Monitoring traffic intersections in real time and predicting possible collisions is an important first step towards building an early collision-warning system. We present a vision-based system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. Innovative low-overhead collision-prediction algorithms (such as the one using the time-as-axis paradigm) are presented. The proposed system was able to perform successfully in real time on videos of quarter-video graphics array (VGA) (320 /spl times/ 240) resolution under various weather conditions. The errors in target position and dimension estimates in a test video sequence are quantified and several experimental results are presented.


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    Titel :

    A vision-based approach to collision prediction at traffic intersections


    Beteiligte:
    Atev, S. (Autor:in) / Arumugam, H. (Autor:in) / Masoud, O. (Autor:in) / Janardan, R. (Autor:in) / Papanikolopoulos, N.P. (Autor:in)


    Erscheinungsdatum :

    01.12.2005


    Format / Umfang :

    312450 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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