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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    Titel :

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


    Beteiligte:
    Bertozzi, M. (Autor:in) / Broggi, A. (Autor:in) / Rose, M. Del (Autor:in) / Felisa, M. (Autor:in) / Rakotomamonjy, A. (Autor:in) / Suard, F. (Autor:in)


    Erscheinungsdatum :

    2007-09-01


    Format / Umfang :

    626317 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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