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Proceedings Paper

Multilevel evidence fusion for the recognition of 3-D objects: an overview of computer vision research at IBM/T.J. Watson
Author(s): Ruud M. Bolle; Andrea Califano; John R. Kender; Rick Kjeldsen; Rakesh Mohan
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Paper Abstract

We describe the research activities of the Exploratory Computer Vision Group at the IBM Thomas J. Watson Research Center; this is a follow-up of the work reported previously.6 The focus of the ongoing work is the development of an experimental vision system for recognition of 3D objects. The thrust of the development of the vision system is to investigate techniques that may lead to a system that scales with the size of the problem; here, by the size of the problem, we mean the complexity of the scene - the number of object in the scene - and, the number of objects in the database - i.e., the number of objects that the system can recognize. Fusion is a recurring theme in our research. E.g., fusion of evidence about different features extracted from the data; fusion of information obtained at different points in the image; fusion of information extracted from high and low-resolution images. Therefore, rather than focussing on a particular aspect of our work, we present an overview of the work.

Paper Details

Date Published: 1 April 1991
PDF: 14 pages
Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25267
Show Author Affiliations
Ruud M. Bolle, IBM/Thomas J. Watson Research Ctr. (United States)
Andrea Califano, IBM/Thomas J. Watson Research Ctr. (United States)
John R. Kender, IBM/Thomas J. Watson Research Ctr. (United States)
Rick Kjeldsen, IBM/Thomas J. Watson Research Ctr. (United States)
Rakesh Mohan, IBM/Thomas J. Watson Research Ctr. (United States)


Published in SPIE Proceedings Vol. 1383:
Sensor Fusion III: 3D Perception and Recognition
Paul S. Schenker, Editor(s)

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