This paper presents a system to measure the speed of vehicles on roads. Traffic law violations are controlled by detecting over speeding vehicles. Vehicles in a video are detected, tracked and their speed is estimated. Speed estimation is performed based on camera input without any extra sensors making it cost effective. Fast Retina Key-point (FREAK) and Features from Accelerated Segment Test (FAST) algorithms are used for feature extraction. FAST and FREAK provide results rapidly and are helpful in real time applications. Time calculation for speed estimation is independent of the processor being used. Voting based classifier is used for detecting vehicles. Seven different classifiers are used in it. Random Forest provided the highest accuracy of 88.4% and F1 score of 88.5%. Proposed system provided speed estimation with an approximate error of 2 km/hr. The average percentage error obtained for the estimated speed is 9.22%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vision-Based Vehicle Speed Estimation


    Contributors:


    Publication date :

    2024-03-15


    Size :

    292983 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Vision‐based vehicle speed estimation: A survey

    Fernández Llorca, David / Hernández Martínez, Antonio / García Daza, Iván | Wiley | 2021

    Free access

    Vision‐based vehicle speed estimation: A survey

    David Fernández Llorca / Antonio Hernández Martínez / Iván García Daza | DOAJ | 2021

    Free access

    Vision-based Vehicle Speed Estimation: A Survey

    Llorca, David Fernández / Martínez, Antonio Hernández / Daza, Iván García | ArXiv | 2021

    Free access

    A Vision-Based Pipeline for Vehicle Counting, Speed Estimation, and Classification

    Liu, Chenghuan / Huynh, Du Q. / Sun, Yuchao et al. | IEEE | 2021


    HVD-Net: A Hybrid Vehicle Detection Network for Vision-Based Vehicle Tracking and Speed Estimation

    Muhammad Hassaan Ashraf / Farhana Jabeen / Hamed Alghamdi et al. | DOAJ | 2023

    Free access