To enable intelligent vehicular indoor applications highly accurate localization is required. There is a high number of different approaches which are however difficult to compare due to a lack of a common evaluation methodology. Thus, we present a testbed for vehicular indoor localization, to enable the benchmarking of different approaches under comparable conditions. As a first building block, we present a simple yet highly accurate ground truth system based on off-the-shelf infrastructure cameras and printable markers. Our employed marker detection algorithm and systematic 3-layer projection approach achieves a median accuracy of 0.48cm and 0.05 degrees for 2D position and orientation.


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    Titel :

    Testbed for automotive indoor localization


    Beteiligte:
    Becker, Daniel (Autor:in) / Thiele, Fabian (Autor:in) / Sawade, Oliver (Autor:in) / Radusch, Ilja (Autor:in)

    Kongress:

    2015


    Erscheinungsdatum :

    2015


    Format / Umfang :

    4 pages


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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