In this paper, we consider the problem of estimating the pose of a driver from video data. We propose extensions to our previous eigenface and Fisherface-based methods to improve classification performance. In particular, a hybrid neural network/nearest neighbor algorithm is formulated for classification of frames. Experimental results show that the hybrid neural network outperforms the nearest neighbor classifier.


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    Title :

    Improving driver pose estimation


    Contributors:
    Watta, P. (author) / Yulin Hou, (author) / Lakshmanan, S. (author) / Natarajan, N. (author)

    Published in:

    Publication date :

    2002-01-01


    Size :

    315249 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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