Affine Correspondences between Central
Cameras for Rapid Relative Pose Estimation
Abstract. This paper presents a novel algorithm to estimate the relative pose, i.e. the 3D rotation and translation of two cameras, from two
affine correspondences (ACs) considering any central camera model. The
solver is built on new epipolar constraints describing the relationship of
an AC and any central views. We also show that the pinhole case is a
specialization of the proposed approach. Benefiting from the low number of required correspondences, robust estimators like LO-RANSAC
need fewer samples, and thus terminate earlier than using the five-point
method. Tests on publicly available datasets containing pinhole, fisheye
and catadioptric camera images confirmed that the method often leads
to results superior to the state-of-the-art in terms of geometric accuracy