Place Recognition Based on Planar Surfaces Using Multiple RGB-D Images Taken From the same Position

This paper considers indoor place recognition based on matching of planar surfaces and straight edges extracted from depth images obtained by an RGB-D camera. The idea of using planar surfaces as landmarks for robot localization has already been investigated. In this paper, the advantage of using multiple RGB-D images acquired from the same viewpoint by a camera mounted on a pan-tilt head is addressed. This simple straightforward method of expanding the field of view of a standard RGB-D camera allows 3D models of the observed place to be built, which contain information about relative positions of geometric features that are not contained within a single camera FoV. A high recognition rate is achieved indicating the practical applicability of the investigated approach. A publicly available dataset for the evaluation of place recognition methods is created. Using this dataset, the ability of recognizing places from viewpoints that differ from those from which the model is built can be tested as well as robustness to scene and lighting changes.