Detecting the road geometry at night time is an essential precondition to provide optimal illumination for the driver and the other traffic participants. In this paper we propose a novel approach to estimate the current road curvature based on three sensors: A far infrared camera, a near infrared camera and an imaging radar sensor. Various Convolutional Neural Networks with different configuration are trained for each input. By fusing the classifier responses of all three sensors, a further performance gain is achieved. To annotate the training and evaluation dataset without costly human interaction a fully automatic curvature annotation algorithm based on inertial navigation system is presented as well.


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    Title :

    Night time road curvature estimation based on Convolutional Neural Networks


    Contributors:


    Publication date :

    2013-06-01


    Size :

    787296 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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