is improved, but compression efficiency deteriorates due to encoding unnecessary precision
Solution Approach 1:
The patent applies local quality by determining quantization precision based on the distance of each vertex from the rotation center. Vertices farther from the rotation center use finer quantization precision while vertices closer to the center use coarser precision, encoding only the necessary precision for each vertex location.
Solution Approach 2:
The patent implements partial action by applying high quantization precision only where necessary (for vertices farther from the rotation center) and using coarser precision where it is sufficient (for vertices closer to the center), avoiding the encoding of unnecessary precision information.
3Productivity
If adaptive quantization based on vertex distance is implemented, then compression efficiency is improved, but encoding complexity increases
Solution Approach 1:
The patent applies preliminary action by calculating the distance of each vertex from the rotation center before the quantization process. This pre-calculation allows the system to determine the appropriate quantization precision for each vertex in advance, simplifying the subsequent encoding process rather than increasing complexity.
Data Source
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AI summary
A 3D model can be modeled using pattern-instance representation, wherein an instance component may be represented as transformation (for example, rotation, translation, and scaling) of a pattern. Quantization errors may be introduced when encoding rotation information, causing different vertex coordinate errors at different vertices of an instance. To efficiently compensate the vertex coordinate errors, an upper bound can be estimated for the vertex coordinate error of a vertex. Based on the upper bound, the codec decides whether the vertex coordinate error of the vertex needs to be compensated, and decides a quantization parameter for compensating the vertex coordinate error if compensation is needed. The upper bound can be estimated at both the encoder and decoder, and thus, no explicit signaling is needed to indicate whether vertex coordinate error compensation is used or to indicate the quantization parameter for the vertex coordinate error.