The precise map is the main provider of static environment information for the intelligent vehicles. Therefore, it is considered as a fundamental requirement for such systems. The accuracy of Mobile Mapping Systems (MMS), one of the main vehicle-based 3D laser scanning technologies, is significantly degraded due to the blockage of GPS signals in deep urban areas where tall buildings are surrounding streets. Existing solutions for the adjustment of the MMS data which require a manual measurement of the Ground Control Points (GCP) are labor-intensive and costly. In this paper, a fully-automatic framework for the calibration of the MMS is presented which corrects the 3D laser scanning data based on the road markings extracted from the aerial surveillance data. The proposed framework consists of three main steps: road marking extraction from aerial data, road marking extraction from the MMS point cloud, and the registration of the MMS road markings to the aerial reference. For the registration, a method based on the dynamic sliding window is introduced. The experimental results of the Hitotsubashi intersection in Tokyo demonstrate that the proposed method is practical for the MMS calibration in the urban area and it could achieve a pixel-level accuracy, where the Ground Sampling Distance (GSD) of the airborne image was 12cm.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic calibration of 3D mobile laser scanning using aerial surveillance data for precise urban mapping


    Beteiligte:
    Javanmardi, M. (Autor:in) / Javanmardi, E. (Autor:in) / Gu, Y. (Autor:in) / Kamijo, S. (Autor:in)


    Erscheinungsdatum :

    2017-06-01


    Format / Umfang :

    2503358 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Precise mobile laser scanning for urban mapping utilizing 3D aerial surveillance data

    Javanmardi, Mahdi / Javanmardi, Ehsan / Gu, Yanlei et al. | IEEE | 2017


    Unmanned Aerial Solution for Ecological Mapping Surveillance

    Tiwari, Anawil / Neigapula, Keerthana / Devi, Monisha et al. | SAE Technical Papers | 2022



    Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data

    Yu, Yongtao / Li, Jonathan / Guan, Haiyan et al. | IEEE | 2015


    Providing automatic dependent surveillance-broadcast data for unmanned aerial vehicles

    X / EVANS JONATHAN / FANELLI MATT | Europäisches Patentamt | 2020

    Freier Zugriff