Human tracking method based on improved HOG+Real AdaBoost

Daisuke Aoki, Junzo Watada

    研究成果: Conference contribution

    抜粋

    This paper proposes an object detection method that uses Histograms of Oriented Gradients (HOG) features using boosting algorithm. There has been done many research works in late years on statistical learning methods and object detection methods that associate low level of features obtained. However the proposed approach, low level of HOG features are associated by using Real AdaBoost to continuously achieve features. In this wise, it is possible to capture a shape of edge continuity, which single HOG features can't do, so highly accuracy detection is realized. This paper, to evaluate the effectiveness of the proposed method, three different experiments with different patterns are conducted for detecting humans. Moreover, a boosting classifier is used to represent the co-occurrence of HOG features appearance for detecting a human.

    元の言語English
    ホスト出版物のタイトル2015 10th Asian Control Conference: Emerging Control Techniques for a Sustainable World, ASCC 2015
    出版者Institute of Electrical and Electronics Engineers Inc.
    ISBN(印刷物)9781479978625
    DOI
    出版物ステータスPublished - 2015 9 8
    イベント10th Asian Control Conference, ASCC 2015 - Kota Kinabalu, Malaysia
    継続期間: 2015 5 312015 6 3

    Other

    Other10th Asian Control Conference, ASCC 2015
    Malaysia
    Kota Kinabalu
    期間15/5/3115/6/3

    ASJC Scopus subject areas

    • Control and Systems Engineering

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  • これを引用

    Aoki, D., & Watada, J. (2015). Human tracking method based on improved HOG+Real AdaBoost. : 2015 10th Asian Control Conference: Emerging Control Techniques for a Sustainable World, ASCC 2015 [7244780] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASCC.2015.7244780