Automatic parameter selection for Eigenfaces

Tjahyadi, Ronny, Liu, Wanquan and Venkatesh, Svetha 2004, Automatic parameter selection for Eigenfaces, in ICOTA 2004 : 6th International Conference on Optimization : Techniques and Applications, [University of Ballarat], [Ballarat, Vic.], pp. 1-10.

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Title Automatic parameter selection for Eigenfaces
Author(s) Tjahyadi, Ronny
Liu, Wanquan
Venkatesh, SvethaORCID iD for Venkatesh, Svetha
Conference name International Conference on Optimization : Techniques and Applications (6th : 2004 : Ballarat, Vic.)
Conference location Ballarat, Vic.
Conference dates 9-11 Dec. 2004
Title of proceedings ICOTA 2004 : 6th International Conference on Optimization : Techniques and Applications
Editor(s) Rubinov, Alex
Sniedovich, Moshe
Publication date 2004
Conference series International Conference on Optimization : Techniques and Applications
Start page 1
End page 10
Total pages 10
Publisher [University of Ballarat]
Place of publication [Ballarat, Vic.]
Keyword(s) Eigenfaces
threshold selection methods
Summary In this paper, we investigate the parameter selection issues for Eigenfaces. Our focus is on the eigenvectors and threshold selection issues. We propose a systematic approach in selecting the eigenvectors based on the relative errors of the eigenvalues. In addition, we have designed a method for selecting the classification threshold that utilizes the information obtained from the training database effectively. Experimentation was conducted on the ORL and AMP face databases with results indicating that the automatic eigenvectors and threshold selection methods provide an optimum recognition in terms of precision and recall rates. Furthermore, we show that the eigenvector selection method outperforms energy and stretching dimension methods in terms of selected number of eigenvectors and computation cost.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
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