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Gabor-Eigen-Whiten-Cosine: A Robust Scheme for Face Recognition

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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

Recognizing faces with complex intrapersonal variations is a challenging task, especially when using small size samples. Our approach, which obtains state of the art results, is based on a new face recognition scheme: Gabor-Eigen-Whiten-Cosine (GEWC). The novelty of this paper lies in 1) the finding that the same face with complex variations, projected into the Gabor based whitened PCA feature space, is approximately angle invariance; and 2) the experimental studies that analyze the joint contribution of Gabor wavelet, whitening process, and cosine similarity measure on the PCA based face recognition. The new GEWC method has been successfully tested and evaluated using comparative experiments on 3000+ FERET frontal face images with 1196 subjects. In particular, the GEWC method achieves constant 100% accuracy on the 200-subject experiment across illuminations and facial expressions. Furthermore, its recognition rates reach up to 96.3%, 99.5%, 78.8%, and 77.8% on the FB, fc, dup I, and dup II probes respectively using only one training sample per person.

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Author information

Authors and Affiliations

  1. Beijing University of Posts and Telecommunications, 100876, Beijing, China

    Weihong Deng, Jiani Hu & Jun Guo

Authors
  1. Weihong Deng
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  2. Jiani Hu
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  3. Jun Guo
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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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Deng, W., Hu, J., Guo, J. (2005). Gabor-Eigen-Whiten-Cosine: A Robust Scheme for Face Recognition. 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_26

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  • DOI: https://doi.org/10.1007/11564386_26

  • 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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