This paper introduces a novel depth recovery method based on light absorption in water. Water absorbs light at almost all wavelengths whose absorption coefficient is related to the wavelength. Based on the Beer-Lambert model, we introduce a bispectral depth recovery method that leverages the light absorption difference between two near-infrared wavelengths captured with a distant point source and orthographic cameras. Through extensive analysis, we show that accurate depth can be recovered irrespective of the surface texture and reflectance, and introduce algorithms to correct for nonidealities of a practical implementation including tilted light source and camera placement, nonideal bandpass filters and the perspective effect of the camera with a diverging point light source. We construct a coaxial bispectral depth imaging system using low-cost off-the-shelf hardware and demonstrate its use for recovering the shapes of complex and dynamic objects in water. We also present a trispectral variant to further improve robustness to extremely challenging surface reflectance. Experimental results validate the theory and practical implementation of this novel depth recovery paradigm, which we refer to as shape from water.

中文翻译：

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水中近红外光吸收的深度传感

本文介绍了一种基于水中光吸收的新型深度恢复方法。水吸收几乎所有波长的光，其吸收系数与波长有关。基于 Beer-Lambert 模型，我们引入了一种双光谱深度恢复方法，该方法利用远距离点光源和正交相机捕获的两个近红外波长之间的光吸收差异。通过广泛的分析，我们表明无论表面纹理和反射率如何，都可以恢复准确的深度，并引入算法来校正实际实现的非理想性，包括倾斜光源和相机放置、非理想带通滤波器和相机的透视效果发散点光源。我们使用低成本的现成硬件构建了一个同轴双谱深度成像系统，并演示了其用于恢复水中复杂动态物体形状的用途。我们还提出了一种三光谱变体，以进一步提高对极具挑战性的表面反射的鲁棒性。实验结果验证了这种新型深度恢复范式的理论和实际实施，我们将其称为水的形状。