Pruning the image set for appearance based robot localization
Olaf Booij, Zoran Zivkovic and Ben Kröse
In Proceedings of the annual conference of the Advanced School for Computing and Imaging, 2005
Abstract
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 a low level representation that consists of a graph in which relations between images are represented. We use a metric based on visual landmarks (SIFT features) and geometrical constraints. This graph is then pruned using the Connected Dominating Set algorithm. The method is applied on real data and evaluated by correlating new images with images in the Connected Dominating Set.
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