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Gait recognition using fractal scale

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Abstract

Gait is an identifying biometric feature. Video-based gait recognition has now become a new challenging topic in computer vision. In this paper, fractal scale wavelet analysis is applied to describe and automatically recognize gait. Fractal scale, which is based on wavelet analysis, represents the self-similarity of signals, and improves the flexibility of wavelet moments. It is translation, scale and rotation invariant, and has anti-noise and occlusion handling performance. Moreover, by introducing the Mallat algorithm of wavelet, it reduces the computation complexity. Experiments on three databases show that fractal scale has simple computation and is an efficient descriptor for gait recognition.

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Acknowledgments

The authors would like to thank University of South Florida and Dr. R. Gross from the Carnegie Mellon University for their help to provide the databases needed in the research. This work was supported by National High-Tech Research and Development Plan (grant No: 2001AA231031), National Key Basic Research Plan (grant No: 2004CB318000) and National Special R&D Plan for Olympic Games (grant No: 2001BA904B08).

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Authors and Affiliations

  1. Machine Vision Group, Infotech Oulu and Department of Electrical and Information Engineering, University of Oulu, P.O. Box 4500, 90014, Oulu, Finland

    Guoying Zhao

  2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, China

    Guoying Zhao & Hua Li

  3. National Research Center for Intelligent Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, China

    Guoying Zhao & Hua Li

  4. School of Mathematics Science, Beijing Normal University, Beijing, 100875, China

    Li Cui

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  1. Guoying Zhao
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  2. Li Cui
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  3. Hua Li
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Correspondence to Guoying Zhao.

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Zhao, G., Cui, L. & Li, H. Gait recognition using fractal scale. Pattern Anal Applic 10, 235–246 (2007). https://doi.org/10.1007/s10044-007-0064-z

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  • DOI: https://doi.org/10.1007/s10044-007-0064-z

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