Gesture recognition for a partner robot based on computational intelligence

Author

Kubota, Naoyuki ; Tomioka, Yu. ; Yamaguchi, Toru

Author_Institution

Dept. of Syst. Design, Tokyo Metropolitan Univ., Hino

fYear

2008

fDate

1-6 June 2008

Firstpage

1477

Lastpage

1482

Abstract

Recently, various types of human-friendly robot have been developed. Such robots should perform voice recognition, gesture recognition, and others. This paper discusses the learning capability of a human gesture recognition method based on computational intelligence. The proposed method is composed of image processing for human face and hand detection based on a steady-state genetic algorithm, an extraction method for human hand motion based on a fuzzy spiking neural network, and an unsupervised classification method for human hand motion based on a self-organizing map. We show several experimental results and discuss their effectiveness.

Keywords

feature extraction; fuzzy neural nets; gesture recognition; image classification; image motion analysis; self-organising feature maps; computational intelligence; extraction method; fuzzy spiking neural network; human face-hand detection; human gesture recognition method; human hand motion; human-friendly robots; partner robot; steady-state genetic algorithm; unsupervised classification method; voice recognition; Computational intelligence; Face detection; Fuzzy neural networks; Genetic algorithms; Humans; Image processing; Intelligent robots; Motion detection; Speech recognition; Steady-state;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on

Conference_Location

Hong Kong

ISSN

1098-7584

Print_ISBN

978-1-4244-1818-3

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZY.2008.4630567

Filename

4630567