Light Field-Based Underwater 3D Reconstruction Via Angular Resampling

TL;DR

This paper introduces a novel light field-based method for high-quality 3D underwater scene reconstruction from a single viewpoint, addressing refraction challenges with angular resampling and calibration techniques.

Contribution

It proposes a new approach leveraging angular uniformity constraints and a fast approximation algorithm for refraction, along with a calibration method for water-air interface geometry.

Findings

Achieves state-of-the-art 3D reconstruction accuracy

Effective in static and dynamic underwater scenes

Outperforms existing methods in quality and efficiency

Abstract

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.