24 May 1996 Model-based matching using elliptical features
Author Affiliations +
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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James R. Burrill, Sharon X. Wang, Art Barrow, Mike Friedman, Matt Soffen, "Model-based matching using elliptical features", Proc. SPIE 2756, Automatic Object Recognition VI, (24 May 1996); doi: 10.1117/12.241136; https://doi.org/10.1117/12.241136
PROCEEDINGS
11 PAGES


SHARE
RELATED CONTENT

Three-dimensional model alignment without computing pose
Proceedings of SPIE (April 01 1992)
3D object parts inference from range image data
Proceedings of SPIE (January 09 1997)
Grouping-based recognition system
Proceedings of SPIE (February 01 1992)
Detection of buildings by fusion of range and image data
Proceedings of SPIE (August 17 1994)

Back to Top