On face recognition using hierarchical self-organized gabor features

Saleh Aly, Naoyuki Tsuruta, Rin-Ichiro Taniguchi

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

3 引用 (Scopus)

抜粋

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.

元の言語英語
ホスト出版物のタイトルProceedings of the 11th IAPR Conference on Machine Vision Applications, MVA 2009
ページ475-478
ページ数4
出版物ステータス出版済み - 12 1 2009
イベント11th IAPR Conference on Machine Vision Applications, MVA 2009 - Yokohama, 日本
継続期間: 5 20 20095 22 2009

その他

その他11th IAPR Conference on Machine Vision Applications, MVA 2009
日本
Yokohama
期間5/20/095/22/09

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

フィンガープリント On face recognition using hierarchical self-organized gabor features' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

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