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Compact Binary Patterns (CBP) with Multiple Patch Classifiers for Fast and Accurate Face Recognition

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Computational Modeling of Objects Represented in Images (CompIMAGE 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6026))

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Abstract

Face recognition is one of the most active research areas in pattern recognition for the last decades because of its potential applications as well as scientific challenges. Although numerous methods for face recognition have been developed, recognition accuracy and speed still remain a problem. In this paper, we propose a novel method for fast and accurate face recognition. The contribution of the paper is three folds: 1) we propose a new method for facial feature extraction named the Compact Binary Patterns (CBP), which is a more compact and efficient generalization of Local Binary Patterns. 2) We show that Whitened Principal Component Analysis (WPCA) is a simple but very efficient way to enhance CBP features. 3) To further improve the recognition rate, we divide a face into patches and perform recognition using multiple classifiers, whose weights are estimated by a Memetic Algorithm. Our method is tested thoroughly on the FERET dataset and achieves promising results.

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Authors and Affiliations

  1. School of Computer Science, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB, UK

    Hieu V. Nguyen & Li Bai

Authors
  1. Hieu V. Nguyen
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  2. Li Bai
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Editor information

Editors and Affiliations

  1. Department of Computer Science, State University of New York at Fredonia, 14063, Fredonia, NY, USA

    Reneta P. Barneva

  2. Mathematics Department, SUNY Buffalo State College, 14222, Buffalo, NY, USA

    Valentin E. Brimkov

  3. Hauptman-Woodward Medical Research Institute, 700 Ellicott Street, 14203-110, Buffalo, NY, USA

    Herbert A. Hauptman

  4. University of Porto, Porto, Portugal

    Renato M. Natal Jorge

  5. Departamento de Engenharia Mecânica e Gestão Industrial, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    João Manuel R. S. Tavares

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© 2010 Springer-Verlag Berlin Heidelberg

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Nguyen, H.V., Bai, L. (2010). Compact Binary Patterns (CBP) with Multiple Patch Classifiers for Fast and Accurate Face Recognition. In: Barneva, R.P., Brimkov, V.E., Hauptman, H.A., Natal Jorge, R.M., Tavares, J.M.R.S. (eds) Computational Modeling of Objects Represented in Images. CompIMAGE 2010. Lecture Notes in Computer Science, vol 6026. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12712-0_17

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  • DOI: https://doi.org/10.1007/978-3-642-12712-0_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12711-3

  • Online ISBN: 978-3-642-12712-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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