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Chinese Conference on Pattern Recognition

CCPR 2014: Pattern Recognition pp 325–334Cite as

Eye Localization Based on Multi-Channel Correlation Filter Bank

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Part of the Communications in Computer and Information Science book series (CCIS,volume 483)

Abstract

Accurate eye localization plays a key role in many face analysis related applications. In this paper, we propose a novel eye localization framework with a group of trained filter arrays called multi-channel correlation filter bank (MCCFB). Each filter array in the bank suits to a different face condition, thus combining these filter array can locate eyes more precisely for variable poses, appearances and illuminations when comparing to single filter/filter array. To demonstrate the performance of our strategy, MCCFB is compared to other eye localization methods, experimental results show superiority of our method in detection ratio, localization accuracy and robustness.

Keywords

  • Eye localization
  • Correlation Filter
  • Filter Bank
  • Multi- channel
  • Regression
  • Biometric Security

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  • DOI: 10.1007/978-3-662-45646-0_33
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Author information

Authors and Affiliations

  1. State Key Laboratory of Information Security, IIE, CAS, China

    Rui Yang, Shiming Ge, Kaixuan Xie & Shuixian Chen

  2. Beijing Key Laboratory of IOT Information Security Technology, IIE, CAS, China

    Rui Yang, Shiming Ge, Kaixuan Xie & Shuixian Chen

  3. University of Chinese Academy of Sciences, China

    Rui Yang & Kaixuan Xie

Authors
  1. Rui Yang
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  2. Shiming Ge
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  3. Kaixuan Xie
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  4. Shuixian Chen
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Editor information

Editors and Affiliations

  1. College of Electrical and Information Engineering, Hunan University, 410082, Changsha, P.R. China

    Shutao Li

  2. Chinese Academy of Sciences, Beijing, China

    Chenglin Liu

  3. College of electrical and information engineering, Hunan University, 410082, Changsha, P.R. China

    Yaonan Wang

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Yang, R., Ge, S., Xie, K., Chen, S. (2014). Eye Localization Based on Multi-Channel Correlation Filter Bank. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_33

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  • DOI: https://doi.org/10.1007/978-3-662-45646-0_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45645-3

  • Online ISBN: 978-3-662-45646-0

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