Unrestricted Recognition of 3-D Objects for Robotics Using Multi-Level Triplet Invariants
2004 (English)In: Artificial Intelligence Magazine, Vol. 25, no 2, 51-67 p.Article in journal (Refereed) Published
A method for unrestricted recognition of 3-D objects has been developed. By unrestricted, we imply that the recognition shall be done independently of object position, scale, orientation and pose, against a structured background. It shall not assume any preceding segmentation and 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 feed-back learning procedure, percepts are mapped upon system states corresponding to manipulation parameters of the object. The method uses a learning architecture employing channel information representation.
The paper contains a discussion of how objects can be represented. A structure is proposed 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-37297Local ID: 34530OAI: oai:DiVA.org:liu-37297DiVA: diva2:258146