DocumentCode :
2317803
Title :
A distance for elastic matching in object recognition
Author :
Azencott, Robert ; Coldefy, Francois ; Younes, Laurent
Volume :
1
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
687
Abstract :
We define distances between geometric curves by the square root of the minimal energy required to transform one curve into the other. The energy is formally defined from a left invariant Riemannian distance on an infinite dimensional group acting on the curves, which can be explicitly computed. The obtained distance boils down to a variational problem for which an optimal matching between the curves has be computed. An analysis of the distance when the curves are polygonal leads to a numerical procedure for the solution of the variational problem, which can efficiently be implemented, as illustrated by experiments
Keywords :
computational geometry; computer vision; edge detection; image matching; object recognition; variational techniques; Riemannian distance; computer vision; elastic matching; geometric curves; image matching; infinite dimensional group; minimal energy; object recognition; variational problem; Computer vision; Costs; Laboratories; Object recognition; Optimal matching; Pattern recognition; Robustness; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.546112
Filename :
546112
Link To Document :
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