Robust human tracking using statistical human shape model with postural variation

Kiyoshi Hashimoto, Hirokatsu Kataoka, Yoshimitsu Aoki, Yuji Sato

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Human tracking in monocular image sequences has been studied in the field of computer vision for many kinds of applications such as surveillance system, intelligent room, sports video analysis and so on. Human tracking in real environment is challenging topic due to various factors such as illumination change, partial or almost complete occlusion of human body, and wide variety of body shapes. In this paper, we present a robust human tracking using statistical human shape model of appearance variation with postural change. Our part-based statistical human model can generate learned appearances of main human poses, and enables effective and robust human tracking with simple features such silhouette, edge and color. Our proposed method achieves human tracking robust not only to partial occlusion but also to postural change. The experimental results validate the robustness of our methods in the real indoor environments.

    Original languageEnglish
    Title of host publicationProceedings, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society
    Pages2478-2483
    Number of pages6
    DOIs
    Publication statusPublished - 2013 Dec 1
    Event39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013 - Vienna, Austria
    Duration: 2013 Nov 102013 Nov 14

    Publication series

    NameIECON Proceedings (Industrial Electronics Conference)

    Other

    Other39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013
    CountryAustria
    CityVienna
    Period13/11/1013/11/14

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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  • Cite this

    Hashimoto, K., Kataoka, H., Aoki, Y., & Sato, Y. (2013). Robust human tracking using statistical human shape model with postural variation. In Proceedings, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society (pp. 2478-2483). [6699520] (IECON Proceedings (Industrial Electronics Conference)). https://doi.org/10.1109/IECON.2013.6699520