Volume 9 Number 1 (Jan. 2014)
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JSW 2014 Vol.9(1): 26-36 ISSN: 1796-217X
doi: 10.4304/jsw.9.1.26-36

The Population-Based Optimization Algorithms for Role Modelling and Path Generation in Group Animation

Hong Liu1, Yuanyuan Li2, Hanchao Yu2
1School of Information Science and Engineering, Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan City, P.R.China
2School of Information Science and Engineering, Shandong Normal University, Jinan City, P.R.China


Abstract—Traditional animation by key frame techniques takes animators lots of time and vigour to model and simulate behaviours of crowds. For solving this problem, this paper presents a novel group animation generation approach based on population-based optimization algorithms. It is mainly divided into two parts. First, it puts forward a role modelling approach based on dynamic selfadaptive genetic algorithm and NURBS technology. Second, following the introduction to PSO (Particle Swarm Optimization) algorithm, a group path generative approach is presented. It simulates group behaviours, including cohesion and separation, dynamic object tracking and collision avoidance. Finally, a group of shark modelling and path generation images are exhibited as examples.

Index Terms—group animation, role modelling, genetic algorithm, PSO algorithm, path generation

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Cite: Hong Liu, Yuanyuan Li, Hanchao Yu, "The Population-Based Optimization Algorithms for Role Modelling and Path Generation in Group Animation," Journal of Software vol. 9, no. 1, pp. 26-36, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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