Automatic parameters selection for eigenfaces

Tjahyadi, Ronny, Liu, Wanquan and Venkatesh, Svetha 2006, Automatic parameters selection for eigenfaces, Pacific journal of optimization, vol. 2, no. 2, pp. 277-288.

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Title Automatic parameters selection for eigenfaces
Author(s) Tjahyadi, Ronny
Liu, Wanquan
Venkatesh, SvethaORCID iD for Venkatesh, Svetha
Journal name Pacific journal of optimization
Volume number 2
Issue number 2
Start page 277
End page 288
Total pages 12
Publisher Yokohama Publishers
Place of publication Yokohama, Japan
Publication date 2006-05
ISSN 1348-9151
Keyword(s) face recognition
principal component analysis
matrix approximation
Summary In this paper, we investigate the parameters selection for Eigenfaces. Our focus is on the eigenvectors and threshold selection issues. We will propose a systematic approach in selecting the eigenvectors based on relative errors of the eigenvalues for the covariance matrix. In addition, we have proposed a method for selecting the classification threshold that utilizes the information obtained from the training data set. Experimentation was conducted on two benchmark face databases, ORL and AMP, with results indicating that the proposed automatic eigenvectors and threshold selection methods produce better recognition performance 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 080104 Computer Vision
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2006, Yokohama Publishers
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