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Intelligent Video Event Analysis and Understanding pp 39–67Cite as

Gait Analysis and Human Motion Tracking

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 332))

Abstract

We present a strategy based on human gait to achieve efficient tracking, recovery of ego-motion and 3-D reconstruction from an image sequence acquired by a single camera attached to a pedestrian. In the first phase, the parameters of the human gait are established by a classical frame-by-frame analysis, using an generalised least squares (GLS) technique. The gait model is non-linear, represented by a truncated Fourier series. In the second phase, this gait model is employed within a “predict-correct” framework using a maximum a posteriori, expectation maximization (MAP-EM) strategy to obtain robust estimates of the ego-motion and scene structure, while continuously refining the gait model. Experiments on synthetic and real image sequences show that the use of the gait model results in more efficient tracking. This is demonstrated by improved matching and retention of features, and a reduction in execution time, when processing video sequences.

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Author information

Authors and Affiliations

  1. Queen’s University Belfast, Belfast, United Kingdom

    Huiyu Zhou

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  1. Huiyu Zhou
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Editor information

Editors and Affiliations

  1. School of Computing, University of Dundee , DD1 4HN, Dundee, Scotland, UK

    Jianguo Zhang

  2. Department of Electronic & Electrical Engineering, The University of Sheffield, S1 3JD, Sheffield, UK

    Ling Shao

  3. Microsoft Research Asia , 49 Zhichun Road, 100190, Beijing, P.R. China

    Lei Zhang

  4. Digital Imaging Research Centre, Faculty of Computing, Information Systems and Mathematics, Kingston University, Penrhyn Road, Kingston upon Thames, KT1 2EE, Surrey, UK

    Graeme A. Jones

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Zhou, H. (2011). Gait Analysis and Human Motion Tracking. In: Zhang, J., Shao, L., Zhang, L., Jones, G.A. (eds) Intelligent Video Event Analysis and Understanding. Studies in Computational Intelligence, vol 332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17554-1_3

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  • DOI: https://doi.org/10.1007/978-3-642-17554-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17553-4

  • Online ISBN: 978-3-642-17554-1

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