Large-baseline matching and reconstruction from symmetry cells

In this paper, we study how the presence of symmetry in man-made environments may significantly facilitate the task of automatic matching features and recovering 3-D camera pose and scene structure from multiple perspective images. While conventional methods typically rely on small-motion tracking or robust statistic techniques to resolve the coupling between feature matching and 3-D recovery, we here propose a new symmetry-based approach which allows automatic feature matching between images taken with arbitrary (both large and small) camera motions. To this end, we develop the multiple-view geometry of symmetry cells. To resolve possible ambiguities that may arise in matching symmetry cells and camera pose recovery, we find a consistent solution by finding the maximal complete subgraph of a matching graph; we also use a topological check to avoid mismatches. As our experiments shows, the resulting algorithms are simple, accurate and easy to implement.