A Comparison of Particle Swarm Optimization and Genetic Algorithm for Human Head Tracking

抄録

This paper proposes a comparison study of particle swarm optimization and genetic algorithm for a perceptual system of a partner robot. The robot requires the capability of visual perception to interact with a human. Basically, a robot should perform moving object extraction for visual perception used in the interaction with human. In order to reduce time cost consumption, we used differential extraction. In this paper, we propose human head tracking for a partner robot by using particle swarm optimization and genetic algorithm. The experimental results show that the performance comparison of the human head tracking between both algorithms.