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Regularization of LDA for Face Recognition: A Post-processing Approach

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Analysis and Modelling of Faces and Gestures (AMFG 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3723))

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Abstract

When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null space (irregular) and those in the range space (regular) of the within-class scatter matrix. Recently, regularization techniques, which alleviate the over-fitting to the training set, have been used to further improve the recognition performance of LDA. Most current regularization techniques, however, are pre-processing approaches and can’t be used to regularize irregular discriminant vectors. This paper proposes a post-processing method, 2D-Gaussian filtering, for regularizing both regular and irregular discriminant vectors. This method can also be combined with other regularization techniques. We present two LDA methods, regularization of subspace LDA (RSLD) and regularization of complete Fisher discriminant framework (RCFD) and test them on the FERET face database. Post-processing is shown to improve the recognition accuracy in face recognition.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China

    Wangmeng Zuo & Kuanquan Wang

  2. Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    David Zhang & Jian Yang

Authors
  1. Wangmeng Zuo
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  2. Kuanquan Wang
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  3. David Zhang
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  4. Jian Yang
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Editor information

Editors and Affiliations

  1. Intuitive Surgical Inc, 950 Kifer Road, 94086, Sunnyvale, CA, USA

    Wenyi Zhao

  2. Shaogang Gong, Department of Computer Science, Queen Mary, University of London, E1 4NS, London, UK

    Shaogang Gong

  3. Microsoft Research Asia, P.O. Box, Beijing, P.R. China

    Xiaoou Tang

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© 2005 Springer-Verlag Berlin Heidelberg

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Zuo, W., Wang, K., Zhang, D., Yang, J. (2005). Regularization of LDA for Face Recognition: A Post-processing Approach. In: Zhao, W., Gong, S., Tang, X. (eds) Analysis and Modelling of Faces and Gestures. AMFG 2005. Lecture Notes in Computer Science, vol 3723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564386_29

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  • DOI: https://doi.org/10.1007/11564386_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29229-6

  • Online ISBN: 978-3-540-32074-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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