We present a robust and real time approach to lane marker detection in urban streets. It is based on generating a top view of the road, filtering using selective oriented Gaussian filters, using RANSAC line fitting to give initial guesses to a new and fast RANSAC algorithm for fitting Bezier Splines, which is then followed by a post-processing step. Our algorithm can detect all lanes in still images of the street in various conditions, while operating at a rate of 50 Hz and achieving comparable results to previous techniques.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real time detection of lane markers in urban streets


    Beteiligte:
    Aly, Mohamed (Autor:in)


    Erscheinungsdatum :

    01.06.2008


    Format / Umfang :

    1409879 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Real time Detection of Lane Markers in Urban Streets

    Aly, M. | British Library Conference Proceedings | 2008


    Real Time Detection and Classification of Arrow Markings in Urban Streets

    Philipp, Frank / Schumacher, Sven / Tadjine, Hadj Hamma et al. | Online Contents | 2018


    Real Time Detection and Classification of Arrow Markings in Urban Streets

    Philipp, Frank / Schumacher, Sven / Tadjine, Hadj Hamma et al. | Springer Verlag | 2018


    DETERMINING OF LANE CAPACITY OF INTERCITY ROADS AND URBAN STREETS

    Nahlyuk I. / Makarychev А. / Horbachov P. et al. | DOAJ | 2018

    Freier Zugriff

    A Driver Behavior-Based Lane-Changing Model for Urban Arterial Streets

    Sun, D. / Elefteriadou, L. | British Library Online Contents | 2014