Unrestricted recognition of 3D objects for robotics using multilevel triplet invariants
2004 (English)In: The AI Magazine, ISSN 0738-4602, Vol. 25, no 2, 51-67 p.Article in journal (Refereed) Published
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.
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-48326OAI: oai:DiVA.org:liu-48326DiVA: diva2:269222