Complex motion makes consecutive frames experience dramatic change, and thus becomes a barrier to object-tracking. Three factors contribute to more complexity of motion: longer sampling period,an moving object with complex appearance and nonrestraint movement, occlusion, which causes mean shift algorithm losing its target due to too low a Bhattacharyya coefficient. To treat it, mean shift algorithm is improved based on a new way of fast color thresholding and region merging in this paper. Visual experiments show the effectiveness of the proposed method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A New Improvement on Mean-Shift Algorithm


    Beteiligte:
    Li, Zhong-Sheng (Autor:in) / Li, Ren-Fa (Autor:in) / Liu, Yu-Feng (Autor:in) / Zhang, Yao-Xue (Autor:in)


    Erscheinungsdatum :

    2008-05-01


    Format / Umfang :

    359203 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Fast mean shift based traffic image filtering algorithm

    Yu, Zhang / Shi Zhong-ke, / Wang Run-quan, | IEEE | 2009


    Fast Mean Shift Based Traffic Image Filtering Algorithm

    Yu, Z. / Zhong-ke, S. / Run-quan, W. | British Library Conference Proceedings | 2009


    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