Camera based systems are routinely used for monitoring highway traffic, supplementing inductive loops and microwave sensors employed for counting purposes. These techniques achieve very good counting accuracy and are capable of discriminating trucks and cars. However, pedestrians and cyclists are mostly counted manually. We describe a new camera based automatic system that utilizes Kalman filtering in tracking and learning vector quantization for classifying the observations to pedestrians and cyclists. Both the requirements for such systems and the algorithms used are described. The tests performed show that the system achieves around 80-90% accuracy in counting and classification.


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    Titel :

    A real-time system for monitoring of cyclists and pedestrians


    Beteiligte:
    Heikkila, J. (Autor:in) / Silven, O. (Autor:in)

    Erschienen in:

    Image and Vision Computing ; 22 , 7 ; 563-570


    Erscheinungsdatum :

    2004


    Format / Umfang :

    8 Seiten, 12 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    A real-time system for monitoring of cyclists and pedestrians

    Heikkila, J. / Silven, O. | Tema Archiv | 1999


    A real-time system for monitoring of cyclists and pedestrians

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