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Human Head Tracking Based on Particle Swarm Optimization and Genetic Algorithm

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
    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

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