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.
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| http://dx.doi.org/10.1109/TPAMI.2021.3075450 | DOI Listing |
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