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Autonomous 3D metric reconstruction from uncalibrated aerial images captured from UAVs

机译:从无人机获取的未校准航拍图像进行自主3D度量重建

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摘要

In this article, we propose a methodology to co-register multitemporal images captured from different sources in order to make it possible to generate precise, fully-automatic spatial information. The goal is to identify objects in images without metric or assigned coordinates by relating them with the same objects in images from other sources where the metric is known. In this way, processing times are reduced and manual intervention is unnecessary, thus making it ideally suited for continuous update programmes. This article describes the use of a modified optimization of the scale invariant feature transform to successfully match old and new images. After that, control points are automatically assigned to each new image to generate orthophotos automatically and evaluate them through positional accuracy tests.
机译:在本文中,我们提出了一种方法来共同注册从不同来源捕获的多时相图像,以便使其能够生成精确的全自动空间信息。目的是通过将度量与已知度量的其他来源的图像中的相同对象相关联,来识别图像中没有度量或分配坐标的对象。这样,可以减少处理时间,并且不需要人工干预,因此非常适合连续更新程序。本文介绍了如何使用比例不变特征变换的修改优化来成功匹配新旧图像。之后,将控制点自动分配给每个新图像,以自动生成正射影像并通过位置精度测试对其进行评估。

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