Traffic signs recognition is a basic task for autonomous vehicle. Among the numerous traffic signs, traffic cone is a very important mark used to guide cars where to go. A method based on vision and radar sensors information fusion is proposed to detect traffic cone in this paper. The algorithm mainly includes two parts: finding where the obstacle is in the image and recognizing whether it is a cone. We use homography to calibrate camera and radar, from which the radar data can be mapped on the image and a small corresponding image patch can be easily cutout. Then, a method based on contour feature called chamfer matching is used to determine whether the obstacle in the image patch is a cone. The approach has been tested on our autonomous vehicle, which shows it can guarantee both effectiveness and instantaneity.


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    Title :

    Real-time traffic cone detection for autonomous vehicle


    Contributors:
    Yong, Huang (author) / Jianru, Xue (author)


    Publication date :

    2015-07-01


    Size :

    855373 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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