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Automatic 3D Reconstruction from Multi-date Satellite Images

机译：从多日期卫星图像自动进行3D重建

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We propose an algorithm for computing a 3D model from several satellite images of the same site. The method works even if the images were taken at different dates with important lighting and vegetation differences. We show that with a large number of input images the resulting 3D models can be as accurate as those obtained from a single same-date stereo pair. To deal with seasonal vegetation changes, we propose a strategy that accounts for the multi-modal nature of 3D models computed from multi-date images. Our method uses a local affine camera approximation and thus focuses on the 3D reconstruction of small areas. This is a common setup in urgent cartography for emergency management, for which abundant multi-date imagery can be immediately available to build a reference 3D model. A preliminary implementation of this method was used to win the IARPA Multi-View Stereo 3D Mapping Challenge 2016. Experiments on the challenge dataset are used to substantiate our claims.
机译：我们提出了一种用于从同一站点的多个卫星图像计算3D模型的算法。即使图像是在不同日期拍摄的，且光照和植被差异很大，该方法仍然有效。我们显示，使用大量输入图像时，生成的3D模型可以与从单个相同日期的立体声对获得的3D模型一样准确。为了应对季节性植被变化，我们提出了一种策略，该策略考虑了根据多日期图像计算出的3D模型的多模式性质。我们的方法使用局部仿射相机逼近，因此着重于小区域的3D重建。这是紧急情况制图中用于应急管理的常见设置，可以立即使用其丰富的多日期图像来构建参考3D模型。该方法的初步实现用于赢得2016年IARPA多视图立体3D映射挑战赛。挑战数据集上的实验用于证实我们的主张。

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