Surface Normals and Shape From Water
Surface Normals and Shape From Water
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DOI：
10.1109/tpami.2021.3121963
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发表时间：
2019-10
影响因子：
23.6
通讯作者：
M. Kuo;S. Murai;Ryo Kawahara;S. Nobuhara;K. Nishino
中科院分区：
文献类型：
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作者：
M. Kuo;S. Murai;Ryo Kawahara;S. Nobuhara;K. Nishino
本文介绍了一种重建水中动态物体表面法线和深度的新方法。过去的形状恢复方法利用各种视觉线索来估计形状(例如深度)或表面法线。估计两者的方法都是从一个计算到另一个。我们证明，当物体在水下观察时，这两个几何表面属性可以同时恢复到每个像素。我们的主要想法是利用沿着不同水下光路的多波长近红外光吸收，并结合表面阴影。我们的方法既可以处理朗伯曲面，也可以处理非朗伯曲面。给出了这种表面法线和水法面形的原则性理论和确定其成像参数值的实用标定方法。通过构造，该方法可以实现为一次成像系统。我们制作了一个离线和视频率成像系统的原型，并在一些真实世界的静态和动态对象上演示了该方法的有效性。结果表明，该方法可以恢复原本无法获取的复杂表面特征。
In this paper, we introduce a novel method for reconstructing surface normals and depth of dynamic objects in water. Past shape recovery methods have leveraged various visual cues for estimating shape (e.g., depth) or surface normals. Methods that estimate both compute one from the other. We show that these two geometric surface properties can be simultaneously recovered for each pixel when the object is observed underwater. Our key idea is to leverage multi-wavelength near-infrared light absorption along different underwater light paths in conjunction with surface shading. Our method can handle both Lambertian and non-Lambertian surfaces. We derive a principled theory for this surface normals and shape from water method and a practical calibration method for determining its imaging parameters values. By construction, the method can be implemented as a one-shot imaging system. We prototype both an off-line and a video-rate imaging system and demonstrate the effectiveness of the method on a number of real-world static and dynamic objects. The results show that the method can recover intricate surface features that are otherwise inaccessible.