Non-intrusive video-detection for traffic flow observation and surveillance is the primary alternative to conventional inductive loop detectors. Video image detection systems (VIDS) can derive traffic parameters by means of image processing and pattern recognition methods. Existing VIDS emulate the inductive loops. The authors propose a trajectory based recognition algorithm to expand the common approach and to obtain new types of information (e.g. queue length or erratic movements). Different views of the same area by more than one camera sensor are necessary, because of the typical limitations of single camera systems, resulting from occlusions by other cars, trees and traffic signs. A distributed cooperative multi-camera system enables a significant enlargement of the observation area. The trajectories are derived from multi-target tracking. The fusion of object data from different cameras will be done by a tracking approach. This approach opens up opportunities to identify and specify traffic objects, their location, speed and other characteristic object information. The system creates new derived and consolidated information of traffic participants. Thus, also descriptions of individual traffic participants are possible.


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    Title :

    Multi-camera detection and multi-target tracking. Traffic surveillance applications


    Additional title:

    Multi-Kamera-Detektion und Multi-Targetverfolgung. Verkehrsüberwachungsanwendung


    Contributors:
    Reulke, R. (author) / Bauer, S. (author) / Döring, T. (author) / Spangenberg, R. (author)


    Publication date :

    2008


    Size :

    7 Seiten, 9 Bilder, 21 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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