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Asian Conference on Computer Vision

ACCV 2012: Computer Vision – ACCV 2012 pp 639–651Cite as

Semantic Pixel Sets Based Local Binary Patterns for Face Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7725))

Abstract

Feature extraction plays an important role in face recognition. Based on local binary patterns (LBP), we propose a novel face representation method which obtains histograms of semantic pixel sets based LBP (spsLBP) with a robust code voting (rcv). By clustering according the semantic pixel relations before the histogram estimation, the spsLBP makes better use of the spatial information over the original LBP. In this paper, we use a simple rule to use the semantic information. We cluster by the pixel intensity values, which is also invariant to monotonic grayscale changes, and it is in particular very useful when there are occlusions and expression variations on face images. Besides, the proposed representation adopts a new code voting strategy for LBP histogram computation, which makes it more robust. The proposed method is evaluated on three widely used face recognition databases: AR, FERET and LFW. Experimental results show that the proposed method can outperform the original uniform LBP and its extensions.

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Author information

Authors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Science, P.O. Box 2728, Beijing, 100080, P.R. China

    Zhenhua Chai, Ran He, Zhenan Sun & Tieniu Tan

  2. Advanced Technologies Application Center, 7th Avenue #21812 b/ 218 and 222, P.C. 12200, Playa, Havana, Cuba

    Heydi Mendez-Vazquez

Authors
  1. Zhenhua Chai
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  2. Heydi Mendez-Vazquez
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  3. Ran He
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  4. Zhenan Sun
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  5. Tieniu Tan
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 151-744, Seoul, Korea

    Kyoung Mu Lee

  2. Microsoft Research Asia, No. 5, Danling st., Haidian district, 100080, Beijing, P.R. China

    Yasuyuki Matsushita

  3. School of Interactive Computing, Georgia Institute of Technology, 801 Atlantic Drive, CCB 315, 30332, Atlanta, GA, USA

    James M. Rehg

  4. Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Zhong Quan Cun East Road 95, Haidian District, 100 190, Beijing, P.R. China

    Zhanyi Hu

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© 2013 Springer-Verlag Berlin Heidelberg

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Chai, Z., Mendez-Vazquez, H., He, R., Sun, Z., Tan, T. (2013). Semantic Pixel Sets Based Local Binary Patterns for Face Recognition. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37444-9_50

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  • DOI: https://doi.org/10.1007/978-3-642-37444-9_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37443-2

  • Online ISBN: 978-3-642-37444-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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