This contribution presents a multi sensor fusion approach for vehicle detection. Shadow and Symmetry features, abstracted to 3D sensors by including street surface information, are combined in an Interacting Multiple Model filter with two system models, one for constant velocity, one for constant acceleration. Measurements are associated to tracks by means of a Cheap Joint Probabilistic Data Association technique. Virtual prediction steps are used to incorporate multiple sensors and to achieve a versatile fusion architecture that allows easy integration of further sensors.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fusing multiple 2D visual features for vehicle detection


    Contributors:


    Publication date :

    2006-01-01


    Size :

    1621987 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Fusing Multiple 2D Visual Features for Vehicle Detection

    Hoffmann, C. | British Library Conference Proceedings | 2006


    Vehicle detection fusing 2D visual features

    Hoffman, C. / Dang, T. / Stiller, C. | IEEE | 2004


    MPP1.01 Vehicle Detection Fusing 2D Visual Features

    Hoffmann, C. / Dang, T. / Stiller, C. et al. | British Library Conference Proceedings | 2004


    EMERGENCY VEHICLE DETECTION FUSING AUDIO AND VISUAL DATA

    XU KECHENG / SUN HONGYI / LUO QI et al. | European Patent Office | 2022

    Free access

    Fusing mixed visual features for human action recognition

    Tang,C. / Zhou,C. / Pan,W. et al. | Automotive engineering | 2013