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Geodesic Matching with Free Extremities
Authors:Laurent Garcin  Laurent Younes
Affiliation:(1) Laboratoire MATIS, Institut Géographique National, Saint Mande Cedex;(2) Center for Imaging Science, Department of Appplied Mathematics and Statistics, Johns Hopkins University, Baltimore
Abstract:In this paper, we describe how to use geodesic energies defined on various sets of objects to solve several distance related problems. We first present the theory of metamorphoses and the geodesic distances it induces on a Riemannian manifold, followed by classical applications in landmark and image matching. We then explain how to use the geodesic distance for new issues, which can be embedded in a general framework of matching with free extremities. This is illustrated by results on image and shape averaging and unlabeled landmark matching. Laurent Garcin is a former student of the Ecole Polytechnique. He obtained his Ph.D. in 2004 at the Ecole Normale de Cachan, working on matching methods for landmarks and images. He is an engineer at the French National Geographic Institute. Laurent Younes is a former student of the Ecole Normale Superieure in Paris. He was awarded the Ph.D. from the University Paris Sud in 1989, and the thesis advisor certification from the same university in 1995. He works on the statistical analysis of images and shapes, and on modeling shape deformations and shape spaces. Laurent Younes entered CNRS, the French National Research Center in October 1991, in which he has been a “Directeur de Recherche" until 2003. He is now a professor at the Department of Applied Mathematics and Statistics Department and the Center for Imaging Science at Johns Hopkins University in July 2003.
Keywords:geodesic distance  image matching  shape matching  deformable templates  K?rcher mean
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