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Paper Detail

Paper:	SS-1.2
Session:	Statistical Inferences on Nonlinear Manifolds with Applications in Signal and Image Processing
Time:	Tuesday, May 16, 10:50 - 11:10
Presentation:	Special Session Lecture
Topic:	Special Sessions: Statistical inferences on nonlinear manifolds with applications in signal and image processing
Title:	GENERATIVE MODEL AND CONSISTENT ESTIMATION ALGORITHMS FOR NON-RIGID DEFORMABLE MODELS
Authors:	Stephanie Allassonni`ere, E. Kuhn, LAGA - Université Paris, France; Alain Trouve, CMLA - ENS de Cachan, France; Yali Amit, University of Chicago, United States
Abstract:	The link between Bayesian and variational approaches is well known in the image analysis community in particular in the context of deformable models. However, true generative models and consistent estimation procedures are usually not available and the current trend is the computation of statistics mainly based on PCA analysis. We advocate in this paper a careful statistical modeling of deformable structures and we propose an effective and consistent estimation algorithm for the various parameters (geometric and photometric) appearing in the models.