Paper Info
Title
A Statistical Model to Describe Invariants Extracted from a 3-D Quadric Surface Patch and Its Applications in Region-Based Recognition
Abstract
A statistical model, describing noise-disturbed invariants extracted from a surface patch of a range image, has been developed and applied to region based pose estimation and classification of 3D quadrics. The Mahalanobis dis- tance, which yields the same results as a Baysian classi- fier, is used for the classification of the surface patches. The results, compared with the Euclidean distance, appear to be much more reliable reliable.
Year
DOI
Venue
1998
10.1109/ICPR.1998.711232
ICPR
Keywords
Field
DocType
3-d quadric surface patch,region-based recognition,statistical model,statistics,statistical analysis,image classification,machine vision,noise,pose estimation,read only memory,data acquisition,euclidean distance,mahalanobis distance
Computer vision,Pattern recognition,Euclidean distance,Mahalanobis distance,Pose,Artificial intelligence,Invariant (mathematics),Statistical model,Contextual image classification,Mathematics,Quadric,Quadratic classifier
Conference
ISSN
ISBN
Citations 
1051-4651
0-8186-8512-3
3
PageRank 
References 
Authors
1.68
4
5
Name
Order
Citations
PageRank
G Y. Wang131.68
Z. Houkes2185.64
P P. L. Regtien3356.10
M J. Korsten453.35
G R. Ji531.68