A real-time adaptive segmentation method based on new distance features is proposed for the binary centroid tracker. These novel features are the distances between the predicted center pixel of a target object, measured by a tracking filter, and each pixel in the extraction of a moving target. The proposed method restricts clutters with target-like intensity from entering a tracking window and has low computational complexity for real-time applications compared with other complex feature-based methods. Comparative experiments show that the proposed method is superior to other segmentation methods based on intensity features in target detection and tracking.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Robust centroid target tracker based on new distance features in cluttered image sequences


    Beteiligte:
    Cho, Jae-Soo (Autor:in) / Kim, Do-Jong (Autor:in) / Park, Dong-Jo (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2000


    Format / Umfang :

    10 Seiten, 29 Quellen



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Robust real-time face tracker for cluttered environments

    Anderson, K. / McOwan, P. W. | British Library Online Contents | 2004



    Noise effects on centroid tracker aim point estimation

    Van Rheeden, D.R. / Jones, R.A. | IEEE | 1988


    Artificial neural network for star tracker centroid computation

    Zapevalin, P.R. / Novoselov, A. / Zharov, V.E. | Elsevier | 2022


    A Parallel Feature Tracker for Extended Image Sequences

    Sing Bing Kang / Szeliski, R. / Shum, H.-Y. | British Library Online Contents | 1997