Robust human tracking using statistical human shape model with postural variation

Kiyoshi Hashimoto, Hirokatsu Kataoka, Yoshimitsu Aoki, Yuji Sato

    研究成果: Conference contribution

    抄録

    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.

    本文言語English
    ホスト出版物のタイトルProceedings, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society
    ページ2478-2483
    ページ数6
    DOI
    出版ステータスPublished - 2013 12 1
    イベント39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013 - Vienna, Austria
    継続期間: 2013 11 102013 11 14

    出版物シリーズ

    名前IECON Proceedings (Industrial Electronics Conference)

    Other

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

    ASJC Scopus subject areas

    • 制御およびシステム工学
    • 電子工学および電気工学

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