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.
Night time road curvature estimation based on Convolutional Neural Networks
2013-06-01
787296 byte
Conference paper
Electronic Resource
English
NIGHT TIME ROAD CURVATURE ESTIMATION BASED ON CONVOLUTIONAL NEURAL NETWORKS
British Library Conference Proceedings | 2013
|CONVOLUTIONAL NEURAL NETWORKS FOR NIGHT-TIME ANIMAL ORIENTATION ESTIMATION
British Library Conference Proceedings | 2013
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