计算机科学 ›› 2013, Vol. 40 ›› Issue (1): 244-246.

• 人工智能 • 上一篇    下一篇

基于遗传算法和微粒群算法的群体动画造型平台

王爱霖,刘弘,张鹏   

  1. (山东师范大学信息科学与工程学院 济南250358);(山东师范大学山东省分布式计算机软件新技术重点实验室 济南250014)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Genetic Algorithm and Particle Swarm Optimization Based Animation Group Modeling Platform

  • Online:2018-11-16 Published:2018-11-16

摘要: 动漫制作经常需要大量的个体模型。为了解决群体造型的效率性和仿真度问题,提出了基于遗传算法和微 粒群算法的群体造型方法—NGP算法,利用该算法实现由一个复杂模型生成复杂模型群体的过程。遗传算法适用 于同一类群体的造型,对每种部件应用这种方法形成各种各样的部件库;微粒群算法适用于对复杂模型的部件进行组 合,采用这种方法对各部件进行组合优化,以形成模型群体。实现了基于NGP算法的群体动画造型平台。实验结果 表明,平台生成的群体仿真度高,且生成过程效率高。

关键词: 仿真,群体造型,遗传算法,微粒群算法

Abstract: Animation production often requires a lot of individual model. In order to solve the problem of group mode- ling efficiency and simulation,population modeling method based on genetic algorithm and particle swarm algorithm- the NGP algorithm was proposed. The algorithm achieves the process of group cartoon model generated by one cartoon model. Genetic algorithm is applied to groups of the same type of modeling,applying this method for each component to form a variety of component libraries. Particle swarm algorithm is applied to the combination of the components of the complex models, combinatorial optimization of the various components in this algorithm, the formation of the model groups. Animation modeling platform based on the NGP algorithm was achieved. I}he experiment show the generated model has a high degree of simulation, and the generation process is quick.

Key words: Simulation, Group modeling, Genetic algorithm, Particle swarm optimization

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