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We present a novel and simple computational imaging solution to robustly and accurately recover 3D dynamic fluid surfaces. Traditional specular surface reconstruction schemes place special patterns (checkerboard or color patterns) beneath the fluid surface to establish point-pixel correspondences. However, point-pixel correspondences alone are insufficient to recover surface normal or height and they rely on additional constraints to resolve the ambiguity. In this paper, we exploit using Bokode - a computational optical device that emulates a pinhole projector - for capturing ray-ray correspondences which can then be used to directly recover the surface normals. We further develop a robust feature matching algorithm based on the Active-Appearance Model to robustly establishing ray-ray correspondences. Our solution results in an angularly sampled normal field and we derive a new angular-domain surface integration scheme to recover the surface from the normal fields. Specifically, we reformulate the problem as an over-constrained linear system under spherical coordinate and solve it using Singular Value Decomposition. Experiments results on real and synthetic surfaces demonstrate that our approach is robust and accurate, and is easier to implement than state-of-the-art multi-camera based approaches.