from images to rooms
Zoran Zivkovic, Olaf Booij and Ben Kröse
IEEE Transactions on Robotics, Volume 55, Issue 5, 31 May 2007, Pages 411-418
Abstract
In this paper we start from a set of images obtained by the robot that is moving around in an environment. We present a method to automatically group the images into groups that correspond to convex subspaces in the environment which are related to the human concept of rooms. Pairwise similarities between the images are computed using local features extracted from the images and geometric constraints. The images with the proposed similarity measure can be seen as a graph or in a way as a base level dense topological map. From this low level representation the images are grouped using a graph-clustering technique which effectively finds convex spaces in the environment. The method is tested and evaluated on challenging data sets acquired in real home environments. The resulting higher level maps are compared with the maps humans made based on the same data.
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