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@inproceedings\{vucini_erald-2007-FRI,
title = "Face Recognition under Varying Illumination",
author = "Erald Vu{\c c}ini and Muhittin G{\"o}kmen and Meister
Eduard Gr{\"o}ller",
year = "2007",
abstract = "This paper proposes a novel pipeline to develop a Face
Recognition System robust to illumination variation. We
consider the case when only one single image per person is
available during the training phase. In order to utilize the
superiority of Linear Discriminant Analysis (LDA) over
Principal Component Analysis (PCA) in regard to variable
illumination, a number of new images illuminated from
different directions are synthesized from a single image by
means of the Quotient Image. Furthermore, during the testing
phase, an iterative algorithm is used for the restoration of
frontal illumination of a face illuminated from any
arbitrary angle. Experimental results on the YaleB database
show that our approach can achieve a top recognition rate
compared to existing methods and can be integrated into real
time face recognition system.",
pages = "57--64",
month = jan,
organization = "WSCG",
note = "Full Paper",
address = "University of West Bohemia, Univerzitni 8, Box 314, CZ 306
14 Plzen, Czech Republic",
booktitle = "15th WSCG 2007",
editor = "Vaclav Skala",
isbn = "978-80-86943-01-5",
series = "WSCG’2007 Full Papers Proceedings",
publisher = "University of West Bohemia",
location = "Plzen, Czech Republic",
keywords = "Dimensionality Reduction, Face Recognition, Image Synthesis,
Illumination Restoration",
URL = "http://www.cg.tuwien.ac.at/research/publications/2007/vucini_erald-2007-FRI/",
}
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