doi: 10.4304/jsw.9.1.26-36
The Population-Based Optimization Algorithms for Role Modelling and Path Generation in Group Animation
- 1 School of Information Science and Engineering, Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan City, P.R.China
- 2 School 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.
Keywords
- group animation
- role modelling
- genetic
How to Cite
Hong Liu, Yuanyuan Li, and 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. https://doi.org/ 10.4304/jsw.9.1.26-36
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).