We introduce a novel 3D sensing method for recovering a consistent, dense 3D shape of a dynamic, non-rigid object in water. The method reconstructs a complete (or fuller) 3D surface of the target object in a canonical frame (e.g., rest shape) as it freely deforms and moves between frames by estimating underwater 3D scene flow and using it to integrate per-frame depth estimates recovered from two near-infrared observations. The reconstructed shape is refined in the course of this global non-rigid shape recovery by leveraging both geometric and radiometric constraints. We implement our method with a single camera and a light source without the orthographic assumption on either by deriving a practical calibration method that estimates the point source position with respect to the camera. Our reconstruction method also accounts for scattering by water. We prototype a video-rate imaging system and show 3D shape reconstruction results on a number of real-world static, deformable, and dynamic objects and creatures in real-world water. The results demonstrate the effectiveness of the method in recovering complete shapes of complex, non-rigid objects in water, which opens new avenues of application for underwater 3D sensing in the sub-meter range.

中文翻译：

---

来自水的非刚性形状

我们介绍了一种新颖的 3D 传感方法，用于恢复水中动态非刚性物体的一致、密集的 3D 形状。该方法通过估计水下 3D 场景流并使用它来整合恢复的每帧深度估计，在规范帧（例如，静止形状）中重建目标对象的完整（或更完整）3D 表面，因为它在帧之间自由变形和移动来自两个近红外观测。通过利用几何和辐射约束，在这种全局非刚性形状恢复过程中对重建的形状进行了改进。我们通过推导出一种实用的校准方法来估计点光源相对于相机的位置，从而使用单个相机和一个光源来实现我们的方法，而没有正射假设。我们的重建方法还考虑了水的散射。我们制作了一个视频速率成像系统的原型，并展示了真实世界水中许多静态、可变形和动态物体和生物的 3D 形状重建结果。结果证明了该方法在恢复水中复杂、非刚性物体的完整形状方面的有效性，为亚米级水下 3D 传感开辟了新的应用途径。