This paper describes a vehicle detection system fusing radar and vision data. Radar data are used to locate areas of interest on images. Vehicle search in these areas is mainly based on vertical symmetry. All the vehicles found in different image areas are mixed together, and a series of filters is applied in order to delete false detections. In order to speed up and improve system performance, guard rail detection and a method to manage overlapping areas are also included. Both methods are explained and justified in this paper. The current algorithm analyzes images on a frame-by-frame basis without any temporal correlation. Two different statistics, namely: 1) frame based and 2) event based, are computed to evaluate vehicle detection efficiency, while guard rail detection efficiency is computed in terms of time savings and correct detection rates. Results and problems are discussed, and directions for future enhancements are provided


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    Title :

    Vehicle and Guard Rail Detection Using Radar and Vision Data Fusion


    Contributors:
    Alessandretti, G. (author) / Broggi, A. (author) / Cerri, P. (author)


    Publication date :

    2007-03-01


    Size :

    1382480 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Vehicle and Guard Rail Detection Using Radar and Vision Data Fusion

    Alessandretti, G. / Broggi, A. / Cerri, P. | British Library Conference Proceedings | 2007


    Vehicle and guard rail detection using radar and vision data fusion

    Alessandretti, G. / Broggi, A. / Cerri, P. | Tema Archive | 2007


    Guard Rail Detection Using Radar and Vision Data Fusion for Vehicle Detection Algorithm Improvement and Speed-Up

    Broggi, A. / Cerri, P. / Oleari, F. et al. | British Library Conference Proceedings | 2005