The number of the vehicles continues to increase from year to year and cause congestion especially when there is a long holiday. The cost of installing and maintaining the recording equipment and supporting infrastructure is quite extortionate. Therefore, the calculation of speed with a flexible and inexpensive cost requires drones. The purpose of this study is to monitor the flow of traffic in areas where there is no supporting infrastructure to install traffic cameras used to calculate the speed of the vehicles during long holidays. The camera shots taken from the drones are used to detect the types of passenger cars using library of You Only Look Once (YOLO) deep learning. The detected object is then tracked by using SORT (Simple Online and Realtime Tracking) to always detect the same object and calculate the speed of the vehicle when passing the RoI (Region of Interest). On the 5, 10, and 15 meters RoI, the lowest error values are 4.79%, 4.38%, and 2.96% respectively. Each of the results was obtained at a height of 10 meters. The proposed method can prove the error calculation of speed vehicle is small when the frame rate (fps) is high, altitude is low and the distance ROI is long.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vehicle Speed Calculation from Drone Video Based on Deep Learning




    Publication date :

    2020-11-17


    Size :

    693419 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Vehicle speed calculation method based on video image

    WANG YATAO / JIANG LONG / ZHANG LEI | European Patent Office | 2024

    Free access

    Deep Learning-Based Autonomous Drone(s) Assistance

    Prithvi Krishna, C. / Bharatiraja, C. | Springer Verlag | 2021



    AERIAL VEHICLE SUCH AS HIGH SPEED DRONE

    NAKAMATS YOSHIRO | European Patent Office | 2021

    Free access

    AERIAL VEHICLE SUCH AS HIGH SPEED DRONE

    NAKAMATS YOSHIRO | European Patent Office | 2019

    Free access