Search For:

Displaying 1-8 out of 8 total
Stochastic Filtering of Level Sets for Curve Tracking
Found in: Pattern Recognition, International Conference on
By Christophe Avenel, Etienne Mémin, Patrick Pérez
Issue Date:August 2010
pp. 3553-3556
This paper focuses on the tracking of free curves using non-linear stochastic filtering techniques. It relies on a particle filter which includes color measurements. The curve and its velocity are defined through two coupled implicit level set representati...
 
A Stochastic Filtering Technique for Fluid Flow Velocity Fields Tracking
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Anne Cuzol, Etienne Mémin
Issue Date:July 2009
pp. 1278-1293
In this paper, we present a method for the temporal tracking of fluid flow velocity fields. The technique we propose is formalized within a sequential Bayesian filtering framework. The filtering model combines an Itô diffusion process coming from a stochas...
 
Dynamically consistent optical flow estimation
Found in: Computer Vision, IEEE International Conference on
By Nicolas Papadakis, Thomas Corpetti, Etienne Memin
Issue Date:October 2007
pp. 1-7
In this paper, we present a framework for dynamic consistent estimation of dense motion fields over a sequence of images. The originality of the approach is to exploit recipes related to optimal control theory. This setup allows performing the estimation o...
 
Variational optimal control technique for the tracking of deformable objects
Found in: Computer Vision, IEEE International Conference on
By Nicolas Papadakis, Etienne Memin
Issue Date:October 2007
pp. 1-7
In this paper, a new framework for the tracking of closed curves is described. The proposed approach, formalized through an optimal control technique, enables a continuous tracking along an image sequence of a deformable curve. The associated minimization ...
 
Dense Estimation of Layer Motions in the Atmosphere
Found in: Pattern Recognition, International Conference on
By Patrick Heas, Etienne Memin, Nicolas Papadakis
Issue Date:August 2006
pp. 1-4
In this paper, we address the problem of estimating dense motion fields related to a stratified atmosphere which is observed through satellite imagery. Estimating the evolving vertical distribution of horizontal wind fields from satellite image time series...
 
A Stochastic Filter for Fluid Motion Tracking
Found in: Computer Vision, IEEE International Conference on
By Anne Cuzol, Etienne Mémin
Issue Date:October 2005
pp. 396-402
In this paper we present a method for the tracking of fluid flows velocity fields. The technique we propose is formalized within sequential Bayesian filter framework. The filter we propose here combines an Itô diffusion process coming from a stochastic for...
 
An Energy-Based Framework for Dense 3D Registration of Volumetric Brain Images
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Pierre Hellier, Christian Barillot, Étienne Mémin, Patrick Pérez
Issue Date:June 2000
pp. 2270
In this paper, we describe a new method for medical image registration. The registration is formulated as a minimization problem involving robust estimators. We propose an efficient hierarchical optimization framework, which is both multiresolution and mul...
 
Fluid Motion Recovery by Coupling Dense and Parametric Vector Fields
Found in: Computer Vision, IEEE International Conference on
By Étienne Mémin, Patrick Pérez
Issue Date:September 1999
pp. 620
In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques are not well adapted and more dedicated approaches have to be designed.In thi...
 
 1