Efficient and accurate collision detection based on surgery simulation

Authors:
Kai Xie;Jie Yang;Yue Min Zhu
Affiliations:
Inst. of Image Processing & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China;Inst. of Image Processing & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China;CREATIS – CNRS research unit 5515 & INSERM unit 630, Villeurbanne, France
Venue:
Miar'06 Proceedings of the Third international conference on Medical Imaging and Augmented Reality
Year:
2006

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Abstract

In this paper, we present a sphere-tree based hierarchical collision detection algorithm (STHCD) for surgery simulation. Each model is represented as a clustered hierarchy of sphere tree (CHST). Graphics processing unit (GPU)-based occlusion queries were used for fast collision culling between massive models. Furthermore, we are able to generate these hierarchies and perform collision queries using out-of-core techniques on all triangulated models. Experimental results show that STHCD performs real-time collision detection between massive bones and implant models, consisting of millions of triangles at interactive rates on a commodity PC.