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

[PDF]

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.