We describe the functional and architectural breakdown of a monocular pedestrian detection system. We describe in detail our approach for single-frame classification based on a novel scheme of breaking down the class variability by repeatedly training a set of relatively simple classifiers on clusters of the training set. Single-frame classification performance results and system level performance figures for daytime conditions are presented with a discussion about the remaining gap to meet a daytime normal weather condition production system.


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    Titel :

    Pedestrian detection for driving assistance systems: single-frame classification and system level performance


    Beteiligte:
    Shashua, A. (Autor:in) / Gdalyahu, Y. (Autor:in) / Hayun, G. (Autor:in)


    Erscheinungsdatum :

    2004-01-01


    Format / Umfang :

    798363 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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