A Linear Approach to Absolute Pose Estimation for Light Fields

This paper presents the first absolute pose estimation approach tailored to Light Field cameras. It builds on the observation that the ratio between the disparity arising in different sub-aperture images and their corresponding baseline is constant. Hence, we augment the 2D pixel coordinates with the corresponding normalised disparity to obtain the Light Field feature. This new representation reduces the effect of noise by aggregating multiple projections and allows for linear estimation of the absolute pose of a Light Field camera using the well-known Direct Linear Transformation algorithm. We evaluate the resulting absolute pose estimates with extensive simulations and experiments involving real Light Field datasets, demonstrating the competitive performance of our linear approach. Furthermore, we integrate our approach in a state-of-the-art Light Field Structure from Motion pipeline and demonstrate accurate multi-view 3D reconstruction.