The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night. The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions. The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness.


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    Title :

    Image analysis and rule-based reasoning for a traffic monitoring system


    Contributors:
    Cucchiara, R. (author) / Piccardi, M. (author) / Mello, P. (author)


    Publication date :

    2000


    Size :

    12 Seiten, 30 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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    Cucchiara, R. / Piccardi, M. / Mello, P. | British Library Online Contents | 2000


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