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Proceedings Paper

Model-based matching using elliptical features
Author(s): James R. Burrill; Sharon X. Wang; Art Barrow; Mike Friedman; Matt Soffen
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Paper Abstract

This paper describes a method of using elliptical features in model matching that forms the basis of a system for vehicle detection and classification. The novelty of the system is the employment of an algorithm that utilizes both line and ellipse features simultaneously. The baseline algorithm has been successfully used in images, which contain straight line features, to find a discrete correspondence between an object model and image features and to determine the pose of the object in the image relative to the camera. This research enhances the baseline algorithm by using elliptical image features to recognize circular objects in a model. Elliptical features show many desired properties in recognition. Utilizing these features not only increases the confidence level of detection and classification, but also provides the system with a good initial pose for a more robust performance.

Paper Details

Date Published: 24 May 1996
PDF: 11 pages
Proc. SPIE 2756, Automatic Object Recognition VI, (24 May 1996); doi: 10.1117/12.241136
Show Author Affiliations
James R. Burrill, Amerinex Applied Imaging, Inc. (United States)
Sharon X. Wang, ID Vision, Inc. (United States)
Art Barrow, Amerinex Applied Imaging, Inc. (United States)
Mike Friedman, Amerinex Applied Imaging, Inc. (United States)
Matt Soffen, Amerinex Applied Imaging, Inc. (United States)


Published in SPIE Proceedings Vol. 2756:
Automatic Object Recognition VI
Firooz A. Sadjadi, Editor(s)

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