An Efficient Dynamic Multi-Angular Feature Points Matcher for Catadioptric Views

A new efficient matching algorithm dedicated to catadioptric sensors is proposed in this paper. The presented approach is designed to overcome the varying resolution of the mirror. The aim of this work is to provide a matcher that gives reliable results similar to the ones obtained by classical operators on planar projection images. The matching is based on a dynamical size windows extraction, computed from the viewing angular aperture of the neighborhood around the points of interest. An angular scaling of this angular aperture provides a certain number of different neighborhood resolution around the same considered point. A combinatory cost method is introduced in order to determine the best match between the different angular neighborhood patches of two interest points. Results are presented on sparse matched corner points, that can be used to estimate the epipolar geometry of the scene in order to provide a dense 3D map of the observed environment.