Browsing by Author "Cheng, Yu-Chun"

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Continuous Self-Collision Detection for Deformable Surfaces Interacting with Solid Models
(2014-09-01)
Wong, Sai-Keung
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Cheng, Yu-Chun
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交大名義發表
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National Chiao Tung University
In this paper, we propose a new continuous self-collision detection (CSCD) method for a deformable surface that interacts with a simple solid model. The method is developed based on the radial-view-based culling method. Our method is suitable for the deformable surface that has large contact region with the solid model. The deformable surface may consist of small round-shaped holes. At the pre-processing stage, the holes of the deformable surface are filled with ghost triangles so as to make the mesh of the deformable surface watertight. An observer primitive (i.e. a point or a line segment) is computed so that it lies inside the solid model. At the runtime stage, the orientations of triangles with respect to the observer primitive are evaluated. The collision status of the deformable surface is then determined. We evaluated our method for several animations including virtual garments. Experimental results show that our method improves the process of CSCD.
GPU-based radial view-based culling for continuous self-collision detection of deformable surfaces
(2016-01)
Wong, Sai-Keung
;
Cheng, Yu-Chun
;
資訊工程學系
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Department of Computer Science
We propose a graphics processing unit-based approach to accelerate the radial view-based culling method for continuous self-collision detection of deformable surfaces. The deformable surfaces may have small round-shaped holes and ghost triangles are used to fill the holes. We identify the key processes of the radial view-based culling method, including triangle classification, traversal of bounding volume hierarchies and handling violated triangles (i.e., the triangles intersecting with ghost triangles). We propose efficient parallel processing techniques to perform these key processes on a programmable graphics unit. We have evaluated our proposed approach on several examples. Experimental results show that our approach significantly cuts down the cost of the key processes of the radial-based culling method, compared with the serial implementation on CPU.