This paper presents a novel method for traffic sign detection and visibility evaluation from mobile Light Detection and Ranging (LiDAR) point clouds and the corresponding images. Our algorithm involves two steps. Firstly, a detection algorithm based on high retro-reflectivity of the traffic sign from the MLS point clouds is designed for sign detection in complicated road scenes. To solve the spatial features of traffic signs, we also create geo-referenced relations between traffic signs and roads according to the normal of ground. Secondly, we propose a visibility estimation method to evaluate the visibility level of the traffic sign based on a combination of visual appearance and spatial-related features. The proposed algorithm is validated on a set of transportation-related point-clouds acquired by a RIEGL VMX-450 LiDAR system. The experiment results demonstrate that the efficiency and reliability of the proposed algorithm in detection traffic signs are robust, and also prove the potential of using mobile LiDAR data for traffic sign visibility evaluation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Using mobile LiDAR point clouds for traffic sign detection and sign visibility estimation


    Contributors:
    Wu, Shuang (author) / Wen, Chenglu (author) / Luo, Huan (author) / Chen, Yiping (author) / Wang, Cheng (author) / Li, Jonathan (author)


    Publication date :

    2015-07-01


    Size :

    551908 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    AUTOMATED VISIBILITY FIELD EVALUATION OF TRAFFIC SIGN BASED ON 3D LIDAR POINT CLOUDS

    S. Zhang / C. Wang / M. Cheng et al. | DOAJ | 2019

    Free access



    Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds

    Huang, Pengdi / Cheng, Ming / Chen, Yiping et al. | IEEE | 2017


    Estimation of traffic sign visibility toward smart driver assistance

    Doman, Keisuke / Deguchi, Daisuke / Takahashi, Tomokazu et al. | IEEE | 2010