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Face Recognition System Robust to Occlusion

  • Conference paper
Bio-Inspired Computing and Applications (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6840))

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Abstract

This paper presents an efficient face recognition system which can handle partial occlusion in both training and test image sets. We hybridize Gabor filter with Eigen faces which make use of localization effect of Gabor filter and whole appearance effect of Eigen faces. It has been tested on AR database which contains naturally occluded face images.

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References

  1. Fidler, S., Skocaj, D., Leonardis, A.: Combining reconstructive and discriminative subspace methods for robust classification and regression by subsampling. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(3), 337–350 (2006)

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  2. Jia, H., Martinez, A.M.: Face recognition with occlusions in the training and testing sets. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 1–6 (2008)

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  4. Martinez, A., Benavente, R.: The ar face database. Tech. Rep. 24, Computer Vision Center, Bellatera (1998), http://www.cat.uab.cat/Publications/1998/MB98

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, 208016, India

    Mohit Sharma, Surya Prakash & Phalguni Gupta

Authors
  1. Mohit Sharma
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  2. Surya Prakash
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  3. Phalguni Gupta
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, 2522, P.O. Box, North Wollongong, NSW, Australia

    Prashan Premaratne

  4. School of Computer Science and Engineering, Inha University, 402-751, Inchon, Korea

    Kyungsook Han

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© 2012 Springer-Verlag Berlin Heidelberg

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Sharma, M., Prakash, S., Gupta, P. (2012). Face Recognition System Robust to Occlusion. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_80

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  • DOI: https://doi.org/10.1007/978-3-642-24553-4_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24552-7

  • Online ISBN: 978-3-642-24553-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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