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Unrestricted recognition of 3D objects for robotics using multilevel triplet invariants
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science.
2004 (English)In: The AI Magazine, ISSN 0738-4602, Vol. 25, no 2, 51-67 p.Article in journal (Refereed) Published
Abstract [en]

A method for unrestricted recognition of three-dimensional objects was developed. By unrestricted, we imply that the recognition will be done independently of object position, scale, orientation, and pose against a structured background. It does not assume any preceding segmentation or allow a reasonable degree of occlusion. The method uses a hierarchy of triplet feature invariants, which are at each level defined by a learning procedure. In the feedback learning procedure, percepts are mapped on system states corresponding to manipulation parameters of the object. The method uses a learning architecture with channel information representation. This article discusses how objects can be represented. We propose a structure to deal with object and contextual properties in a transparent manner.

Place, publisher, year, edition, pages
2004. Vol. 25, no 2, 51-67 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-48326OAI: oai:DiVA.org:liu-48326DiVA: diva2:269222
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-12

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Granlund, GöstaMoe, Anne

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