Refractive 3D reconstruction on underwater images

Anne Jordt , Kevin Köser , Reinhard Koch
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引用次数: 48

Abstract

Cameras can be considered measurement devices complementary to acoustic sensors when it comes to surveying marine environments. When calibrated and used correctly, these visual sensors are well-suited for automated detection, quantification, mapping, and monitoring applications and when aiming at high-accuracy 3D models or change detection. In underwater scenarios, cameras are often set up in pressure housings with a flat glass window, a flat port, which allows them to observe the environment. In this contribution, a geometric model for image formation is discussed that explicitly considers refraction at the interface under realistic assumptions like a slightly misaligned camera (w.r.t. the glass normal) and thick glass ports as common for deep sea applications. Then, starting from camera calibration, a complete, fully automated 3D reconstruction system is discussed that takes an image sequence and produces a 3D model. Newly derived refractive estimators for sparse two-view geometry, pose estimation, bundle adjustment, and dense depth estimation are discussed and evaluated in detail.

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水下图像的折射三维重建
在测量海洋环境时,相机可以被认为是声传感器的补充测量设备。当校准和正确使用时,这些视觉传感器非常适合自动检测,量化,绘图和监控应用,以及针对高精度3D模型或变化检测。在水下场景中,摄像机通常安装在带有平面玻璃窗和平面端口的压力外壳中,这样他们就可以观察环境。在这篇文章中,我们讨论了一个图像形成的几何模型,该模型明确考虑了在现实假设下的界面折射,比如轻微错位的相机(与玻璃法线相对)和深海应用中常见的厚玻璃端口。然后,从相机标定开始,讨论了一个完整的、全自动的三维重建系统,该系统采用图像序列并产生三维模型。对稀疏双视几何、位姿估计、束平差和密集深度估计等新导出的折射率估计方法进行了详细的讨论和评价。
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