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Pseudo-Fisherface method for single image per person face recognition

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2 Author(s)
A. Majumdar ; Department of Electrical and Computer Engineering, University of British Columbia, Columbia ; R. K. Ward

The problem of recognizing a face from a single sample available in a stored dataset is addressed. A new method of tackling this problem by using the Fisherface method on a generic dataset is explored. The recognition scheme is also extended to multiscale transform domains like wavelet, curvelet and contourlet. The proposed method in the transform domain shows better recognition errors than the SPCA algorithm and Eigenface selection method, both of which are specially tailored for recognizing faces from single samples.

Published in:

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

March 31 2008-April 4 2008