A complete and extendable approach to visual recognition
Bolle, R.M.
Califano, A.
Kjeldsen, R.
IBM T.J. Watson Res. Center, Yorktown Heights, NY ;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: May 1992
Volume: 14,
Issue: 5
On page(s): 534-548
ISSN: 0162-8828
References Cited: 48
CODEN: ITPIDJ
INSPEC Accession Number: 4185377
Digital Object Identifier: 10.1109/34.134058
Current Version Published: 2002-08-06
Abstract
A framework for 3D object recognition is presented. Its
flexibility and extensibility are accomplished through a uniform,
parallel, and modular recognition architecture. Concurrent and stacked
parameter transforms reconstruct a variety of features from the input
scene. At each stage, constraint satisfaction networks collect and fuse
the evidence obtained through the parameter transforms, ensuring a
globally consistent interpretation of the input scene and allowing for
the integration of diverse types of information. The final
interpretation of the scene is a small consistent subset of the many
initial hypotheses about partial features, primitive features, feature
assemblies, and 3D objects computed by the various parameter transforms.
A complete, integrated, and implemented system that extracts planar
surfaces, patches of quadrics of revolution, and planar intersection
curves of these surfaces from a depth map viewing 3D objects is
described. Experimental results on the recognition behavior of the
system are presented
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