In this paper, a new boosting algorithm, called FloatBoost, is proposed to construct a strong face-nonface classifier. FloatBoost incorporates the idea of Floating Search into AdaBoost, and yields similar or higher classification accuracy than AdaBoost with a smaller number of weak classifiers. We also present a novel framework for fast multi-view face detection. A detector-pyramid architecture is designed to quickly discard a vast number of non-face sub-windows and hence perform multi-view face detection efficiently. This results in the first real-time multi-view face detection system which runs at 5 frames per second for 320x240 image sequence.


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    Titel :

    Multi-view face detection with FloatBoost


    Beteiligte:
    ZhenQiu Zhang, (Autor:in) / MingJing Li, (Autor:in) / Li, S.Z. (Autor:in) / HongJiang Zhang, (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    406393 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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