Sampling based bundle adjustment using feature matches between ground-view and aerial images

This paper proposes a new pipeline of Structure-from-Motion that uses feature matches between ground-view and aerial images for removing accumulative errors. In order to find good matches from unreliable matches, we newly propose RANSAC based outlier elimination methods in both feature matching and bundle adjustment stages. To this end, in the feature matching stage, the consistency of orientation and scale extracted from images by a feature descriptor is checked. In the bundle adjustment stage, we focus on the consistency between estimated geometry and matches. In experiments, we quantitatively evaluate performances of the proposed feature matching and bundle adjustment.