Sulistijono, Indra Adji and Kubota, Naoyuki (2007) Human Head Tracking Based on Particle Swarm Optimization and Genetic Algorithm. Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII), 11 (6). pp. 681-687. ISSN 1343-0130
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Abstract
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.
Item Type: | Article |
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Uncontrolled Keywords: | human head tracking, particle swarm optimization, steady-state genetic algorithm, visual perception, partner robot |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
Depositing User: | Dr.Eng. Indra Adji Sulistijono |
Date Deposited: | 21 Mar 2012 09:06 |
Last Modified: | 21 Mar 2012 09:06 |
URI: | http://repo.pens.ac.id/id/eprint/1666 |
Available Versions of this Item
- Human Head Tracking Based on Particle Swarm Optimization and Genetic Algorithm. (deposited UNSPECIFIED)
- Human Head Tracking Based on Particle Swarm Optimization and Genetic Algorithm. (deposited 21 Mar 2012 09:06)[Currently Displayed]
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