While short range 3D pedestrian detection is sufficient for emergency breaking, long range detections are required for smooth breaking and gaining trust in autonomous vehicles. The current state-of-the-art on the KITTI benchmark performs suboptimal in detecting the position of pedestrians at long range. Thus, we propose an approach specifically targeting long range 3D pedestrian detection (LRPD), leveraging the density of RGB and the precision of LiDAR. Therefore, for proposals, RGB instance segmentation and LiDAR point based proposal generation are combined, followed by a second stage using both sensor modalities symmetrically. This leads to a significant improvement in mAP on long range compared to the current state-of-the art. The evaluation of our LRPD approach was done on the pedestrians from the KITTI benchmark.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB


    Contributors:


    Publication date :

    2020-09-20


    Size :

    2871334 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Context-aware pedestrian detection using LIDAR

    Oliveira, L / Nunes, U | IEEE | 2010


    CNN-LIDAR pedestrian classification: combining range and reflectance data

    Melotti, Gledson / Asvadi, Alireza / Premebida, Cristiano | IEEE | 2018


    LIDAR and vision-based pedestrian detection system

    Premebida, C. / Ludwig, O. / Nunes, U. | British Library Online Contents | 2009


    Density Enhancement-Based Long-Range Pedestrian Detection Using 3-D Range Data

    Li, Keqiang / Wang, Xiao / Xu, Youchun et al. | IEEE | 2016