Abstract:
State-of-the-art robot mapping approaches are capable of acquiring impressively accurate 2D and 3D models of their environments. To the best of our knowledge few of them ...Show MoreMetadata
Abstract:
State-of-the-art robot mapping approaches are capable of acquiring impressively accurate 2D and 3D models of their environments. To the best of our knowledge few of them can acquire models of task-relevant objects. In this paper, we introduce a novel method for acquiring models of task-relevant objects from stereo images. The proposed algorithm applies methods from projective geometry and works for rectangular objects, which are, in office- and museum-like environments, the most commonly found subclass of geometric objects. The method is shown to work accurately and for a wide range of viewing angles and distances.
Published in: IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004
Date of Conference: 26 April 2004 - 01 May 2004
Date Added to IEEE Xplore: 06 July 2004
Print ISBN:0-7803-8232-3
Print ISSN: 1050-4729