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Spatial Histogram Features for Face Detection in Color Images

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Book cover Advances in Multimedia Information Processing - PCM 2004 (PCM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3331))

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Abstract

This paper presents a novel face detection approach in color images. We employ spatial histograms as robust features for face detection. The spatial histograms consist of marginal distribution of color image information. Facial texture and shape are preserved by the spatial histogram representation. A hierarchical classifier combining histogram matching and support vector machine is utilized to identify face and non-face. The experiments show that this approach performs an excellent capability for face detection, and it is robust to lighting changes.

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Author information

Authors and Affiliations

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

    Hongming Zhang & Debin Zhao

Authors
  1. Hongming Zhang
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  2. Debin Zhao
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Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, 113-8656, Tokyo, Japan

    Kiyoharu Aizawa

  2. IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, 242-0001, Kanagawa, Japan

    Yuichi Nakamura

  3. National Institute of Informatics, Tokyo, Japan

    Shin’ichi Satoh

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© 2004 Springer-Verlag Berlin Heidelberg

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Zhang, H., Zhao, D. (2004). Spatial Histogram Features for Face Detection in Color Images. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30541-5_47

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  • DOI: https://doi.org/10.1007/978-3-540-30541-5_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23974-1

  • Online ISBN: 978-3-540-30541-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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