A performance comparison of automatic detection schemes in wide-area aerial imagery
AffiliationUniv Arizona, Dept Elect & Comp Engn
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CitationGao, 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.
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AbstractAccurate 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.
VersionFinal accepted manuscript