On Linear Structure from Motion for Light Field Cameras

We present a novel approach to relative pose estimation which is tailored to 4D light field cameras. From the relationships between scene geometry and light field structure and an analysis of the light field projection in terms of Pluecker ray coordinates, we deduce a set of linear constraints on ray space correspondences between a light field camera pair. These can be applied to infer relative pose of the light field cameras and thus obtain a point cloud reconstruction of the scene. While the proposed method has interesting relationships to pose estimation for generalized cameras based on ray-to-ray correspondence, our experiments demonstrate that our approach is both more accurate and computationally more efficient. It also compares favourably to direct linear pose estimation based on aligning the 3D point clouds obtained by reconstructing depth for each individual light field. To further validate the method, we employ the pose estimates to merge light fields captured with hand-held consumer light field cameras into refocusable panoramas.