Surface classification: hypothesis testing and parameter estimation
Flynn, P.J.
Jain, A.K.
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI;
This paper appears in: Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Publication Date: 5-9 Jun 1988
On page(s): 261-267
Meeting Date: 06/05/1988 - 06/09/1988
Location: Ann Arbor, MI, USA
ISBN: 0-8186-0862-5
References Cited: 20
INSPEC Accession Number: 3258524
Digital Object Identifier: 10.1109/CVPR.1988.196246
Current Version Published: 2002-08-06
Abstract
A 3-D surface classification method based on the quadric surface
model is described. This technique does not require the points from the
surface to lie on a grid. A sample of surface points is classified as
planar or nonplanar through two hypothesis tests. If the sample is
nonplanar, curvature features are evaluated at each point to classify
the sample as spherical, cylindrical, or conical. A nonlinear
optimization technique is then used to refine the parameters (e.g.
radius, orientation) of the resulting surface type
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