Adaptive 3D Mesh Decimation for Streaming and Printing
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Solution Overview
Problem
Existing 3D mesh simplification techniques fail to optimize geometry for specific consumption scenarios, leading to suboptimal quality and efficiency in data streaming and 3D printing, as they apply a one-size-fits-all approach without considering contextual priorities or device capabilities.
Innovation Solution
The method involves sorting 3D data by resolution priority and selectively simplifying it, with higher priority regions retaining higher resolution, and aligning simplification with target device specifications, such as 3D printer capabilities or display resolution, to achieve aggressive compression while preserving fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mesh decimation is applied to reduce data bandwidth, then data transmission efficiency is improved, but geometric fidelity deteriorates
Solution Approach 1:
The patent applies different decimation strategies to different regions of the 3D mesh based on their visual importance. High-curvature regions and regions containing important features are preserved with higher fidelity, while low-curvature regions are aggressively decimated. This local differentiation resolves the contradiction by maintaining geometric fidelity where needed while achieving compression where permissible.
Solution Approach 2:
The patent segments the 3D mesh into multiple regions based on curvature analysis and feature detection. Each segment is then processed with appropriate decimation parameters, allowing the system to achieve overall compression while preserving critical geometric details in specific segments.
2Productivity
If aggressive mesh decimation is applied to reduce model complexity, then processing speed is improved, but visual quality deteriorates
Solution Approach 1:
The system identifies and protects visually critical regions from aggressive decimation while allowing non-critical regions to be simplified. This ensures that the portions of the model most important for visual quality maintain their detail, while other portions are optimized for processing speed.
Solution Approach 2:
The patent implements adaptive decimation parameters that can be dynamically adjusted based on the specific characteristics of the mesh and the desired output quality. This dynamic adjustment allows optimization for processing speed while maintaining visual quality thresholds.
3Ease of manufacture
If uniform decimation parameters are applied to all mesh regions, then implementation simplicity is improved, but contextual optimization deteriorates
Solution Approach 1:
The patent automatically analyzes the mesh to identify regions with different visual importance and applies context-appropriate decimation parameters to each region. This automated local optimization achieves contextual adaptation without requiring manual intervention, balancing implementation simplicity with optimization quality.
Solution Approach 2:
The decimation system performs self-analysis of the mesh characteristics and automatically adjusts its parameters accordingly. The algorithm identifies high-curvature regions, feature-containing regions, and low-curvature regions, and applies appropriate decimation strength to each, making the system adaptable without external guidance.
4Manufacturing precision
If high resolution is maintained throughout the entire 3D model, then geometric fidelity is improved, but data bandwidth requirement deteriorates
Solution Approach 1:
The patent maintains high geometric fidelity only in regions where it is visually necessary (high-curvature regions, regions containing important features) while reducing resolution in regions where it is not needed (low-curvature regions). This selective preservation of fidelity significantly reduces data bandwidth requirements while maintaining perceptual quality.
Solution Approach 2:
The mesh is segmented into regions of different visual importance, and each segment is processed at an appropriate resolution level. This segmentation strategy reduces overall data bandwidth requirements by avoiding the transmission of high-resolution data for all regions uniformly.
Data Source
AI summary
Systems, devices, and methods are described herein for geometrically simplifying three-dimensional (3D) video data. In one aspect, a method may include obtaining 3D data, with the 3D data including a plurality of portions associated with a default resolution priority. A higher resolution priority may be associated with one or more portions of the 3D data. Next, portions of the 3D data may be sorted according to resolution priorities associated with each portion, and geometric simplification may be performed on the sorted portions of the 3D data, beginning with portions associated with a least resolution priority and continuing with portions associated with successively higher resolution priorities. The simplified 3D data may be processed, for example, for rendering on a computing device or transmission to another device for display or generation, such as a 3D printing device for generating a 3D object.