This paper details filtering subsystem for a tetravision based pedestrian detection system. The complete system is based on the use of both visible and far infrared cameras; in an initial phase it produces a list of areas of attention in the images which can contain pedestrians. This list is furtherly refined using symmetry-based assumptions. Then, this results is fed to a number of independent validators that evaluate the presence of human shapes inside the areas of attention. Histogram of oriented gradients and Support Vector Machines are used as a filter and demonstrated to be able to successfully classify up to 91% of pedestrians in the areas of attention.


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    Title :

    A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier


    Contributors:
    Bertozzi, M. (author) / Broggi, A. (author) / Rose, M. Del (author) / Felisa, M. (author) / Rakotomamonjy, A. (author) / Suard, F. (author)


    Publication date :

    2007-09-01


    Size :

    626317 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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