Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M3 tracker, i.e. AM3. In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Robust real-time vision-based aircraft tracking from Unmanned Aerial Vehicles


    Beteiligte:


    Erscheinungsdatum :

    01.05.2014


    Format / Umfang :

    3669163 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Vision-Based Tracking for Unmanned Aerial Vehicles

    V. K. Chitrakaran / D. M. Dawson / H. Kannan et al. | NTIS | 2006



    Real-time visual object tracking for unmanned aerial vehicles (UAVs)

    GAO YU / WANG XING / MA RUI et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    REAL-TIME VISUAL OBJECT TRACKING FOR UNMANNED AERIAL VEHICLES (UAVS)

    GAO YU / WANG XING / MA RUI et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Vision-based navigation of unmanned aerial vehicles

    Courbon, Jonathan / Mezouar, Youcef / Guenard, Nicolas et al. | Tema Archiv | 2010