  Recovering 3D geometry of underwater scenes is challenging because of
non-linear refraction of light at the water-air interface caused by the camera
housing. We present a light field-based approach that leverages properties of
angular samples for high-quality underwater 3D reconstruction from a single
viewpoint. Specifically, we resample the light field image to angular patches.
As underwater scenes exhibit weak view-dependent specularity, an angular patch
tends to have uniform intensity when sampled at the correct depth. We thus
impose this angular uniformity as a constraint for depth estimation. For
efficient angular resampling, we design a fast approximation algorithm based on
multivariate polynomial regression to approximate nonlinear refraction paths.
We further develop a light field calibration algorithm that estimates the
water-air interface geometry along with the camera parameters. Comprehensive
experiments on synthetic and real data show our method produces
state-of-the-art reconstruction on static and dynamic underwater scenes.

Computer Vision and Pattern Recognition