Classical mean shift tracking algorithm doesnt show good performance when the tracked objects move fast, change in size or pose. This paper proposes an improved mean shift method used for vehicle tracking. Firstly, a position prediction model based on second order auto-regression process is used to find the initial position of mean shift iteration, reduce times of iteration and enhance the tracking accuracy. Secondly, we employ a position search method based on the weight image to improve the tracking result when the result of basic mean shift tracking is not good. The proposed algorithm is tested in a real traffic video to track a vehicle changing in size and pose with more accurate result than basic mean shift tracking algorithm.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An Improved Mean Shift Algorithm for Vehicle Tracking



    Published in:

    Advanced Materials Research ; 718-720 ; 2329-2334


    Publication date :

    2013-07-31


    Size :

    6 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Vehicle Tracking from Videos Based on Mean Shift Algorithm

    Xiong, C.-Z. / Pang, Y.-G. / Li, Z.-X. et al. | British Library Conference Proceedings | 2009


    A SIFT-BASED MEAN SHIFT ALGORITHM FOR MOVING VEHICLE TRACKING

    Liang, W. / Xie, X. / Wang, J. et al. | British Library Conference Proceedings | 2014


    Human Sperm Tracking Using Improved Anti-collision Mean Shift Tracking Method

    Tan, Weng Chun / Isa, Nor Ashidi Mat / Mohamed, Mahaneem | TIBKAT | 2019


    Human Sperm Tracking Using Improved Anti-collision Mean Shift Tracking Method

    Tan, Weng Chun / Mat Isa, Nor Ashidi / Mohamed, Mahaneem | Springer Verlag | 2019


    A Mean Shift Tracking Algorithm Based on Multi-Cue Fusion

    Ma, J. / Han, C. | British Library Online Contents | 2009