Abstract
Notice of Violation of IEEE Publication Principles<br><br>"Efficient Collision Detection for Arbitrary Polyhedral Model Based on GPU and Swept Volume"<br>by Shujuan Peng and Yuanxiang Li and Hui Zeng<br>in the Proceedings of the International Colloquium on Computing, Communication, Control and Management, ISECS, Vol 2, August 2008, pp. 260-264<br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.<br><br>This paper contains significant portions of original text from the paper cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission.<br><br>Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:<br><br>"IBCD: A Fast Collision Detection Algorithm Based on Image Space Using OBB"<br>by Z. Fan, H. Wan, S. Gao<br>in the Journal of Visualization and Computer Animation (14) John Wiley and Sons, September 2003, pp. 169-181<br><br> <br/> This paper presents an efficient collision detection algorithm for arbitrary polyhedral objects moving randomly within the virtual environment. We decompose the non-convex objects into some convex pieces using the surface convex decomposition, construct the OBB for each convex piece and build the bounding volume hierarchy for the convex hull in the pro-precess phrase. Given the initial and final configurations of a moving polyhedral model, in the run-time phrase, our algorithm creates the continuous motion using the motion interpolation and use the swept volume to get the potentially collision objects set. The algorithm makes efficient use of the graphics rendering hardware (Z-buffer and stencil buffer) to reduce the computational cost of CPU in the run-time collision. The simulation result proves our algorithm is efficient compared with other related algorithms.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have