Recognizing objects by matching oriented points
Johnson, A.E.
Hebert, M.
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA;
This paper appears in: Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
Publication Date: 17-19 Jun 1997
On page(s): 684-689
Meeting Date: 06/17/1997 - 06/19/1997
Location: San Juan, Puerto Rico
ISBN: 0-8186-7822-4
References Cited: 14
INSPEC Accession Number: 5644232
Digital Object Identifier: 10.1109/CVPR.1997.609400
Current Version Published: 2002-08-06
Abstract
We present an approach to recognition of complex objects in
cluttered 3-D scenes that does not require feature extraction or
segmentation. Our object representation comprises descriptive images
associated with each oriented point on the surface of an object. Using a
single point basis constructed from an oriented point, the position of
other points on the surface of the object can be described by two
parameters. The accumulation of these parameters for many points on the
surface of the object results in an image at each oriented point. These
images, localized descriptions of the global shape of the object, are
invariant to rigid transformations. Through correlation of images, point
correspondences between a model and scene data are established and then
grouped using geometric consistency. The effectiveness of our algorithm
is demonstrated with results showing recognition of complex objects in
cluttered scenes with occlusion
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