In this paper, a self-contained system that is capable of precisely recognizing traffic data in real-time is designed and tested. This system detects the range and velocity of objects using a high-frequency automotive radar module. The system also records a video stream and employs a YOLOv3 detection algorithm using the COCO dataset to identify, label, and track different classes of vehicles and pedestrians. The fusion of these two sensor systems combines the benefits of both the radar’s accuracy and the camera’s object detection. The final design is deployed in a real-world environment and validated against collected ground-truth data. The system is capable of providing traffic information accurately.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Sensor Fusion for Traffic Monitoring Using Camera, Radar, and ROS


    Contributors:


    Publication date :

    2022-08-11


    Size :

    11848398 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    CAMERA-RADAR FUSION USING CORRESPONDENCES

    MICHIELIN FRANCESCO / VOGEL OLIVER | European Patent Office | 2023

    Free access

    In-cabin radar and camera fusion sensor module

    KWON RAK BEOM / SHIN DOO SUNG / JUNG JAE HOON et al. | European Patent Office | 2024

    Free access

    A Camera-LiDAR Fusion Framework for Traffic Monitoring

    Sochaniwsky, Adrian / Huangfu, Yixin / Habibi, Saeid et al. | IEEE | 2024


    Traffic vehicle detection by fusion of millimeter wave radar and camera

    Zhang, Wentao / Liu, Kun / Li, Heng | IEEE | 2022


    Traffic Incident Detection Based on mmWave Radar and Improvement Using Fusion with Camera

    Zhimin Tao / Yanbing Li / Pengcheng Wang et al. | DOAJ | 2022

    Free access