Dynamic radial view based culling for continuous self-collision detection

Sai-Keung Wong, Wen-Chieh Lin, Yu-Shuen Wang, Chun Hung Hung, Yi Jheng Huang

研究成果: Conference contribution同行評審

8 引文 斯高帕斯(Scopus)

摘要

The radial view-based culling (RVBC) method has been presented for continuous self-collision detection to efficiently cull away noncolliding regions. While this technique mainly relies on the segmented clusters of the reference pose and the associated fixed observer points, it has several drawbacks during the animation and the reduced cost of executing collision detection is limited. We thus present a modified framework to improve the culling efficiency of RVBC. At the preprocessing stage, we segment the closed deformable mesh according to not only the attached skeleton but also the triangle orientations, in order to minimize the collision checks of triangles in a cluster. At the runtime stage, we dynamically merge adjacent clusters and update the positions of observer points if the merged shape is nearly convex. This strategy minimizes the number of triangles in different clusters that required collision check. Our framework can be easily integrated with bounding volume hierarchies to boost the culling efficiency. Experimental results show that our framework achieves up to 5.2 times speedup over the original RVBC method and even more times over the recent techniques.

原文English
主出版物標題Proceedings of the 18th Meeting of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2014
發行者Association for Computing Machinery
頁面39-46
頁數8
ISBN(列印)9781450327176
DOIs
出版狀態Published - 1 一月 2014
事件18th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2014 - San Francisco, CA, United States
持續時間: 14 三月 201416 三月 2014

出版系列

名字Proceedings of the Symposium on Interactive 3D Graphics

Conference

Conference18th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2014
國家/地區United States
城市San Francisco, CA
期間14/03/1416/03/14

指紋

深入研究「Dynamic radial view based culling for continuous self-collision detection」主題。共同形成了獨特的指紋。

引用此