DocumentCode :
3207527
Title :
Elastic-string models for representation and analysis of planar shapes
Author :
Mio, Washington ; Srivastava, Anuj
Author_Institution :
Dept. of Math., Florida State Univ., Tallahassee, FL, USA
Volume :
2
fYear :
2004
fDate :
27 June-2 July 2004
Abstract :
We develop a new framework for the quantitative analysis of shapes of planar curves. Shapes are modeled on elastic strings that can be bent, stretched or compressed at different rates along the curve. Shapes are treated as elements of a space obtained as the quotient of an infinite-dimensional Riemannian manifold of elastic curves by the action of a reparameterization group. The Riemannian metric encodes the elastic properties of the string and has the property that reparameterizations act by isometrics. The geodesies in shape space are used to quantify shape dissimilarities, interpolate and extrapolate shapes, and align shapes according to their elastic properties. The shape spaces and metrics constructed offer a novel environment for the study of shape statistics and for the investigation and simulation of shape dynamics.
Keywords :
differential geometry; image representation; object recognition; statistical analysis; Riemannian metric; elastic-string models; infinite-dimensional Riemannian manifold; planar curve shapes; quantitative analysis; shape dissimilarities; Algorithm design and analysis; Deformable models; Image analysis; Infrared detectors; Interpolation; Magnetic resonance imaging; Mathematics; Shape; Statistical analysis; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-2158-4
Type :
conf
DOI :
10.1109/CVPR.2004.1315138
Filename :
1315138
Link To Document :
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