This paper presents a novel feature-matching based approach for rigid object tracking. The proposed method models the tracking problem as discovering the affine transforms of object images between frames according to the extracted feature correspondences. False feature matches (outliers) are automatically detected and removed with a new SVM regression technique, where outliers are iteratively identified as support vectors with the gradually decreased insensitive margin /spl epsi/. This method, in addition to object tracking, can also be used for general feature-based epipolar constraint estimation, in which it can quickly detect outliers even if they make up, in theory, over 50% of the whole data. We have applied the proposed method to track real objects under cluttering backgrounds with very encouraging results.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Tracking of object with SVM regression


    Beteiligte:
    Weiyu Zhu, (Autor:in) / Song Wang, (Autor:in) / Ruei-Sung Lin, (Autor:in) / Levinson, S. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    1049402 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Tracking of Object with SVM Regression

    Zhu, W. / Wang, S. / Lin, R.-S. et al. | British Library Conference Proceedings | 2001


    Group Regression for Query Based Object Detection and Tracking

    Ruppel, Felicia / Faion, Florian / Glaser, Claudius et al. | IEEE | 2023


    Tracking with general regression

    Mayol, W. W. | British Library Online Contents | 2008


    OBJECT TRACKING SYSTEM, OBJECT TRACKING METHOD, AND OBJECT TRACKING PROGRAM

    NAKAMURA AKIHIRO / FUJII AKINOBU | Europäisches Patentamt | 2021

    Freier Zugriff

    Object tracking apparatus and object tracking method

    AIZAWA TOMOYOSHI | Europäisches Patentamt | 2019

    Freier Zugriff