Lots of rear end collisions due to driver inattention have been identified as a major automotive safety issue. A short advance warning can reduce the number and severity of the rear end collisions. This paper describes a Forward Collision Warning (FCW) system based on monocular vision, and presents a new vehicle detection method: appearance-based hypothesis generation, template tracking-based hypothesis verification which can remove false positive detections and automatic image matting for detection refinement. The FCW system uses time to collision (TTC) to trigger the warning.In order to compute time to collision (TTC), firstly, haar and adaboost algorithm is utilized to detect the vehicle; Secondly, we use simplified Lucas-Kanade algorithm and virtual edge to remove false positive detection and use automatic image matting to do detection refinement; Thirdly, hierarchical tracking system is introduced for vehicle tracking; Camera calibration is utilized to get the headway distance and TTC at last. The use of a single low cost camera results in an affordable system which is simple to install. The FCW system has been tested in outdoor environment, showing robust and accurate performance.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vehicle localisation using a single camera


    Contributors:
    Jianzhu Cui, (author) / Fuqiang Liu, (author) / Zhipeng Li, (author) / Zhen Jia, (author)


    Publication date :

    2010-06-01


    Size :

    1172352 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Vehicle Localisation Using a Single Camera, pp. 871-876

    Cui, J. / Liu, F. / Li, Z. et al. | British Library Conference Proceedings | 2010


    Infrastructure camera calibration with GNSS for vehicle localisation

    Ojala, Risto / Vepsäläinen, Jari / Pirhonen, Jesse et al. | Wiley | 2023

    Free access

    Infrastructure camera calibration with GNSS for vehicle localisation

    Risto Ojala / Jari Vepsäläinen / Jesse Pirhonen et al. | DOAJ | 2023

    Free access

    VEHICLE LOCALISATION

    TAIE MOSTAFA / MARSHALL CHARLES | European Patent Office | 2020

    Free access

    Vehicle localisation

    FU JUNSHENG / ZHANG HAN / GUSTAFSSON TONY et al. | European Patent Office | 2024

    Free access