Dynamic clothing collision resolution using PSO

  • Authors:
  • Wen-hui Li;Yi Wang;Yi Li;Qi Jiang

  • Affiliations:
  • Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education, College of Computer Science and Technology, Jilin University, ChangChun, China.;School of Software of Dalian University of Technology, Dalian, China.;Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education, College of Computer Science and Technology, Jilin University, ChangChun, China.;Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education, College of Computer Science and Technology, Jilin University, ChangChun, China

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2010

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Abstract

This paper presents a novel stochastic method for dynamic clothing simulation and collision detection by using a Particle Swarm Optimisation (PSO) algorithm. Firstly, we convert the collision detection problem to a multi-objective dynamic environment optimisation problem. Then, we use a density-based clustering PSO to find optimal or near-optimal solutions. During the searching process, we also put forward a restrictive fly algorithm to prevent particles from flying out of the solution space. Experimental results demonstrate that PSO has good performances in our optimisation problem. Besides, with active pair searching and Bounding Volume Hierarchies (BVHs), our method can achieve high detection ratio and balanced performances at interactive rates.