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Optimization of Radial Distortion Self-Calibration for Structure from Motion from Uncalibrated UAV Images

机译:从Uncalbriated UAV映像的运动径向失真自校准的优化

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Structure from motion (SfM) and self-calibration from images of unknown radial distortions could fail under some critical configurations and produce distorted reconstruction results. In this paper, we propose an effective approach to optimize the estimation of radial distortion coefficient by taking full advantage of GPS information, which allows for more accurate SfM results. A feedback function is designed as the metric to indicate the magnitude of the distortion error. Heuristic search strategies are applied to search for the optimal distortion coefficient. Extensive experimental results show that our approach can effectively reduce the distorted deformation error and improve the estimation accuracy of the distortion coefficient.
机译:从运动(SFM)的结构和从未知径向扭曲图像的自校准可能在某种关键配置中失败,产生扭曲的重建结果。在本文中,我们提出了一种有效的方法来通过充分利用GPS信息来优化径向失真系数的估计,这允许更准确的SFM结果。反馈功能被设计为指标以指示失真误差的幅度。启发式搜索策略应用于搜索最佳失真系数。广泛的实验结果表明,我们的方法可以有效地降低扭曲的变形误差,提高失真系数的估计精度。

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