On face recognition using hierarchical self-organized gabor features

Saleh Aly, Naoyuki Tsuruta, Rin-Ichiro Taniguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Gabor-based face representation has achieve enormous success in face recognition. However, one drawback of Gabor-based face representation is the huge amount of data that must be stored. Due to the nonlinear structure of the data obtained from Gabor response, classical linear projection methods like principal component analysis failed to reduce this large amount of data. As a way to solve this problem, a nonlinear projection method is exploited. A set of hierarchical self-organizing maps is employed to capture the nonlinearity of the data and to represent it in a new reduced feature space. Experimental results on ORL face database prove the validity of our proposed feature extraction method.

Original languageEnglish
Title of host publicationProceedings of the 11th IAPR Conference on Machine Vision Applications, MVA 2009
Pages475-478
Number of pages4
Publication statusPublished - Dec 1 2009
Event11th IAPR Conference on Machine Vision Applications, MVA 2009 - Yokohama, Japan
Duration: May 20 2009May 22 2009

Other

Other11th IAPR Conference on Machine Vision Applications, MVA 2009
CountryJapan
CityYokohama
Period5/20/095/22/09

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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  • Cite this

    Aly, S., Tsuruta, N., & Taniguchi, R-I. (2009). On face recognition using hierarchical self-organized gabor features. In Proceedings of the 11th IAPR Conference on Machine Vision Applications, MVA 2009 (pp. 475-478)