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

Indra Adji Sulistijono; Naoyuki Kubota

doi:10.14864/softscis.2006.0.2204.0

SCIS & ISIS 2006

Session ID : SU-C2-3

DOI https://doi.org/10.14864/softscis.2006.0.2204.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

SU-C2 Machine Learning & Evolutionary Optimization (3)

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

*Indra Adji Sulistijono, Naoyuki Kubota

Author information

Keywords: human head tracking, particle swarm optimization, genetic algorithm

CONFERENCE PROCEEDINGS FREE ACCESS

Details

Abstract

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.

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