A performance comparison of automatic detection schemes in wide-area aerial imagery
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Xin_SSIAI2016CarDetectionPaper.pdf
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Final Accepted Manuscript
Affiliation
Univ Arizona, Dept Elect & Comp EngnIssue Date
2016-04-28
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IEEECitation
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.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
978-1-4673-9919-7Version
Final accepted manuscriptAdditional Links
http://ieeexplore.ieee.org/document/7459191/ae974a485f413a2113503eed53cd6c53
10.1109/SSIAI.2016.7459191