For autonomous parking applications to become possible, knowledge about the parking environment is required. Therefore, a real-time algorithm for detecting parked vehicles from radar data is presented. These data are first accumulated in an occupancy grid from which objects are detected by applying techniques borrowed from the computer vision field. Two random forest classifiers are trained to recognize two categories of objects: parallel-parked vehicles and cross-parked vehicles. Performances of the classifiers are evaluated as well as the capacity of the complete system to detect parked vehicles in real world scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Detection of parked vehicles from a radar based occupancy grid


    Beteiligte:
    Dube, Renaud (Autor:in) / Hahn, Markus (Autor:in) / Schutz, Markus (Autor:in) / Dickmann, Jurgen (Autor:in) / Gingras, Denis (Autor:in)


    Erscheinungsdatum :

    2014-06-01


    Format / Umfang :

    1008944 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    DETECTION OF PARKED VEHICLES FROM A RADAR BASED OCCUPANCY GRID

    Dube, R. / Hahn, M. / Schutz, M. et al. | British Library Conference Proceedings | 2014


    Night Detection of Parked Vehicles

    ZHANG GUOBIAO | Europäisches Patentamt | 2016

    Freier Zugriff

    Night detection of parked vehicles

    ZHANG GUOBIAO | Europäisches Patentamt | 2017

    Freier Zugriff

    Night detection of parked vehicles

    ZHANG GUOBIAO / SHIH ANDREW T / SHIH ALLISON P | Europäisches Patentamt | 2016

    Freier Zugriff

    Night Detection of Parked Vehicles

    ZHANG GUOBIAO | Europäisches Patentamt | 2016

    Freier Zugriff