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Feature Correspondence and Semi-Automatic Ground Truthing for Airborne Data Collection

机译:用于机载数据收集的功能对应和半自动地面串联

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A significant amount of airborne data has been collected in the past and more is expected to be collected in the future to support airborne landmine detection research and evaluation under various programs. In order to evaluate mine and minefield detection performance for sensor and detection algorithms, it is essential to generate reliable and accurate ground truth for the location of the mine targets and fiducials present in raw imagery. The current ground truthing operation is primarily manual, which makes the ground truthing a time consuming and expensive exercise in the overall data collection effort. In this paper, a semi-automatic ground-truthing technique is presented which reduces the role of the operator to a few high-level input and validation actions. A correspondence is established between the high-contrast targets in the airborne imagery called the image features, and the known GPS locations of the targets on the ground called the map features by imposing various position and geometric constraints. These image and map features may include individual fiducial targets, rows of fiducial targets and triplets of non-collinear fiducials. The targets in the imagery are established using the RX anomaly detector. An affine or linear conformal transformation from map features to image features is calculated based on feature correspondence. This map-to-image transformation is used to generate ground-truth for mine targets. Since accurate and reliable flight-log data is currently not available, one-time specification of a few parameters like flight speed, flight direction, camera resolution and specification of the location of the initial frame on the map is required from the operator. These parameters are updated and corrected for subsequent frames based on the processing of previous frames. Image registration is used to ground-truth images which do not have enough high-contrast fiducials for reliable correspondence. A GUI called SemiAutoGT developed in MATLAB for the ground truthing process is briefly discussed. Results are presented for ground-truthing of the data collected under the Lightweight Airborne Multispectral Minefield Detection (LAMD) program.
机译:在过去收集了大量的空中数据,预计将于将来收集更多,以支持在各个方案下支持空中的地雷检测研究和评估。为了评估传感器和检测算法的矿井和雷区检测性能,必须为矿井目标和基准的位置生成可靠和准确的基础事实,以原始图像中存在的基准。目前的地面跟踪操作主要是手动,这使得地面在整体数据收集工作中进行耗时和昂贵的运动。在本文中,提出了一种半自动地面特拉图技术,其降低了操作者对少量高级输入和验证动作的作用。通过施加各种位置和几何约束,在称为图像特征的空中图像中的高对比度目标和地面上的目标的已知GPS位置之间建立了对应关系。这些图像和地图特征可以包括各个基准目标,基准目标的行和非共线面基准的三胞胎。使用Rx异常检测器建立图像中的目标。根据特征对应计算从地图特征到图像特征的仿射或线性共形变换。此Map-to-Image转换用于为矿山目标生成地面真理。由于目前无法获得准确可靠的飞行日志数据,因此需要从运营商处需要飞行速度,飞行方向,摄像机分辨率等少数参数的一次性规范。基于先前帧的处理更新和校正这些参数并校正后续帧。图像注册用于地面真实图像,其没有足够的高对比度基准,以获得可靠的对应关系。简要讨论了一个名为Semiautogt的GUI,用于在MATLAB中开发地面追踪过程。在轻量级空中多光谱型矿场检测(LAMD)程序下收集的数据的地面追踪结果。

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