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Published on: October 20, 2023
Surface and curve skeletonization of large 3D models on the GPU
Andrei C Jalba1, Jacek Kustra, Alexandru C Telea
1Department of Mathematics and Computer Science, Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven, The Netherlands. A.C.Jalba@tue.nl
Summary
This study introduces a fast GPU framework for 3D shape skeletonization, enabling precise surface and curve skeleton extraction for complex models. The method significantly speeds up computation and reduces memory usage.
Area of Science:
- Computer Graphics
- Computational Geometry
- Geometric Modeling
Background:
- Extracting skeletal structures from 3D shapes is crucial for analysis and processing.
- Existing methods often struggle with large polygonal meshes, computational efficiency, and precision.
Purpose of the Study:
- To develop a high-performance GPU-based framework for accurate surface and curve skeleton extraction.
- To improve the speed and precision of skeletonization for complex 3D models.
Main Methods:
- Utilized a GPU-based framework with parallel search for point-cloud skeleton computation.
- Employed a novel GPU-based geodesic tracing for skeleton regularization.
- Implemented a fast image-based method for surface reconstruction from skeletons.
Main Results:
- Achieved orders of magnitude speed-up compared to existing skeletonization techniques.
- Demonstrated high-precision skeleton extraction and surface reconstruction.
- Showcased efficient reconstruction of skeletal manifold structures and curve skeletons.
Conclusions:
- The proposed GPU framework offers significant performance improvements for 3D shape skeletonization.
- The method provides a robust and accurate solution for complex geometric models.
- The framework enables efficient reconstruction of both skeletal structures and original surfaces.
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