论文标题
物体筛分和形态闭合，以减少大区域空中图像中的虚假检测
Object sieving and morphological closing to reduce false detections in wide-area aerial imagery
论文作者
论文摘要
为了在广阔的空中图像中检测物体检测，通常需要进行后处理以减少错误检测。我们提出了一个两阶段的后处理方案，该计划包括一个鉴定面积的筛分过程和形态的闭合操作。我们使用两个广阔的空中视频来比较在不存在和存在我们的后处理方案的情况下五种对象检测算法的性能。将自动检测结果与地面真相对象进行比较。几个指标用于性能比较。
For object detection in wide-area aerial imagery, post-processing is usually needed to reduce false detections. We propose a two-stage post-processing scheme which comprises an area-thresholding sieving process and a morphological closing operation. We use two wide-area aerial videos to compare the performance of five object detection algorithms in the absence and in the presence of our post-processing scheme. The automatic detection results are compared with the ground-truth objects. Several metrics are used for performance comparison.
