# Light Field-Based Underwater 3D Reconstruction Via Angular Resampling

arXiv: https://arxiv.org/abs/2109.02116 · HTML: https://mlsanity.com/paper/2109.02116/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 70 references that are in the map.
- First posted on arXiv 5 Sep 2021.

## Builds on (most cited first, 4 of 4)

- [A Generic Multi-Projection-Center Model and Calibration Method for Light Field Cameras](https://mlsanity.com/paper/1808.02244/) (2018)
- [Photometric Stereo in Participating Media Considering Shape-Dependent Forward Scatter](https://mlsanity.com/paper/1804.02836/) (2018)
- [Underwater Stereo using Refraction-free Image Synthesized from Light Field Camera](https://mlsanity.com/paper/1905.09588/) (2019)
- [Unified Underwater Structure-from-Motion](https://mlsanity.com/paper/1909.03583/) (2019)

## Built on by (most cited first, 2 of 2)

- [Beyond Subspace Isolation: Many-to-Many Transformer for Light Field Image Super-resolution](https://mlsanity.com/paper/2401.00740/) (2024)
- [UW-SDF: Exploiting Hybrid Geometric Priors for Neural SDF Reconstruction from Underwater Multi-view Monocular Images](https://mlsanity.com/paper/2410.08092/) (2024)

## Abstract (arXiv)

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.