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Speed-Invariant Gait Recognition

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Signal and Image Processing for Biometrics

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 292))

Abstract

We propose a method of speed-invariant gait recognition in a unified framework of model- and appearance-based approaches. When a person changes his/her walking speed, kinematic features (e.g., stride and joint angle) are changed while static features (e.g., thigh and shin lengths) are preserved. Based on the fact, firstly, static and kinematic features are decoupled from a gait silhouette sequence by fitting a human model. Secondly, a factorization-based stride transformation model for the kinematic features is created by using a training set for multiple non recognition-target persons on multiple speeds. This model can transform the kinematic features from a gallery speed to another arbitrary probe speed. Because only the kinematic features are insufficient to achieve a high recognition performance, we therefore finally synthesize a gait silhouette sequence by combining the preserved static features and the transformed kinematic features for matching. Experiments with the OU-ISIR Gait Database show the effectiveness of the proposed method.

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Notes

  1. 1.

    Publicly available at http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitTM.html.

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Acknowledgments

This work was supported by JSPS Grant-in-Aid for Scientific Research (S) 21220003.

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Authors and Affiliations

  1. The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, Japan

    Yasushi Makihara, Akira Tsuji & Yasushi Yagi

Authors
  1. Yasushi Makihara
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  2. Akira Tsuji
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  3. Yasushi Yagi
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Corresponding author

Correspondence to Yasushi Makihara .

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Editors and Affiliations

  1. Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Jacob Scharcanski

  2. IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal

    Hugo Proença

  3. Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA

    Eliza Du

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Makihara, Y., Tsuji, A., Yagi, Y. (2014). Speed-Invariant Gait Recognition. In: Scharcanski, J., Proença, H., Du, E. (eds) Signal and Image Processing for Biometrics. Lecture Notes in Electrical Engineering, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54080-6_8

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  • DOI: https://doi.org/10.1007/978-3-642-54080-6_8

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  • Print ISBN: 978-3-642-54079-0

  • Online ISBN: 978-3-642-54080-6

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