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https://hdl.handle.net/2440/55299
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Type: | Journal article |
Title: | Subspace-based face recognition: Outlier detection and a new distance criterion |
Author: | Chen, P. Suter, D. |
Citation: | International Journal of Pattern Recognition and Artificial Intelligence, 2005; 19(4):479-493 |
Publisher: | World Scientific Publ Co Pte Ltd |
Issue Date: | 2005 |
ISSN: | 0218-0014 1793-6381 |
Statement of Responsibility: | Pei Chen and David Suter |
Abstract: | Illumination effects, including shadows and varying lighting, make the problem of face recognition challenging. Experimental and theoretical results show that the face images under different illumination conditions approximately lie in a low-dimensional subspace, hence principal component analysis (PCA) or low-dimensional subspace techniques have been used. Following this spirit, we propose new techniques for the face recognition problem, including an outlier detection strategy (mainly for those points not following the Lambertian reflectance model), and a new error criterion for the recognition algorithm. Experiments using the Yale-B face database show the effectiveness of the new strategies. |
Keywords: | Face recognition Lambertian reflection linear subspace principal component analysis illumination effect iterative reweighted least square |
DOI: | 10.1142/S0218001405004174 |
Published version: | http://dx.doi.org/10.1142/s0218001405004174 |
Appears in Collections: | Aurora harvest 5 Computer Science publications |
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