Welcome on the website of the Paris Seminar on the Mathematics of Imaging.
The goal of this seminar is to cover the fields of the mathematics of imaging in a very wide sense (including for instance signal processing, image processing, computer graphics, computer vision, various applications and connexion with statistics and machine learning). It is open to everyone. It takes place the first Thursday of each month at IHP, from 14:00 to 16:00. Each seminar is composed of two presentations.
You can also subscribe to the mailing list of the seminar.
6 december 2018, 14h-15h, room 314.
Hughes Talbot (CentraleSupelec)
Title: Path operators for thin objects restoration
Abstract: In this talk we will present path operators, which are efficient recursive mathematical morphology connected operators that use paths as structuring elements. These operators are designed to preserve thin objects in images, such as hair, cilia, vessels, oriented textures, etc, which are traditionally very difficult to filter using classical operators in many settings. By combining these filters, we show how we can propose a vesselness operator with significant better performance than the traditional linear operators based on the Hessian (Frangi, Sato, etc) or the structure tensor. We also show recent work on how to use these operators as regularizers in variational frameworks for image restoration, in the context of discrete calculus.
6 december 2018, 15h-16h, room 314.
Denis Fortun (iCUBE, CNRS, Université de Strasbourg)
Title: Fast piecewise-affine motion estimation without segmentation
Abstract: In this talk, we will review existing strategies for regularizing motion fields, and present a new method dedicated to piecewise affine models. Current algorithmic approaches for piecewise affine motion estimation are based on alternating motion segmentation and estimation. In contrast, our method estimates piecewise affine motion directly without intermediate segmentation. To this end, we reformulate the problem by imposing piecewise constancy of the parameter field, and derive a specific proximal splitting optimization scheme. A key component of our framework is an efficient 1D piecewise-affine estimator for vector-valued signals. The first advantage of our approach over segmentation-based methods is its absence of initialization. The second advantage is its lower computational cost, which is independent of the complexity of the motion field. In addition to these features, we demonstrate competitive accuracy with other piecewise-parametric methods on standard evaluation benchmarks. Our new regularization scheme also outperforms the more standard use of total variation and total generalized variation.
The seminar will stop in its usual form during the IHP trimester “The Mathematics of Imaging”.
After that the seminar will start again in october 2019.
Bienvenu sur le site du Séminaire Parisien des Mathématiques Appliquées à l’Imagerie.
Le but de ce séminaire est de couvrir le domaine des mathématiques de l’imagerie. Il est ouvert à tous. Le séminaire a lieu le premier jeudi de chaque mois à l’IHP, de 14h à 16h. Chaque séance est composée de deux exposés.
Vous pouvez également vous abonner ou désabonner à la liste de diffusion du séminaire.