Publication

SHAPE PRIOR BASED ON STATISTICAL MAP FOR ACTIVE CONTOUR SEGMENTATION

Publications associées (38)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Fast Parametric Snakes For 3D Microscopy

Michaël Unser, Ricard Delgado Gonzalo

We present a new fast active contour for images in 3D microscopy. We introduce a fully parametric design that relies on exponential B-spline bases and allows us to impose a sphere-like topology. The proposed 3D snake can approximate blob-like objects with ...

Ieee2012

Fast Parametric Snakes for 3D Microscopy

Michaël Unser, Ricard Delgado Gonzalo

IEEE2012

We report on maximum entropy method study of the experimental atomic and ionic charges of LiBD4 in its low-temperature orthorhombic phase. Synchrotron radiation x-ray powder diffraction data, neutron powder diffraction data, and density functional calculat ...

2011

Learning in Gaussian Markov random fields

Thomas Riedl

This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown parameter. Thus in order to support the state estimator with prior information o ...

2010

Combining Geometric and Appearance Priors for Robust Homography Estimation

Pascal Fua, Vincent Lepetit, Mustafa Özuysal

The homography between pairs of images are typically computed from the correspondence of keypoints, which are established by using image descriptors. When these descriptors are not reliable, either because of repetitive patterns or large amounts of clutter ...

2010

One Step Impulse Radio Ultra-WideBand Positioning Algorithm

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We consider the problem of positioning estimation with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths and additive Gaussian noise environments. Most popular positioning algorithms first estimate certain parameters (such as time of arr ...

IEEE2009

A Novel Bayesian Impulse Radio Ultra-WideBand Ranging Algorithm

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under weak Line Of Sight (LOS) environments and additive Gaussian noise. We use a Bayesian approach where the prior distribution of the channel follows the IEEE 802.15.4a ...

IEEE2009

A MAP Approach to Noise Compensation of Speech

Philip Neil Garner

We show that estimation of parameters for the popular Gaussian model of speech in noise can be regularised in a Bayesian sense by use of simple prior distributions. For two example prior distributions, we show that the marginal distribution of the uncorrup ...

Idiap2009

Novel Algorithms on Impulse Radio Ultra-WideBand Ranging

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We consider the problem of ranging with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths propagation environments and additive Gaussian noise. We propose a Bayesian detection algorithm where the prior distribution of the channel follows ...

IEEE2009

Saddlepoint approximation for mixture models

Anthony Christopher Davison

Two-component mixture distributions with one component a point mass and the other a continuous density may be used as priors for Bayesian inference when sparse representation of an underlying signal is required. We show how saddlepoint approximation in suc ...

2009