Mustafa, W., Pugeault, N. and Krüger, N. (2013) Multi-View Object Recognition Using View-Point Invariant Shape Relations and Appearance Information. In: 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 06-10 May 2013, pp. 4230-4237. ISBN 9781467356435 (doi: 10.1109/ICRA.2013.6631175)
Full text not currently available from Enlighten.
Abstract
We present an object recognition system coding shape by view-point invariant geometric relations and appearance. In our intelligent work-cell, the system can observe the work space of the robot by 3 pairs of Kinect and stereo cameras allowing for reliable and complete object information. We show that in such a set-up we can achieve high performance already with a low number of training samples. We show this by training the system to classify 56 objects using Random Forest algorithm. This indicates that our approach can be used in contexts such as assembly manipulation which require high reliability of object recognition.
Item Type: | Conference Proceedings |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Pugeault, Dr Nicolas |
Authors: | Mustafa, W., Pugeault, N., and Krüger, N. |
College/School: | College of Science and Engineering > School of Computing Science |
ISSN: | 1050-4729 |
ISBN: | 9781467356435 |
Published Online: | 17 October 2013 |
University Staff: Request a correction | Enlighten Editors: Update this record