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Recognizing Human Motion Using Parameterized Models of Optical Flow

  • Chapter
Motion-Based Recognition

Part of the book series: Computational Imaging and Vision ((CIVI,volume 9))

Abstract

The tracking and recognition of human motion is a challenging problem with diverse applications in virtual reality, medicine, teleoperations, animation, and human-computer interaction to name a few. The study of human motion has a long history with the use of images for analyzing animate motion beginning with the improvements in photography and the development of motion-pictures in the late nineteenth century. Scientists and artists such as Marey [12] and Muybridge [26] were early explorers of human and animal motion in images and image sequences. Today, commercial motion-capture systems can be used to accurately record the 3D movements of an instrumented person, but the motion analysis and motion recognition of an arbitrary person in a video sequence remains an unsolved problem. In this chapter we describe the representation and recognition of human motion using parameterized models of optical flow. A person’s limbs, face, and facial features are represented as patches whose motion In a image sequence can be modeled by low-order polynomials. A robust optical flow estimation technique is used to recover the motion of these patches and the recovered motion parameters provide a rich, yet concise, description of the human motion which can be used to recognize human activities, gestures, and facial expressions.

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Author information

Authors and Affiliations

  1. Xerox Palo Alto Research Center, Palo Alto, CA, 94304, USA

    Michael J. Black

  2. Computer Vision Laboratory, Center for Automation Research University of Maryland, College Park, MD, 20742, USA

    Yaser Yacoob

  3. Department of Computer Science, University of Toronto, Toronto, Ontario, M5S 1A4, Canada

    Shanon X. Ju

Authors
  1. Michael J. Black
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  2. Yaser Yacoob
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  3. Shanon X. Ju
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Editor information

Editors and Affiliations

  1. Computer Vision Laboratory, Computer Science Department, University of Central Florida, 32816, Orlando, Florida, USA

    Mubarak Shah

  2. Electrical and Computer Engineering, University of California, San Diego, 92137, San Diego, California, USA

    Ramesh Jain

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© 1997 Springer Science+Business Media Dordrecht

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Black, M.J., Yacoob, Y., Ju, S.X. (1997). Recognizing Human Motion Using Parameterized Models of Optical Flow. In: Shah, M., Jain, R. (eds) Motion-Based Recognition. Computational Imaging and Vision, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8935-2_11

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  • DOI: https://doi.org/10.1007/978-94-015-8935-2_11

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4870-7

  • Online ISBN: 978-94-015-8935-2

  • eBook Packages: Springer Book Archive

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