Generalized multidimensional scaling: a framework for isometry-invariant partial surface matching

An efficient algorithm for isometry-invariant matching of surfaces is presented. The key idea is computing the minimum-distortion mapping between two surfaces. For this purpose, we introduce the generalized multidimensional scaling, a computationally efficient continuous optimization algorithm for f...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS Vol. 103; no. 5; p. 1168
Main Authors: Bronstein, Alexander M, Bronstein, Michael M, Kimmel, Ron
Format: Journal Article
Language:English
Published: United States 31.01.2006
Subjects:
Algorithms
Computer Simulation
Computers
Face
Hand - anatomy & histology
Humans
Kinetics
Models, Statistical
Models, Theoretical
Pattern Recognition, Physiological
Pattern Recognition, Visual
Software
Surface Properties
ISSN:0027-8424
Online Access:Get more information
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Summary:An efficient algorithm for isometry-invariant matching of surfaces is presented. The key idea is computing the minimum-distortion mapping between two surfaces. For this purpose, we introduce the generalized multidimensional scaling, a computationally efficient continuous optimization algorithm for finding the least distortion embedding of one surface into another. The generalized multidimensional scaling algorithm allows for both full and partial surface matching. As an example, it is applied to the problem of expression-invariant three-dimensional face recognition.
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ISSN:0027-8424
DOI:10.1073/pnas.0508601103