Mesh Displacement Vector Quantization Across Bit Depths
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Solution Overview
Problem
Existing mesh encoding techniques lack the ability to utilize many desirable scaling factors for large and small coefficients across different bit depths, and often lack a lossless scaling factor of 1.0, limiting flexibility in encoding and decoding meshes.
Innovation Solution
Incorporating a quantization parameter value and a bit depth offset value to enable more flexible scaling and inverse scaling across different bit depths and coefficient values, allowing for improved encoding and decoding of meshes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing techniques for scaling coefficients are used, then the encoding process is simpler, but the flexibility in determining scaling factors is limited and a lossless scaling factor of 1.0 is not available
Solution Approach 1:
The scaling process is divided into two separate parameters: a base scaling factor determined from the quantization parameter, and an additional scaling factor determined from the bit depth offset value. This segmentation allows independent control of scaling behavior for different bit depths and coefficient ranges, providing flexibility while maintaining a systematic encoding process.
Solution Approach 2:
The patent introduces a new parameter (bit depth offset value) that modifies the scaling behavior. By changing this parameter, the system can adapt the scaling factor to different bit depths and coefficient magnitudes, enabling lossless scaling when needed and flexible adaptation to various encoding conditions without fundamentally changing the encoding architecture.
2Measurement precision
If more bits are used to signal displacement vectors, then the precision of mesh representation is improved, but the data transmission and storage requirements increase
Solution Approach 1:
Different scaling factors are applied based on local conditions: the bit depth offset value allows the system to select appropriate scaling for different bit depths and coefficient ranges. This enables precise representation where needed (larger coefficients at high bit depths, small coefficients at low bit depths) while using fewer bits where possible, optimizing the balance between precision and data quantity.
Solution Approach 2:
By introducing the bit depth offset value parameter, the system dynamically adjusts the scaling factor to match the required precision for different coefficient magnitudes and bit depths. This parameter change enables efficient bit allocation that adapts to the actual needs of the mesh data being encoded.
Data Source
AI summary
A device for decoding encoded mesh data can be configured to determine, based on the encoded mesh data, a base mesh; determine, based on the encoded mesh data, a set of coefficients; receive in the encoded mesh data a quantization parameter value; receive in the encoded mesh data a bit depth offset value; determine an inverse scaling factor based on the quantization parameter value and the bit depth offset value; perform an inverse scaling on the set of coefficients based on the inverse scaling factor to determine a set of de-quantized coefficients; determine a displacement vector based on the set of de-quantized coefficients; deform the base mesh based on the displacement vector to determine a decoded mesh; and output the decoded mesh.