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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    Title :

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


    Contributors:
    Shashua, A. (author) / Gdalyahu, Y. (author) / Hayun, G. (author)


    Publication date :

    2004-01-01


    Size :

    798363 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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