Autonomous driving applications must be provided with information about other road users and road side infrastructure by object detection modules. These modules often process point clouds sensed by light detection and ranging (LiDAR) sensors. Within the captured point cloud a large amount of points correspond to physical locations on the ground. These points do not hold information about road users, obstacles or road side infrastructure. Thus an important preprocessing step is identifying ground points to allow the object detection focusing on relevant measurements only. Within this paper we propose a ground point classification which relies on simple but effective geometric features. We evaluate the accuracy of the proposed algorithm on simulated data of different traffic scenarios. In addition, we evaluate the effectiveness of this preprocessing step based on the achieved speed up of an object detection algorithm on real world data.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    3D Ground Point Classification for Automotive Scenarios


    Beteiligte:
    Nitsch, Julia (Autor:in) / Aguilar, Julio (Autor:in) / Nieto, Juan (Autor:in) / Siegwart, Roland (Autor:in) / Schmidt, Max (Autor:in) / Cadena, Cesar (Autor:in)


    Erscheinungsdatum :

    01.11.2018


    Format / Umfang :

    2447472 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Inducing and obtaining cognitive load ground truth data in automotive scenarios

    Sultana, Alina E. / Nicolae, Irina E. / Fulop, Szabolcs et al. | SPIE | 2023


    A GROUND TRUTH BUILDING APPROACH FOR EVALUATION OF GRID BASED DISCRETIZATION TECHNIQUES IN AUTOMOTIVE SCENARIOS

    Valenti, Francesco / Ghidini, Francesca / Patander, Marco et al. | British Library Conference Proceedings | 2016


    Future Automotive GNSS Positioning in Urban Scenarios

    Escher, Martin / Stanisak, Mirko / Bestmann, Ulf | British Library Conference Proceedings | 2016


    Future Scenarios for Automotive Engines in India

    Kanikdale, T. / Venugopal, S. / Society of Automotive Engineers | British Library Conference Proceedings | 2015


    Future Scenarios for Automotive Engines in India

    Venugopal, Shankar / Kanikdale, Tushar | SAE | 2015