3D Model Visual Optimization via Selective Decimation
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Solution Overview
Problem
Current computer-aided design (CAD) systems face challenges in optimizing three-dimensional models for efficient rendering, requiring significant time and subjective expertise to reduce complexity while maintaining visual quality, often resulting in poorly optimized models that omit necessary details or include superfluous information.
Innovation Solution
A method and system for visual optimization of 3D models that selectively adjusts node parameters to reduce rendering complexity, using quantitative analytics and graphical user interfaces (GUIs) to identify and decimate areas of complexity, allowing for efficient rendering while maintaining visual quality, bound by frame rate thresholds or user-defined visual quality levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the three dimensional model is rendered at high complexity level to preserve visual detail, then the visual quality is improved, but the frame rate decreases and rendering efficiency worsens
Solution Approach 1:
The patent applies local quality by differentiating between critical and non-critical areas of the 3D model. Critical areas maintain high geometric fidelity and visual detail, while non-critical areas are decimated to lower complexity. This selective approach preserves visual quality where needed while improving overall rendering efficiency by reducing complexity in less important regions.
Solution Approach 2:
The patent segments the 3D model into distinct critical and non-critical areas based on visual importance. This segmentation allows independent optimization of each region, enabling the system to maintain high visual quality in critical areas while aggressively reducing complexity in non-critical areas, thus resolving the contradiction between visual quality and rendering efficiency.
2Productivity
If the three dimensional model is decimated to reduce complexity for efficient rendering, then the rendering efficiency is improved, but the visual detail is lost
Solution Approach 1:
The patent applies local quality by differentiating between critical and non-critical areas of the 3D model. Critical areas maintain high geometric fidelity and visual detail, while non-critical areas are decimated to lower complexity. This selective approach preserves visual quality where needed while improving overall rendering efficiency by reducing complexity in less important regions.
3Productivity
If manual optimization is performed to reduce model complexity, then the rendering efficiency can be improved, but the time required and expertise needed increase significantly
Solution Approach 1:
The patent implements self-service by enabling the system to automatically identify critical and non-critical areas, perform decimation, and optimize the 3D model without requiring manual intervention. The automated optimization process reduces both the time required and the expertise needed, while still achieving improved rendering efficiency through intelligent complexity reduction.
Solution Approach 2:
The patent applies parameter changes by automatically adjusting geometric fidelity parameters based on the criticality of different model areas. The system modifies decimation parameters, level of detail settings, and complexity thresholds to achieve optimal rendering efficiency without manual optimization, thereby reducing the time and expertise required while maintaining visual quality where critical.
4Productivity
If the model complexity is reduced to meet frame rate thresholds, then the rendering efficiency is improved, but the visual quality deteriorates
Solution Approach 1:
The patent applies local quality by differentiating between critical and non-critical areas of the 3D model. Critical areas maintain high geometric fidelity and visual detail, while non-critical areas are decimated to lower complexity. This selective approach preserves visual quality where needed while improving overall rendering efficiency by reducing complexity in less important regions.
Data Source
AI summary
Visual optimization of three dimensional models in computer automated design is disclosed herein. An example method includes receiving a three dimensional model having a first rendering complexity level, displaying the three dimensional model in such a way that areas of complexity are visually distinct from other areas, based on an optimization schema applied to the three dimensional model, applying the optimization schema to decimate the areas of complexity such that the three dimensional model can be rendered at a second rendering complexity level, the decimation being bounded by a visual quality level for the three dimensional model, and displaying the three dimensional model at the second rendering complexity level on a display system.