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Authors: Nicolas Pugeault 1 ; Emre Baseski 2 ; Dirk Kraft 2 ; Florentin Wörgötter 3 and Norbert Krüger 2

Affiliations: 1 University of Edinburgh, United Kingdom ; 2 Syddansk Universitet, Denmark ; 3 Göttingen University, Germany

Abstract: 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 several formats:
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 (VISAPP 2007) - Robot Vision; ISBN 978-972-8865-76-4, SciTePress, pages 126-135. DOI: 10.5220/0002068501260135

@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 (VISAPP 2007) - Robot Vision},


JO - Robot Vision (VISAPP 2007) - Robot Vision
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
PB - SciTePress