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Advances in Multimedia Modeling pp 436–445Cite as

Illumination Variation Dictionary Designing for Single-Sample Face Recognition via Sparse Representation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7733))

Abstract

This paper focuses on enhancing Sparse Representation based Classifier (SRC) in single-sample face recognition tasks under varying illumination conditions. The major contribution is two-fold: firstly, we present an interesting observation based on Lambertian reflectance model: the identity information will be canceled out by the pair-wise difference images from the same subject in logarithmic domain, and only the subject-independent illumination variation retains. Secondly, inspired from this observation, we propose to “borrow” illumination variations from any generic subject by constructing an illumination variation dictionary composed of pair-wise difference images of generic subjects in logarithmic domain to cover the possible illumination variations between test and gallery samples. Experimental results on Extended Yale B and FERET face databases demonstrate the superiority of our method.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering/Graduate School at Shenzhen, Tsinghua University, China

    Biao Wang, Weifeng Li & Qingmin Liao

  2. Tsinghua-PolyU Biometric Joint Laboratory, Tsinghua University, China

    Biao Wang, Weifeng Li & Qingmin Liao

  3. Shenzhen Key Laboratory of Information Science and Technology, China

    Biao Wang, Weifeng Li & Qingmin Liao

Authors
  1. Biao Wang
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  2. Weifeng Li
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  3. Qingmin Liao
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Editor information

Editors and Affiliations

  1. Microsoft Research Asia, 5 Danling Street, 100080, Beijing, China

    Shipeng Li  & Tao Mei  & 

  2. School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward, K1N 6N5, Ottawa, ON, Canada

    Abdulmotaleb El Saddik

  3. School of Computer and Information, Hefei University of Technology, Road Tunxi 193#, 230009, Hefei, Anhui, China

    Meng Wang  & Richang Hong  & 

  4. Department of Information Engineering and Computer Science, University of Trento, ommarive 14, 38100, Trento, Italy

    Nicu Sebe

  5. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117583, Singapore, Singapore

    Shuicheng Yan

  6. School of Computing, CLARITY: Centre for Sensor Web Technologies, Dublin City University, Glasnevin, 9, Dublin, Ireland

    Cathal Gurrin

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© 2013 Springer-Verlag Berlin Heidelberg

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Cite this paper

Wang, B., Li, W., Liao, Q. (2013). Illumination Variation Dictionary Designing for Single-Sample Face Recognition via Sparse Representation. In: Li, S., et al. Advances in Multimedia Modeling. Lecture Notes in Computer Science, vol 7733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35728-2_42

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  • DOI: https://doi.org/10.1007/978-3-642-35728-2_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35727-5

  • Online ISBN: 978-3-642-35728-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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