LF-fusion: Dense and accurate 3D reconstruction from light field images
Light field (LF) cameras offer the capability of depth estimation in a single shot, which facilitates real-time 3D reconstruction of dynamic scenes. However, the accuracy of depth estimated from LF is still limited. Different from previous methods that generally focus on improving the fidelity of the central view depth, we argue that depth maps obtained at different views contain complementary information. Inspired by the principle of Kinect-fusion, we then propose a novel method for dense and accurate 3D reconstruction from LF images, namely, LF-fusion. Specifically, we use the iterative closest point (ICP) algorithm to register the point clouds generated from different views, and then employ a volumetric integration algorithm based on the truncated signed distance function (TSDF) to reconstruct the final 3D surface. Experiments demonstrate that the proposed method produces superior 3D reconstruction results on two representative LF datasets.