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Combinatorial Optimization for Human Body Tracking

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Advances in Visual Computing (ISVC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10073))

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Abstract

We present a method of improving the accuracy of a 3D human motion tracker. Beginning with confidence-weighted estimates for the positions of body parts, we solve the shortest path problem to identify combinations of positions that fit the rigid lengths of the body. We choose from multiple sets of these combinations by predicting current positions with kinematics. We also refine this choice by using the geometry of the optional positions. Our method was tested on a data set from an existing motion tracking system, resulting in an overall increase in the sensitivity and precision of tracking. Notably, the average sensitivity of the feet rose from 52.6% to 84.8%. When implemented on a 2.9 GHz processor, the system required an average of 3.5 milliseconds per video frame.

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Author information

Authors and Affiliations

  1. Memorial University, St. John’s, Newfoundland and Labrador, Canada

    Andrew Hynes & Stephen Czarnuch

Authors
  1. Andrew Hynes
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  2. Stephen Czarnuch
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Corresponding author

Correspondence to Stephen Czarnuch .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. The Australian National University, O’Malley, Aust Capital Terr, Australia

    Fatih Porikli

  6. Pilot AI Labs, Redwood City, California, USA

    Sandra Skaff

  7. University of Florida, Gainesville, Florida, USA

    Alireza Entezari

  8. Google Inc., Mountain View, California, USA

    Jianyuan Min

  9. Osaka University, Osaka, Japan

    Daisuke Iwai

  10. The MOVES Institute, Monterey, California, USA

    Amela Sadagic

  11. University of Arizona, Tucson, Arizona, USA

    Carlos Scheidegger

  12. Université Paris-Sud, Orsay, France

    Tobias Isenberg

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© 2016 Springer International Publishing AG

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Hynes, A., Czarnuch, S. (2016). Combinatorial Optimization for Human Body Tracking. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2016. Lecture Notes in Computer Science(), vol 10073. Springer, Cham. https://doi.org/10.1007/978-3-319-50832-0_51

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  • DOI: https://doi.org/10.1007/978-3-319-50832-0_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50831-3

  • Online ISBN: 978-3-319-50832-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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