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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    Title :

    A real-time system for monitoring of cyclists and pedestrians


    Contributors:
    Heikkila, J. (author) / Silven, O. (author)

    Published in:

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


    Publication date :

    2004


    Size :

    8 Seiten, 12 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    A real-time system for monitoring of cyclists and pedestrians

    Heikkila, J. / Silven, O. | British Library Online Contents | 2004


    A real-time system for monitoring of cyclists and pedestrians

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



    Underpasses for pedestrians and cyclists

    Voordt, D.J.M. Van Der / Wegen, H.B.R. Van | Taylor & Francis Verlag | 1983


    Automatic Counting of Pedestrians and Cyclists

    B. R. Pires / J. Gong / C. Kaffine et al. | NTIS | 2016