In this paper, we detail a complete software architecture of a key task that an intelligent vehicle has to deal with: frontal object perception. This task is solved by processing raw data of a radar and a mono-camera to detect and track moving objects. Data sets obtained from highways, country roads and urban areas were used to test the proposed method. Several experiments were conducted to show that the proposed method obtains a better environment representation, i.e., reduces the false alarms and missed detections from individual sensor evidence.


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    Title :

    Frontal object perception using radar and mono-vision


    Contributors:


    Publication date :

    2012-06-01


    Size :

    1305362 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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