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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    Title :

    Multi-view face detection with FloatBoost


    Contributors:
    ZhenQiu Zhang, (author) / MingJing Li, (author) / Li, S.Z. (author) / HongJiang Zhang, (author)


    Publication date :

    2002-01-01


    Size :

    406393 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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