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    ROBUST OBJECT TRACKING AND ADAPTIVE DETECTION FOR AUTO NAVIGATION OF UNMANNED AERIAL VEHICLE

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    Nandi_ku_0099M_15079_DATA_1.pdf (3.098Mb)
    Thesis Presentation PDF (2.670Mb)
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    Issue Date
    2017-05-31
    Author
    Nandi, Soumyaroop
    Publisher
    University of Kansas
    Format
    111 pages
    Type
    Thesis
    Degree Level
    M.S.
    Discipline
    Electrical Engineering & Computer Science
    Rights
    Copyright held by the author.
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    Abstract
    Abstract Object detection and tracking is an important research topic in the computer vision field with numerous practical applications. Although great progress has been made, both in object detection and tracking over the past decade, it is still a big challenge in real-time applications like automated navigation of an unmanned aerial vehicle and collision avoidance with a forward looking camera. An automated and robust object tracking approach is proposed by integrating a kernelized correlation filter framework with an adaptive object detection technique based on minimum barrier distance transform. The proposed tracker is automatically initialized with salient object detection and the detected object is localized in the image frame with a rectangular bounding box. An adaptive object redetection strategy is proposed to refine the location and boundary of the object, when the tracking correlation response drops below a certain threshold. In addition, reliable pre-processing and post-processing methods are applied on the image frames to accurately localize the object. Extensive quantitative and qualitative experimentation on challenging datasets have been performed to verify the proposed approach. Furthermore, the proposed approach is comprehensively examined with six other recent state-of-the-art¬ trackers, demonstrating that the proposed approach greatly outperforms these trackers, both in terms of tracking speed and accuracy.
    URI
    http://hdl.handle.net/1808/24144
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    • Engineering Dissertations and Theses [1055]
    • Theses [3901]

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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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