This paper presents a lane estimation technique based on the particle filter framework, which fuses several image-based cues (edges, lane markings and curbs), and 3D cues extracted from stereovision. A partition sampling-like approach is used to decouple pitch estimation from the rest of the parameter set, allowing the use of a significantly lower number of particles, and initialization samples are used for faster handling of discontinuous roads. We also introduce a measure for detection quality, for result validation. The resulted solution has proven to be a reliable and fast lane detector for difficult scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A stereovision-based probabilistic lane tracker for difficult road scenarios


    Beteiligte:


    Erscheinungsdatum :

    2008-06-01


    Format / Umfang :

    766676 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    A Stereovision-Based Probabilistic Lane Tracker for Difficult Road Scenarios

    Danescu, R.G. / Nedevschi, S. / Meinecke, M.-M. et al. | British Library Conference Proceedings | 2008




    Stereovision-based road boundary detection for intelligent vehicles in challenging scenarios

    Guo, Chunzhao / Mita, Seiichi / McAllester, David | Tema Archiv | 2009


    3D lane detection system based on stereovision

    Nedevschi, S. / Schmidt, R. / Graf, T. et al. | IEEE | 2004