Sharp template estimation in a shifted curves model

Bayesian posterior consistency in the functional randomly shifted curves model

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Parameter estimation for a deformable template model

SUMMARY High–level image analysis is an area which has seen considerable research interest in the past few years. In particular the task of object recognition has been successfully tackled using deformable template models in a Bayesian context. However these models are not being widely used in practise , and one of the reasons for this may be that they do require a number of rather non-intuitiv...

Reconstructing Curves with Sharp Corners

A Bayesian Generative Model for Surface Template Estimation

3D surfaces are important geometric models for many objects of interest in image analysis and Computational Anatomy. In this paper, we describe a Bayesian inference scheme for estimating a template surface from a set of observed surface data. In order to achieve this, we use the geodesic shooting approach to construct a statistical model for the generation and the observations of random surface...

Sharp Adaptive Estimation by a Blockwise Method

We consider a blockwise James-Stein estimator for nonparametric function estimation in suitable wavelet or Fourier bases. The estimator can be readily explained and implemented. We show that the estimator is asymptotically sharp-adaptive in minimax risk over any Sobolev ball containing the true function. Further, for a moderately broad range of bounded sets in Besov space our estimator is asymp...