Underwater 3D reconstruction is challenging due to the refraction of light at the water-air interface (most electronic devices cannot be directly submerged in water). In this paper, we present an underwater 3D reconstruction solution using light field cameras. We first develop a light field camera calibration algorithm that simultaneously estimates the camera parameters and the geometry of the water-air interface. We then design a novel depth estimation algorithm for 3D reconstruction. Specifically, we match correspondences on curved epipolar lines caused by water refraction. We also observe that the view-dependent specular reflection is very weak in the underwater environment, resulting the angularly sampled rays in light field has uniform intensity. We therefore propose an angular uniformity constraint for depth optimization. We also develop a fast algorithm for locating the angular patches in presence of non-linear light paths. Extensive synthetic and real experiments demonstrate that our method can perform underwater 3D reconstruction with high accuracy.
翻译:水下 3D 重建由于水- 空气界面的光线折射( 大部分电子设备不能直接浸入水中), 水下 3D 重建具有挑战性 。 在本文中, 我们使用光场照相机提出水下 3D 重建解决方案 。 我们首先开发一个光场摄影机校准算法, 同时估计摄像参数和水- 空气界面的几何。 然后我们设计一个新的3D 重建深度估计算法 。 具体地说, 我们匹配水中反射所引发的曲线上层线上的通信。 我们还观察到, 水下环境中的视镜反射非常弱, 导致光场的角取样射线强度相同 。 因此, 我们提出一个对深度优化的角统一性限制 。 我们还开发一个快速算法, 在非线光路旁定位角的角片段 。 广泛的合成和真实实验证明, 我们的方法可以非常精确地进行水下 3D 重建 。