Browsing by Author "Lin, Ying-yin"

Now showing 1 - 2 of 2

Controlling the movement of crowds in computer graphics by using the mechanism of particle swarm optimization
(2009-06-01)
Chen, Ying-ping
;
Lin, Ying-yin
;
資訊工程學系
;
Department of Computer Science
This paper presents a uniform conceptual model to co-operate with particle swarm optimization (PSO) for controlling the movement of crowds in computer graphics. According to the PSO mechanism, each particle in the swarm adopts the information to automatically find a path from the initial position to the optimum. However, PSO aims to obtain the optimal solution instead of the searching path, while the purpose of this work concentrates on the control of the crowd movement, which is composed of the generated searching paths of particles. Hence, in order to generate seemingly natural, appropriate paths of people in a crowd, we propose a model to work with the computational facilities provided in PSO. Compared to related approaches previously presented in the literature, the proposed model is simple, uniform, and easy to implement. The results of the conducted simulations demonstrate that the coupling of PSO and the proposed technique can generate appropriate non-deterministic, non-colliding paths for the use in computer graphics for several different scenarios, including static and dynamic obstacles, moving targets, and multiple crowds. (C) 2009 Elsevier B. V. All rights reserved.
Crowd control with swarm intelligence
(2007)
Lin, Ying-yin
;
Chen, Ying-ping
;
資訊工程學系
;
Department of Computer Science
This paper presents a uniform conceptual model based on the particle swarm optimization (PSO) paradigm to simulate crowds in computer graphics. According to the mechanisms of PSO, each person (particle) in the crowd (swarm) can adopt the information to search a path from the initial position to the specified target (optimum) automatically. However, PSO aims to obtain the optimal solution, while the purpose of this study concentrates on the generated paths of particles. Hence, in order to generate appropriate paths of people in a crowd, we propose a method to employ the computational facilities provided in PSO. The proposed model is simple, uniform, and easy to implement. The results of simulations demonstrate that using PSO with the proposed technique can generate appropriate non-deterministic, non-colliding paths in several different scenarios, including static obstacles, moving targets, and multiple crowds.