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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    Titel :

    Improving driver pose estimation


    Beteiligte:
    Watta, P. (Autor:in) / Yulin Hou, (Autor:in) / Lakshmanan, S. (Autor:in) / Natarajan, N. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    315249 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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