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 Face Recognition under Varying Illumination

Erald Vuçini, Muhittin Gökmen, Meister Eduard Gröller
Face Recognition under Varying Illumination
In 15th WSCG 2007, pages 57-64. January 2007.
[ Paper]
Information
  • Publication Type: Conference Paper
  • Address: University of West Bohemia, Univerzitni 8, Box 314, CZ 306 14 Plzen, Czech Republic
  • Date (from): January 29, 2007
  • Date (to): February 1,2007
  • Editor: Vaclav Skala
  • ISBN: 978-80-86943-01-5
  • Lecturer: Erald Vucini
  • Location: Plzen, Czech Republic
  • Note: Full Paper
  • Organization: WSCG
  • Publisher: University of West Bohemia
  • Series: WSCG’2007 Full Papers Proceedings
  • Keywords: Dimensionality Reduction, Face Recognition, Image Synthesis, Illumination Restoration

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.

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BibTeX
Download BibTeX-Entry
@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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