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Proceedings Paper

FST-based active object recognition for automated assembly
Author(s): Michael A. Sipe; David P. Casasent
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Paper Abstract

We demonstrate the use of our active object recognition algorithms in a mechanical assembly task. The algorithms are used to classify and estimate the pose of parts of the assembly in different stable rest positions and automatically re-position the camera if the class or pose of an object is ambiguous in a given image. Multiple object views are used in determining both the final object class and pose estimate. The FSTs are analyzed off-line to determine the camera positions that best resolve ambiguities. We also describe methods for rejecting untrained objects and adding new parts to an existing set of FSTs using a new feature update method.

Paper Details

Date Published: 26 August 1999
PDF: 12 pages
Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); doi: 10.1117/12.360284
Show Author Affiliations
Michael A. Sipe, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 3837:
Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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