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Controlling the movement of crowds in computer graphics by using the mechanism of particle swarm optimization

机译:使用粒子群优化机制控制计算机图形中人群的移动

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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.
机译:本文提出了一个统一的概念模型,与粒子群优化(PSO)合作,用于控制计算机图形学中人群的移动。根据PSO机制,群中的每个粒子都采用该信息来自动查找从初始位置到最佳位置的路径。但是,PSO的目的是获得最佳解决方案而不是搜索路径,而这项工作的目的则集中在人群运动的控制上,该运动由生成的粒子搜索路径组成。因此,为了在人群中生成看似自然,适当的人员路径,我们提出了一种模型,可与PSO中提供的计算工具一起使用。与先前文献中提出的相关方法相比,该模型简单,统一且易于实现。进行的仿真结果表明,PSO和所提出的技术的耦合可以生成适当的不确定性,非冲突性路径,以用于计算机图形学中的几种不同情况,包括静态和动态障碍,移动目标和多个人群。

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