Estimation du mouvement fondée sur un schéma direct et rétrograde - Application à la segmentation

Cette thèse traite de la détection et de l'estimation du mouvement dans le contexte de l'analyse de séquence d'images. Plus précisément, le but de ce manuscrit est le développement d'algorithmes d'estimation et de segmentation du flot optique, qui tendent à déterminer les changements relatifs de position des objets visibles dans une scène. Un problème majeur de l'estimation du mouvement est l'insuffisance des contraintes pour rendre l'estimation robuste. Dans notre cas, nous proposons un formalisme qui permet de renforcer les contraintes dans la mise en équation du mouvement. Le formalisme est construit à partir de l'information spatio-temporelle causale et anti-causale (mouvements direct et rétrograde) de deux trames consécutives. Dans un premier temps, le formalisme directrétrograde est testé sur un mouvement de translation. Le second volet dédié à l'estimation consiste en l'extension du formalisme proposé sur un modèle plus général. Pour la segmentation spatio-temporelle, deux catégories de méthode sont évoquées. La première est l'application du schéma direct-rétrograde à la segmentation markovienne. La deuxième catégorie est basée sur la classification utilisant les nuées dynamiques. Pour cela, nous développons une méthode de segmentation qui consiste à associer la méthode K-moyens et le formalisme direct-rétrograde. Le dernier point concerne l'application sur des données réelles. Cette application est réalisée dans le contexte de l'analyse en imagerie sismique fournie par la société GDF.This thesis deals with the motion detection and estimation in the context of the image sequence analysis. More precisely, the goal of this manuscript is the development of optical flow estimation and segmentation algorithms, which rely on the changes of image brightness. The main problem of the motion estimation is the insufficient of constraint for provide a robust estimate. In our case, we tray to develop a formalism which allows to add some constraints in the motion equation. The formalism is carried out in starting from the causal and anti-causal spatio-temporal information (forward an backward motions) of two consecutive frames. Initially, the forward-backward formalism is tested on a translation motion. The second shutter consists of the extension of the suggested formalism on a general model. It is about the parametric model. For the spatio-temporal segmentation, two categories of methods are evoked. The first is the application of the forward-backward formalism to the markovian segmentation. The second category is based on classification using the dynamic clouds. For that, we developed a method of segmentation in which, we associate the K-means algorithm and the forward-backward formalism. Finally, we deal with the application on real data. This application was carried out in the context of the analyse in seismic imagery, provided by the GDF company

Measuring and Modeling Fluid Dynamic Processes using Digital Image Sequence Analysis

In this thesis novel motion models have been developed and incorporated into an extended parameter estimation framework that allows to accurately estimate the parameters and regularize them if needed. The performance of this framework has been increased to real time and implemented on inexpensive graphics hardware. Confidence and situation measures have been designed to discard inaccurate estimates. A phase field approach was developed to estimate piecewise smooth motion while detecting object boundaries at the same time. These algorithmic improvements have been successfully applied to three areas of fluid dynamics: air-sea interaction, microfluidics and plant physiology. At the ocean surface, the fluxes of heat and momentum have been measured with thermographic techniques, both spatially and temporally highly resolved. These measurement techniques present milestones for research in air-sea interaction, where point measurements and particle based laboratory measurements represent the state-of-the art. Calculations were done with two models, both making complement assumptions. Still, results derived from both models agree remarkably well. Measurements were conducted in laboratory settings as well as in the field. Microfluidic flow was measured with a new approach to molecular tagging velocimetry that explicitly models Taylor dispersion. This has lead to an increase in accuracy and applicability. Inaccuracies and problems of previous approaches due to Taylor dispersion were successfully evaded. Ground truth test measurements have been conducted, proving the accuracy of this novel technique. For the first time, flow velocities were measured in the xylem of plant leaves with active thermography. This represents a technique for measuring these flows on extended leaf areas on free standing plants, minimizing the impact caused by the measurement. Ground truth measurements on perfused leafs were performed. Measurements were also conducted on free standing plants in a climatic chamber, to measure xylem flows and relate flow velocities to environmental parameter. With a cuvette, environmental factors were varied locally. These measurements underlined the sensitivity of the new approach. A linear relationship in between flow rates and xylem diameter was found