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Asymmetry-Based Quality Assessment of Face Images

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Book cover Advances in Visual Computing (ISVC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5876))

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Abstract

Quality assessment plays an important role in biometrics field. Unlike the popularity of fingerprint and iris quality assessment, the evaluation of face quality is just started. To solve the incapability for performance prediction and remove the requirement for scale normalization of existing methods, three face quality measures are proposed in this paper. SIFT is utilized to extract scale insensitive feature points on face images, and three asymmetry-based quality measures are calculated by applying different constraints. Systematical experiments validate the efficacy of the proposed quality measures.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Beihang University,  

    Guangpeng Zhang & Yunhong Wang

Authors
  1. Guangpeng Zhang
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  2. Yunhong Wang
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, 338-8570, Japan

    Yoshinori Kuno

  6. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  7. Univ. of Zurich, Department of Informatics, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  8. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  9. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  10.  ,  

    Miguel L. Encarnação

  11. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  12. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

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© 2009 Springer-Verlag Berlin Heidelberg

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Zhang, G., Wang, Y. (2009). Asymmetry-Based Quality Assessment of Face Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_47

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  • DOI: https://doi.org/10.1007/978-3-642-10520-3_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10519-7

  • Online ISBN: 978-3-642-10520-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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