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Stéphanie Allassonnière; Jérémie Bigot; Joan Alexis Glaunès; Florian Maire; Frédéric J.P. Richard
Statistical models for deformable templates in image and shape analysis
(Modèles statistiques d’atlas déformables pour l’analyse d’images et de formes)
Annales mathématiques Blaise Pascal, 20 no. 1 (2013), p. 1-35, doi: 10.5802/ambp.320
Article PDF | Reviews MR 3112238 | Zbl 1294.62121
Class. Math.: 62H12, 62H30, 62H35
Keywords: Review paper, Deformable template model, statistical analysis

Résumé - Abstract

High dimensional data are more and more frequent in many application fields. It becomes particularly important to be able to extract meaningful features from these data sets. Deformable template model is a popular way to achieve this. This paper is a review on the statistical aspects of this model as well as its generalizations. We describe the different mathematical frameworks to handle different data types as well as the deformations. We recall the theoretical convergence properties of the estimators and the numerical algorithm to achieve them. We end with some published examples.


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