NDLI: Face recognition by using discriminative common vectors

Content Provider	IEEE Xplore Digital Library
Author	Cevikalp, H. Wilkes, M.
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. Eng. & Comput. Sci., Vanderbilt Univ., Nashville, TN, USA (Cevikalp, H.; Wilkes, M.)
Abstract	In face recognition tasks, the dimension of the sample space is typically larger than the number of the samples in the training set. As a consequence, the within-class scatter matrix is singular and the linear discriminant analysis (LDA) method cannot be applied directly. This problem is also known as the "small sample size" problem. In this paper, we propose a new face recognition method based on the discriminative common vectors for the small sample size case. The discriminative common vectors representing the people in the face database were found by using the null space of the within-class scatter matrix. Then, these vectors were used for classification of new faces. Test results show that the proposed method is superior to other methods in terms of accuracy, efficiency, and numerical stability.
Starting Page	326
Ending Page	329
File Size	289619
Page Count	4
File Format	PDF
ISBN	0769521282
ISSN	10514651
DOI	10.1109/ICPR.2004.1334118
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-08-26
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face recognition Face detection Null space Light scattering Vectors Application software Linear discriminant analysis Optimized production technology Databases Testing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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