Abstract
In this paper, we present a post-processing scheme to improve the performance of vehicle detection in wide-area aerial imagery. Using low-resolution aerial frames for the performance analysis, we adapted nine algorithms for vehicle detection. We derived a three-stage scheme to measure performance improvement on the selected five object segmentation algorithms before and after post-processing. We compared automatic detections results to ground-truth objects, and classified each type of detections in terms of true positive, false negative and false positive. Several evaluation metrics are adopted for the experimental study.
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05 March 2020
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The author declares no conflict of interests on research. The author owes special gratitude to anonymous reviewers for their valuable comments on improving technical quality of this manuscript.
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Gao, X. A post-processing scheme for the performance improvement of vehicle detection in wide-area aerial imagery. SIViP 14, 625–633 (2020). https://doi.org/10.1007/s11760-019-01592-4
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DOI: https://doi.org/10.1007/s11760-019-01592-4