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Face Recognition Based on Efficient Facial Scale Estimation

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Articulated Motion and Deformable Objects (AMDO 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2492))

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Abstract

Facial recognition technology needs to be robust for arbitrary facial appearances because a face changes according to facial expressions and facial poses. In this paper, we propose a method which automatically performs face recognition for variously scaled facial images. The method performs flexible feature matching using features normalized for facial scale. For normalization, the facial scale is probabilistically estimated and is used as a scale factor of an improved Gabor wavelet transformation. We implement a face recognition system based on the proposed method and demonstrate the advantages of the system through facial recognition experiments. Our method is more efficient than any other and can maintain a high accuracy of face recognition for facial scale variations.

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Authors and Affiliations

  1. Graduate School of Engineering Science, Osaka University, 1-3, Machikaneyama, Toyonaka, Osaka, 560-8531, Japan

    Takatsugu Hirayama, Yoshio Iwai & Masahiko Yachida

Authors
  1. Takatsugu Hirayama
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  2. Yoshio Iwai
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  3. Masahiko Yachida
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Maths, Computer Science Engineering School (EPS-UIB), C/Valldemossa km 7.5, PC 07071, Palma de Mallorca, Baleares, Spain

    Francisco José Perales (Director, Computer Graphics and Vision Group, Sub-Director) (Director, Computer Graphics and Vision Group, Sub-Director)

  2. Department of Computer Science, University of York, YO1 5DD, York, UK

    Edwin R. Hancock

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© 2002 Springer-Verlag Berlin Heidelberg

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Hirayama, T., Iwai, Y., Yachida, M. (2002). Face Recognition Based on Efficient Facial Scale Estimation. In: Perales, F.J., Hancock, E.R. (eds) Articulated Motion and Deformable Objects. AMDO 2002. Lecture Notes in Computer Science, vol 2492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36138-3_17

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  • DOI: https://doi.org/10.1007/3-540-36138-3_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00149-2

  • Online ISBN: 978-3-540-36138-1

  • eBook Packages: Springer Book Archive

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