Visual object tracking is one of the significant parts of systems varying from autonomous driving to drone-based surveillance/tracking. Discriminative correlation filter (DCF)-based trackers have proved their prominence in the past few years. These utilize visual information present in images for monitoring. This work uses the Kalman filter to derive a motion estimation model. It combines it with two DCF-based trackers, namely, the kernelized correlation filter and the discriminative correlation filter with channel and spatial reliability for pedestrian tracking. Camera motion-compensated versions of the trackers are also presented. The performance of the proposed methodology is presented in terms of success rate (SR) and precision (P). Real-time power consumption, memory occupancy, and speed of trackers on the Jetson Nano (ARM Cortex-A57, 4 GB RAM) board have been presented.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Pedestrian Tracking in UAV Images With Kalman Filter Motion Estimator and Correlation Filter


    Beteiligte:
    Kumar, Ranjeet (Autor:in) / Deb, Alok Kanti (Autor:in)


    Erscheinungsdatum :

    2023-07-01


    Format / Umfang :

    7721171 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    The unscented Kalman filter for pedestrian tracking from a moving host

    Meuter, Mirko / Iurgel, Uri / Park, Su-Birm et al. | IEEE | 2008


    Using the Unscented Kalman Filter for Pedestrian Tracking from a Moving Host

    Meuter, M. / Iurgel, U. / Park, S.-B. et al. | British Library Conference Proceedings | 2008


    Time Frequency and Kalman Filter Based Baud Rate Estimator

    Boulinguez, D. / Garnier, C. / Delignon, Y. et al. | British Library Conference Proceedings | 2003


    Time frequency and Kalman filter based baud rate estimator

    Boulinguez, D. / Garnier, C. / ves Delignon, Y. et al. | IEEE | 2003


    State of charge Kalman filter estimator for automotive batteries

    Barbarisi, Osvaldo / Vasca, Francesco / Glielmo, Luigi | Tema Archiv | 2006