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    A performance comparison of automatic detection schemes in wide-area aerial imagery

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    Name:
    Xin_SSIAI2016CarDetectionPaper.pdf
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    Description:
    Final Accepted Manuscript
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    Author
    Gao, Xin
    Ram, Sundaresh
    Rodriguez, Jeffrey J.
    Affiliation
    Univ Arizona, Dept Elect & Comp Engn
    Issue Date
    2016-04-28
    
    Metadata
    Show full item record
    Publisher
    IEEE
    Citation
    Gao, X., Ram, S., & Rodríguez, J. J. (2016, March). A performance comparison of automatic detection schemes in wide-area aerial imagery. In 2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) (pp. 125-128). IEEE.
    Journal
    2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI)
    Rights
    © 2016 IEEE.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Accurate and efficient detection of vehicles in wide-area aerial imagery is a fundamental task in understanding the automobile traffic patterns in an urban environment so as to help regulate the traffic flow. Vehicles with varying shapes and sizes, background clutter, occlusion, low-resolution and noise in the acquired images make the automatic detection of vehicles a challenging task. We present the performance analysis of six object detection algorithms for moving vehicle detection in low-resolution aerial image sequences. We compare the automatic detection results with manual detection, and evaluate the performance of the six object detection algorithms via several metrics.
    ISSN
    978-1-4673-9919-7
    DOI
    10.1109/SSIAI.2016.7459191
    Version
    Final accepted manuscript
    Additional Links
    http://ieeexplore.ieee.org/document/7459191/
    ae974a485f413a2113503eed53cd6c53
    10.1109/SSIAI.2016.7459191
    Scopus Count
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    UA Faculty Publications

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