Support vector machines have shown great potential for learning classification functions that can be applied to object recognition. In this work, we extend SVMs to model the 2D appearance of human faces which undergo nonlinear change across the view sphere. The model enables simultaneous multi-view face detection and pose estimation at near-frame rate.


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    Title :

    Multi-view face detection and pose estimation using a composite support vector machine across the view sphere


    Contributors:
    Ng, J. (author) / Shaogang Gong (author)


    Publication date :

    1999-01-01


    Size :

    1124263 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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