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Non-Rigid Shape From Water

Meng-Yu Jennifer Kuo, Ryo Kawahara, Shohei Nobuhara, Ko Nishino

IEEE Transactions on Pattern Analysis and Machine Intelligence(2021)

Cited 10|Views26
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Abstract
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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Key words
Three-dimensional displays,Shape,Cameras,Image reconstruction,Absorption,Surface reconstruction,Imaging,Computational photography,underwater 3D shape recovery,non-rigid reconstruction,near-infrared light,camera calibration
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