In this paper we present a self-calibration approach that updates the extrinsic parameters and the focal lengths of a stereo vision sensor. We employ a recursive estimation algorithm based on an Extended Kalman Filter. To improve the self-calibration process, we introduce a robust innovation stage for the Kalman filter: A Least Median Squares estimator is employed to eliminate outliers and thus to achieve better performance. The algorithm gives promising results on experiments with synthetic and natural imagery.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Stereo calibration in vehicles


    Contributors:
    Dang, T. (author) / Hoffmann, C. (author)


    Publication date :

    2004-01-01


    Size :

    670743 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Stereo Calibration in Vehicles

    Dang, T. / Hoffmann, C. / IEEE | British Library Conference Proceedings | 2004


    Stereo camera for vehicles

    ADOMAT ROLF / FECHNER THOMAS / KROEKEL DIETER et al. | European Patent Office | 2019

    Free access

    Stereo Camera for Vehicles

    ADOMAT ROLF / FECHNER THOMAS / KROEKEL DIETER et al. | European Patent Office | 2017

    Free access

    Online stereo calibration using FPGAs

    Pettersson, N. / Petersson, L. | IEEE | 2005


    Dynamic stereo with self-calibration

    Tirumalai, A.P. / Schunck, B.G. / Jain, R.C. | IEEE | 1990