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Exploring Objects for Recognition in the Real World
Faculty of Mathematics and Natural Sciences, University of Groningen, The Netherlands. (Artificial Intelligence)
Faculty of Mathematics and Natural Sciences, University of Groningen, The Netherlands. (Artificial Intelligence)
Faculty of Mathematics and Natural Sciences, University of Groningen, The Netherlands. (Artificial Intelligence)
2007 (English)In: Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO 2007), IEEE , 2007, 429-434 p.Conference paper, Published paper (Refereed)
Abstract [en]

Perception in natural systems is a highly active process. In this paper, we adopt the strategy of natural systems to explore objects for 3D object recognition using robots. The exploration of objects enables the system to learn objects from different viewpoints, which is essential for 3D object recognition. Exploration furthermore simplifies the segmentation of the object from its background, which is important for object learning in real-world environments, which are usually highly cluttered. We use the scale invariant feature transform (SIFT) as the basis for our object recognition system. We discuss our active vision approach to learn and recognize 3D objects in cluttered and uncontrolled environments. Furthermore, we propose a model to reduce the number of SIFT keypoints stored in the object database. It is a known drawback of SIFT that the computational complexity of the algorithm increases rapidly with the number of keypoints. We discuss the use of a growing-when-required (GWR) network, which is based on the Kohonen self organizing feature map, for efficient clustering of the keypoints. The results show successful learning of 3D objects in a cluttered and uncontrolled environment. Moreover, the GWR-network strongly reduces the number of keypoints.

Place, publisher, year, edition, pages
IEEE , 2007. 429-434 p.
Keyword [en]
Active Vision, Object Recognition
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-47178DOI: 10.1109/ROBIO.2007.4522200ISBN: 978-1-4244-1761-2 (print)OAI: oai:DiVA.org:kth-47178DiVA: diva2:454555
Conference
IEEE International Conference on Robotics and Biomimetics (ROBIO 2007)
Note
© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111115Available from: 2011-11-15 Created: 2011-11-07 Last updated: 2011-11-15Bibliographically approved

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Citation style
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