This paper presents a method for road detection and obstacle detection entirely based on stereovision. The ground plane is estimated online by least square fitting of disparity data. This operation allows deleting road features for obstacle detection, estimating directly camera roll and pitch, and deriving some clues on road-surface image regions. A model-based algorithm employing only disparity information is demonstrated to be able to segment the whole road surface without knowledge of infrastructures and features like lane markings. This helps navigation in suburban and country-road environments, and recovery from critical failure of lane-markings trackers.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Unified stereovision for ground, road, and obstacle detection


    Beteiligte:
    Lombardi, P. (Autor:in) / Zanin, M. (Autor:in) / Messelodi, S. (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    1140662 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Unified Stereovision for Ground, Road, and Obstacle Detection

    Lombardi, P. / Zanin, M. / Messelodi, S. et al. | British Library Conference Proceedings | 2005



    Obstacle Detection in Urban Traffic Using Stereovision

    Huang, Y. / IEEE | British Library Conference Proceedings | 2005


    Obstacle detection using sparse stereovision and clustering techniques

    Kramm, Sebastien / Bensrhair, Abdelaziz | IEEE | 2012


    Obstacle Detection Using Sparse Stereovision and Clustering Techniques

    Kramm, S. / Bensrhair, A. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2012