Collision Detection Algorithm of Deformable Object Based on Snake Model Optimization

Authors

Li Zhao, School of Computer Science and Control Engineering, North University of China, Taiyuan 030051, China;
Yanxia Jin, School of Computer Science and Control Engineering, North University of China, Taiyuan 030051, China;
Zhipeng Qin, School of Computer Science and Control Engineering, North University of China, Taiyuan 030051, China;
Ren Chao, School of Computer Science and Control Engineering, North University of China, Taiyuan 030051, China;

Abstract

Abstract: In view of the existing collision detection algorithm which is difficult to solve the collision of real-time and reality, an improved algorithm of collision detection was propsed based on deformable objects. The algorithm based on K-DOPs bounding box applied to update process used the improved PSO algorithm to optimize the Snake model boundary. The concave in collision region, the control point clusters and the center formed multi-linear swarm with the improved selection method and the ulti PSO algorithm. Experimental results show that the improved collision detection algorithm can accurate simulate object contour, simplify the bounding box to improve the efficiency of collision detection.

Recommended Citation

Zhao, Li; Jin, Yanxia; Qin, Zhipeng; and Chao, Ren (2019) "Collision Detection Algorithm of Deformable Object Based on Snake Model Optimization," Journal of System Simulation: Vol. 30: Iss. 1, Article 8.
DOI: 10.16182/j.issn1004731x.joss.201801008
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss1/8

First Page

62

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201801008

Last Page

68

CLC

TP391.9

Recommended Citation

Li Zhao, Jin Yanxia, Qin Zhipeng, Ren Chao. Collision Detection Algorithm of Deformable Object Based on Snake Model Optimization[J]. Journal of System Simulation, 2018, 30(1): 62-68.

DOI

10.16182/j.issn1004731x.joss.201801008