Reconciling Landmarks and Level Sets

Pierre Maurel 1, 2 Renaud Keriven 2, 3 Olivier Faugeras 2
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
Abstract : Shape warping is a key problem in statistical shape analysis. This paper proposes a framework for geometric shape warping based on both shape distances and landmarks. Our method is compatible with implicit representations and a matching between shape surfaces is provided at no additional cost. It is, to our knowledge, the rst time that landmarks and shape distances are reconciled in a pure geometric level set framework. The feasibility of the method is demonstrated with two- and three-dimensional examples. Combining shape distance and landmarks, our approach reveals to need only a small number of landmarks to obtain improvements on both warping and matching.
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Pierre Maurel, Renaud Keriven, Olivier Faugeras. Reconciling Landmarks and Level Sets. ICPR 2006, 18th International Conference on Pattern Recognition, Aug 2006, Hong-Kong, China. pp.69-72, ⟨10.1109/ICPR.2006.979⟩. ⟨inria-00608094⟩

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