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An Approach to Automatic Great-scene 3D Reconstruction Based on UAV Sequence Images

机译:基于UAV序列图像的自动伟大场景三维重建方法

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In this paper, we propose an approach to automatic great-scene 3D reconstruction based on UAV sequence images. In this method, Harris feature point and SIFT feature vector is used to distill image feature, achieving images match; quasi-perspective projection model and factorization is employed to calibrate the uncalibrated image sequences automatically; Efficient suboptimal solutions to the optimal triangulation is plied to obtain the coordinate of 3D points; quasi-dense diffusing algorithm is bestowed to make 3D point denseness; the algorithm of bundle adjustment is taken to improve the precision of 3D points; the approach of Possion surface reconstruction is used to make 3D points gridded. This paper introduces the theory and technology of computer vision into great-scene 3D reconstruction, provides a new way for the construction of 3D scene, and provides a new thinking for the appliance of UAV sequence images.
机译:在本文中,我们提出了一种基于UAV序列图像的自动伟大场景3D重建方法。在此方法中,Harris特征点和SIFT特征向量用于蒸馏图像特征,实现图像匹配;采用准透视投影模型和分解来自动校准未校准的图像序列;最佳三角测量的高效次优解层得到了获得3D点的坐标;准密集的扩散算法被赋予3D点密度;采用束调节算法来提高3D点的精度;可能表面重建的方法用于使3D点网格包装。本文介绍了计算机愿景的理论和技术进入伟大场景3D重建,为3D场景建设提供了一种新的方式,为UAV序列图像设备提供了新的思维。

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