This paper presents a monocular machine vision system capable of detecting vehicles in front or behind of our own vehicle. The system consists of two main steps: 1) generation of candidates with respect to a vehicle by analyzing textures, 2) verification of the candidates by an appearance-based method using the AdaBoost learning algorithm. The vehicle candidates are generated by exploiting the facts that a vehicle has vertical and horizontal lines, and furthermore the rear and frontal shapes of a vehicle show symmetry. The proposed system is proven to be effective through experiments under various traffic scenarios.


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    Titel :

    Vehicle detection by edge-based candidate generation and appearance-based classification


    Beteiligte:
    Song, Gwang Yul (Autor:in) / Lee, Ki Yong (Autor:in) / Lee, Joon Woong (Autor:in)


    Erscheinungsdatum :

    2008-06-01


    Format / Umfang :

    741334 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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