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Multi-Kernel Fuzzy-Based Local Gabor Patterns for Gait Recognition

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Advances in Visual Computing (ISVC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10072))

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Abstract

This paper proposes a novel multi-kernel fuzzy-based local Gabor binary patterns method (MFLGBP) for the purpose of gait representation and recognition. First, we construct the gait energy image (GEI) from mean motion cycle of a gait sequence. Then, we apply Gabor filters and encode the variations in the Gabor magnitude by using a kernel-based fuzzy local binary pattern (KFLBP) operator. Finally, classification is performed using a support vector machine (SVM). Experiments are carried out using the benchmark CASIA B gait database. Our proposed feature extraction method has shown promising performance in terms of correct recognition rate as compared to other methods.

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Acknowledgment

The authors would like to thank King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, for the support during this work. The first author would also like to thank Hadhramout Establishment for Human Development (HEHD) for supporting him during the master degree.

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Authors and Affiliations

  1. Information and Computer Science Department, College of Computer Sciences and Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Amer G. Binsaadoon & El-Sayed M. El-Alfy

Authors
  1. Amer G. Binsaadoon
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  2. El-Sayed M. El-Alfy
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Corresponding author

Correspondence to El-Sayed M. El-Alfy .

Editor information

Editors and Affiliations

  1. University of Nevada , Reno, Nevada, USA

    George Bebis

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

    Richard Boyle

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

    Bahram Parvin

  4. Desert Research Institute , Reno, Nevada, USA

    Darko Koracin

  5. The Australian National University , O'Malley, Aust Capital Terr, Australia

    Fatih Porikli

  6. Pilot AI Labs , Redwood City, California, USA

    Sandra Skaff

  7. University of Florida , Gainesville, Florida, USA

    Alireza Entezari

  8. Google Inc. , Mountain View, California, USA

    Jianyuan Min

  9. Osaka University , Osaka, Japan

    Daisuke Iwai

  10. The MOVES Institute , Monterey, California, USA

    Amela Sadagic

  11. University of Arizona , Tucson, Arizona, USA

    Carlos Scheidegger

  12. Université Paris-Sud , Orsay, France

    Tobias Isenberg

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Binsaadoon, A.G., El-Alfy, ES.M. (2016). Multi-Kernel Fuzzy-Based Local Gabor Patterns for Gait Recognition. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10072. Springer, Cham. https://doi.org/10.1007/978-3-319-50835-1_71

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  • DOI: https://doi.org/10.1007/978-3-319-50835-1_71

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50834-4

  • Online ISBN: 978-3-319-50835-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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