Human Head Tracking Based on Particle Swarm Optimization and Genetic Algorithm
Indra Adji Sulistijono*,** and Naoyuki Kubota***,****
*Dept. of Mechanical Engineering, Graduate School of Engineering, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan
**Electronics Eng. Polytechnic Institute of Surabaya - ITS (EEPIS-ITS), Kampus ITS Sukolilo, Surabaya 60111, Indonesia
***Dept. of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan
****SORST, Japan Science and Technology Agency (JST)
This paper compares particle swarm optimization and a genetic algorithm for perception by a partner robot. The robot requires visual perception to interact with human beings. It should basically extract moving objects using visual perception in interaction with human beings. To reduce computational cost and time consumption, we used differential extraction. We propose human head tracking for a partner robot using particle swarm optimization and a genetic algorithm. Experiments involving two maximum iteration numbers show that particle swarm optimization is more effective in solving this problem than genetic algorithm.
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