DocumentCode :
554252
Title :
Improved K-DOPs collision detection algorithms based on genetic algorithms
Author :
Wei Zhao ; Lei Li
Author_Institution :
Sch. of Inf. Technol., Jilin Agric. Univ., Changchun, China
Volume :
1
fYear :
2011
fDate :
12-14 Aug. 2011
Firstpage :
338
Lastpage :
341
Abstract :
In collision detection algorithm based on bounding volume hierarchies, the update cost of the bounding volume hierarchies tree when the collision detection object motion or deformation directly influenced speed of collision detection. According to this trait, the update of bounding volume hierarchies was optimized by utilizing temporal-spatial coherence in virtual environment. It can reduce the cost when the collision detection object motion or deformation that coused the update of the bounding volume hierarchies tree by using the genetic algorithm instead of traditional approximate method and improve the speed of collision detection greatly. Experimental results show that this algorithm can solve the complexity and improve the property of the collision detection algorithm effectively.
Keywords :
cost reduction; genetic algorithms; trees (mathematics); virtual reality; K-discrete orientation polytopes collision detection algorithm; bounding volume hierarchies optimization; bounding volume hierarchies tree; cost reduction; genetic algorithm; temporal-spatial coherence; virtual environment; Approximation algorithms; Complexity theory; Detection algorithms; Educational institutions; Genetic algorithms; Heuristic algorithms; Virtual environments; K-DOPs; bounding box; collision detection; genetic algorithms(GA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
Type :
conf
DOI :
10.1109/EMEIT.2011.6022939
Filename :
6022939
Link To Document :
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