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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Detection of parked vehicles from a radar based occupancy grid


    Contributors:


    Publication date :

    2014-06-01


    Size :

    1008944 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    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 | European Patent Office | 2016

    Free access

    Night detection of parked vehicles

    ZHANG GUOBIAO | European Patent Office | 2017

    Free access

    Night detection of parked vehicles

    ZHANG GUOBIAO / SHIH ANDREW T / SHIH ALLISON P | European Patent Office | 2016

    Free access

    Night Detection of Parked Vehicles

    ZHANG GUOBIAO | European Patent Office | 2016

    Free access