GPU-based radial view-based culling for continuous self-collision detection of deformable surfaces

Abstract

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.