from images to rooms
Olaf Booij, Zoran Zivkovic and Ben Kröse
In Proceedings of the Workshop From sensors to human spatial concepts during the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2006.
Abstract
In this paper we start from a set of images obtained by the robot while it is moving around 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 a base level dense topological map. From this low level representation the images are groped 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.
Downloads
gzipped postscript (450 kb), pdf (277 kb)
