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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.7 P.1225-1232

http://doi.org/10.1631/jzus.2006.A1225


Using LBG quantization for particle-based collision detection algorithm


Author(s):  SAENGHAENGTHAM Nida, KANONGCHAIYOS Pizzanu

Affiliation(s):  Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Thailand

Corresponding email(s):   g47nsn@cp.eng.chula.ac.th, pizzanu@cp.eng.chula.ac.th

Key Words:  Collision detection, Deformable object, Particle, LBG, Vector quantization


SAENGHAENGTHAM Nida, KANONGCHAIYOS Pizzanu. Using LBG quantization for particle-based collision detection algorithm[J]. Journal of Zhejiang University Science A, 2006, 7(7): 1225-1232.

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author="SAENGHAENGTHAM Nida, KANONGCHAIYOS Pizzanu",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1225"
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DOI - 10.1631/jzus.2006.A1225


Abstract: 
Most collision detection algorithms can be efficiently used only with solid and rigid objects, for instance, Hierarchical methods which must have their bounding representation recalculated every time deformation occurs. An alternative algorithm using particle-based method is then proposed which can detect the collision among non-rigid deformable polygonal models. However, the original particle-based collision detection algorithm might not be sufficient enough in some situations due to the improper particle dispersion. Therefore, this research presents an improved algorithm which provides a particle to detect in each separated area so that particles always covered all over the object. The surface partitioning can be efficiently performed by using LBG quantization since it can classify object vertices into several groups base on a number of factors as required. A particle is then assigned to move between vertices in a group by the attractive forces received from other particles on neighbouring objects. Collision is detected when the distance between a pair of corresponding particles becomes very small. Lastly, the proposed algorithm has been implemented to show that collision detection can be conducted in real-time.

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