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