For survey and maintenance of traffic signs, this paper presents a novel traffic sign occlusion detection method using 3-D point clouds and trajectory data acquired by a mobile laser scanning system. To produce a maintenance guide, our method aims to obtain the degree of occlusion by analyzing the spatial relationship between traffic signs, surroundings, and drivers on the road. First, a detection method considering both reflectance and geometric features is developed to capture traffic signs. Next, to simulate the driver’s view, a trajectory-based method is proposed to determine driver’s observation location and the corresponding observed traffic sign. Finally, to determine whether a traffic sign is in occlusion, a hidden point removal algorithm is adopted and carried out. Furthermore, we develop two indices to evaluate the degree of occlusion. The proposed method is tested using two point cloud data sets collected by an RIEGL VMX-450 system along a 23.68-km-long urban road. The obtained results illustrate the feasibility of the proposed occlusion detection method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds


    Beteiligte:
    Huang, Pengdi (Autor:in) / Cheng, Ming (Autor:in) / Chen, Yiping (Autor:in) / Luo, Huan (Autor:in) / Wang, Cheng (Autor:in) / Li, Jonathan (Autor:in)


    Erscheinungsdatum :

    01.09.2017


    Format / Umfang :

    2572268 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    Road extraction from mobile laser scanning point clouds

    Tao, Wang | British Library Conference Proceedings | 2022


    3D Highway Curve Reconstruction From Mobile Laser Scanning Point Clouds

    Zhang, Zongliang / Li, Jonathan / Guo, Yulan et al. | IEEE | 2020