Sparse appearance based modeling for robot localization

In appearance based robot localization a new image is matched with every image in the database. In this paper we describe how to reduce the number of images in this database with minimal loss of information and thereby increasing the efficiency of localization significantly. First we build an appearance based model consisting of a graph in which the nodes denote images and links denote relations between images. This graph is then pruned using the connected dominating set algorithm. The method is tested on an image set acquired by a mobile robot equipped with an omnidirectional camera driving around in an office environment, as well as sets of images taken while driving through a real furnished home environment