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Single image per person face recognition with images synthesized by non-linear approximation

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2 Author(s)
Majumdar, A. ; Dept. of Electr. & Comput. Eng., Univ. of British Columbia, BC ; Ward, R.K.

This paper addresses the problem of identifying faces when the training face database consists of one face image of each person. It proposes a new approach that synthesizes new face samples of varying degrees of edge information; the synthesized images are generated from the original image and form non-linear approximations of the latter. The approximation is framed as an l 1 minimization problem in a transform domain. The paper also shows that a voting based approach to recognize faces from single available samples yields better results than previous works that only augmented the available database. The proposed approach yields considerably better results (about 6% increase in recognition accuracy) than the SPCA method, which was tailored for addressing this problem.

Published in:

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Date of Conference:

12-15 Oct. 2008