Matching cylindrical panorama sequences using planar reprojections

This paper presents a matching scheme for large set of omnidirectional images sequentially captured in an urban environment. Most classical image matching methods when applied to cylindrical panoramas taken in large environments does not always produce a sufficient number of matches. In this work, our objective is to making sure that the full set of panoramas remains as connected as possible at all geographical locations even if only a few panoramas sharing the same view of the scene are available. For this matter, we present a matching strategy that augments the accuracy and the number of match points in the context of urban panorama matching. To improve matching results, the method simulates different local transformations at chosen view directions of the panoramas. We show that our matching scheme improves the matching result on the specific panoramas where the classical methods fail to find a sufficient number of matches. This conclusion is supported by real-world experiments performed on 8017 pairs of images coming from 763 different images.