Extraction of Multi–modal Object Representations in a Robot Vision System

Nicolas Pugeault, Emre Baseski, Dirk Kraft, Florentin Wörgötter, Norbert Krüger



We introduce one module in a cognitive system that learns the shape of objects by active exploration. More specifically, we propose a feature tracking scheme that makes use of the knowledge of a robotic arm motion to: 1) segment the object currently grasped by the robotic arm from the rest of the visible scene, and 2) learn a representation of the 3D shape without any prior knowledge of the object. The 3D representation is generated by stereo–reconstruction of local multi–modal edge features. The segmentation between features belonging to the object those describing the rest of the scene is achieved using Bayesian inference. We then show the shape model extracted by this system from various objects.


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Paper Citation

in Harvard Style

Pugeault N., Baseski E., Kraft D., Wörgötter F. and Krüger N. (2007). Extraction of Multi–modal Object Representations in a Robot Vision System . In Robot Vision - Volume 1: Robot Vision, (VISAPP 2007) ISBN 978-972-8865-76-4, pages 126-135. DOI: 10.5220/0002068501260135

in Bibtex Style

@conference{robot vision07,
author={Nicolas Pugeault and Emre Baseski and Dirk Kraft and Florentin Wörgötter and Norbert Krüger},
title={Extraction of Multi–modal Object Representations in a Robot Vision System},
booktitle={Robot Vision - Volume 1: Robot Vision, (VISAPP 2007)},

in EndNote Style

JO - Robot Vision - Volume 1: Robot Vision, (VISAPP 2007)
TI - Extraction of Multi–modal Object Representations in a Robot Vision System
SN - 978-972-8865-76-4
AU - Pugeault N.
AU - Baseski E.
AU - Kraft D.
AU - Wörgötter F.
AU - Krüger N.
PY - 2007
SP - 126
EP - 135
DO - 10.5220/0002068501260135