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Video-Based People Tracking

  • Chapter
Handbook of Ambient Intelligence and Smart Environments

Abstract

Vision-based human pose tracking promises to be a key enabling technology for myriad applications, including the analysis of human activities for perceptive environments and novel man-machine interfaces. While progress toward that goal has been exciting, and limited applications have been demonstrated, the recovery of human pose from video in unconstrained settings remains challenging. One of the key challenges stems from the complexity of the human kinematic structure itself. The sheer number and variety of joints in the human body (the nature of which is an active area of biomechanics research) entails the estimation of many parameters. The estimation problem is also challenging because muscles and other body tissues obscure the skeletal structure, making it impossible to directly observe the pose of the skeleton.

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Authors and Affiliations

  1. Department of Computer Science, University of Toronto, Toronto, Canada

    Marcus A. Brubaker, Leonid Sigal & David J. Fleet

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  1. Marcus A. Brubaker
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  2. Leonid Sigal
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  3. David J. Fleet
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Correspondence to Marcus A. Brubaker , Leonid Sigal or David J. Fleet .

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Editors and Affiliations

  1. Future University Hakodate, Kameda-Nakano 116-2, Hakodate, Hokkaido, 041-8655, Japan

    Hideyuki Nakashima

  2. Department of Electrical Engineering, Stanford University, 350 Serra Mall, Stanford, CA, 94305-9515, USA

    Hamid Aghajan

  3. School of Computing & Mathematics, University of Ulster at Jordanstown, Shore Road, Newtownabbey, Co. Antrim, UK, BT37 0QB

    Juan Carlos Augusto

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Brubaker, M.A., Sigal, L., Fleet, D.J. (2010). Video-Based People Tracking. In: Nakashima, H., Aghajan, H., Augusto, J.C. (eds) Handbook of Ambient Intelligence and Smart Environments. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-93808-0_3

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  • DOI: https://doi.org/10.1007/978-0-387-93808-0_3

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