The paper addresses the problem of object perception for intelligent vehicle applications with main tasks of detection, tracking and classification of obstacles where multiple sensors (i.e.: lidar, camera and radar) are used. New algorithms for raw sensor data processing and sensor data fusion are introduced making the most information from all sensors in order to provide a more reliable and accurate information about objects in the vehicle environment. The proposed object perception module is implemented and tested on a demonstrator car in real-life traffics and evaluation results are presented.


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    Titel :

    Object perception for intelligent vehicle applications: A multi-sensor fusion approach


    Beteiligte:
    Vu, Trung-Dung (Autor:in) / Aycard, Olivier (Autor:in) / Tango, Fabio (Autor:in)


    Erscheinungsdatum :

    01.06.2014


    Format / Umfang :

    2320868 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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