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Asian Conference on Computer Vision

ACCV 2014: Computer Vision -- ACCV 2014 pp 444–459Cite as

Tracking Multiple People Online and in Real Time

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9007))

Abstract

We cast the problem of tracking several people as a graph partitioning problem that takes the form of an NP-hard binary integer program. We propose a tractable, approximate, online solution through the combination of a multi-stage cascade and a sliding temporal window. Our experiments demonstrate significant accuracy improvement over the state of the art and real-time post-detection performance.

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Notes

  1. 1.

    Graph partitioning is often called graph clustering in the literature. We avoid this term to prevent confusion with other types of clustering we do in this paper.

  2. 2.

    The graph can be directed from past to future in time, if simultaneous observations cannot be co-identical, or undirected otherwise.

  3. 3.

    Velocity is a vector, and its norm is called the speed.

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Acknowledgements

This work was supported by the Army Research Office under Grant No. W911NF-10-1-0387 and by the National Science Foundation under Grants IIS-10-17017 and IIS-14-20894.

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Authors and Affiliations

  1. Duke University, Durham, USA

    Ergys Ristani & Carlo Tomasi

Authors
  1. Ergys Ristani
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  2. Carlo Tomasi
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Corresponding author

Correspondence to Ergys Ristani .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Ristani, E., Tomasi, C. (2015). Tracking Multiple People Online and in Real Time. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9007. Springer, Cham. https://doi.org/10.1007/978-3-319-16814-2_29

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  • DOI: https://doi.org/10.1007/978-3-319-16814-2_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16813-5

  • Online ISBN: 978-3-319-16814-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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