Mon travail de thèse consiste en la mise en place d'une méthode de reconstruction 3D. Les objets à reconstruire sont des petits corps du système solaire qui ont été observée dans le domaine visible par des sondes lors de missions spatiales. La méthode proposée (appelée photoclinométrie par déformation) consiste à déformer un maillage jusqu'à ce que les images synthétiques de ce maillage correspondent aux images observées, ceci s'effectue au sein d'une boucle d'optimisation. Cette méthode nécessitant un maillage de départ proche de la solution souhaitée, nous avons implémenter cette méthode au sein d'un schéma multirésolution (multirésolution photoclinométrie par déformation) permettant d'obtenir une reconstruction sans apriori de forme. Cependant cette méthode ne permet pas d'obtenir de modèles contenant des millions de facettes. Une troisième méthode a donc été développé pour pallier ce problème, elle consiste à découper le maillage en différents morceaux et à appliquer la méthode multirésolution photoclinométrie par déformation à chacun de ces morceaux. Par fusion de ces morceaux, on arrive ainsi à obtenir des maillages de plusieurs millions de facettes (modèle haute résolution). Ces méthodes ont été testées avec la reconstruction des deux astéroïdes (Steins and lutetia) survolé par la sonde Rosetta de l'Agence Spatiale Européenne (ESA). / My PhD work consists in the establishment of a method of 3D reconstruction. Studied objects are small solar system bodies that have been observed in the visible range by sensors during space missions. The proposed method (called photoclinometry by deformation ) consists in deforming a mesh until the synthetic images of the mesh correspond to the observed ones, this is done in an optimization loop . This method requires an initial mesh close to the desired solution. We implement this method in a multiresolution scheme (multiresolution photoclinometry by deformation) to obtain a reconstruction without an apriori shape . However, this method does not allow models containing millions of facets . A third method has been developed to overcome this problem, it consists in cutting the mesh into different pieces and apply the multiresolution method photoclinometry by deforming to each of these pieces . By merging these pieces , we obtain meshes of several millions facets (high resolution model). These methods have been tested by reconstructing the two asteroids (Steins and lutetia) flown-by the Rosetta spacecraft of the European Space Agency (ESA).

Este trabalho apresenta um estudo sobre segmentação de volumes médicos e uma solução para se obter malhas poligonais de pacientes específicos para uso em simulações de cirurgia. Malhas de pacientes específicos são importantes para planejamento de intervenções cirúrgicas e permitem uma melhor visualização de condições patológicas em um paciente, coisa não obtível em malhas geradas artisticamente. Nós analisamos quais são os fatores complicantes para se obter estas malhas de um paciente específico usando apenas imagens médicas obtidas em exames padrões. Para isso, nós revisamos diversos métodos existentes para segmentação de volumes médicos. Isso nos levou a definir os problemas com as técnicas existentes, e a desenvolver um método que não sofra destes problemas, utilizando pouca interação humana e não tendo dependências de mais dados que não o exame do paciente. Nosso alvo para obter malhas especificas foram órgãos de tecido mole, que são um caso especialmente complicado da área, graças a várias questões relacionadas às imagens médicas e à anatomia humana. Atacamos esse problema aplicando modificações geométricas em malhas especiais, que deformam até atingir a forma dos órgãos que se deseja segmentar. Os resultados mostram que nossa técnica conseguiu obter malhas específicas de pacientes a partir de volumes médicos com qualidade superior a de outros algoritmos de mesma classe. Graças a simplicidade do método desenvolvido, nossos resultados são facilmente implementáveis e reproduzidos. / This work presents a study about medical-volume segmentation and a solution to generate patient-specific meshes to use in patient-specific surgery simulations. Patientspecific meshes are useful assets for surgery planning and to allow better visualization of certain pathological conditions of a given patient, which are not obtainable by artistically designed meshes. We analyzed what are the complications to obtain a patient-specific mesh using only standard medical imagery exams. For that, we reviewed several medical volume segmentation techniques. It led us to define the problems within the existing techniques and to develop a method that does not suffer from these problems, with the least possible user interaction or relying on any other data other then the patient exam. Our target for obtaining specific meshes were soft tissue organs, which are a specially complicated case due to various issues related to the medical images and human anatomy. This is accomplished by geometrical operations over special meshes that deform until achieving the shape of the desired organ. Results show that our technique was able to obtain patient-specific meshes from medical images with superior quality than algorithms of the same class. Thanks to the simplicity of the developed approach, its also easy to implement and to reproduce our obtained results.

Geometric reconstruction of dynamic objects is a fundamental task of computer vision and graphics, and modeling human body of high fidelity is considered to be a core of this problem. Traditional human shape and motion capture techniques require an array of surrounding cameras or subjects wear reflective markers, resulting in a limitation of working space and portability. In this dissertation, a complete process is designed from geometric modeling detailed 3D human full body and capturing shape dynamics over time using a flexible setup to guiding clothes/person re-targeting with such data-driven models. As the mechanical movement of human body can be considered as an articulate motion, which is easy to guide the skin animation but has difficulties in the reverse process to find parameters from images without manual intervention, we present a novel parametric model, GMM-BlendSCAPE, jointly taking both linear skinning model and the prior art of BlendSCAPE (Blend Shape Completion and Animation for PEople) into consideration and develop a Gaussian Mixture Model (GMM) to infer both body shape and pose from incomplete observations. We show the increased accuracy of joints and skin surface estimation using our model compared to the skeleton based motion tracking. To model the detailed body, we start with capturing high-quality partial 3D scans by using a single-view commercial depth camera. Based on GMM-BlendSCAPE, we can then reconstruct multiple complete static models of large pose difference via our novel non-rigid registration algorithm. With vertex correspondences established, these models can be further converted into a personalized drivable template and used for robust pose tracking in a similar GMM framework. Moreover, we design a general purpose real-time non-rigid deformation algorithm to accelerate this registration. Last but not least, we demonstrate a novel virtual clothes try-on application based on our personalized model utilizing both image and depth cues to synthesize and re-target clothes for single-view videos of different people.

Este trabalho apresenta um estudo sobre segmentação de volumes médicos e uma solução para se obter malhas poligonais de pacientes específicos para uso em simulações de cirurgia. Malhas de pacientes específicos são importantes para planejamento de intervenções cirúrgicas e permitem uma melhor visualização de condições patológicas em um paciente, coisa não obtível em malhas geradas artisticamente. Nós analisamos quais são os fatores complicantes para se obter estas malhas de um paciente específico usando apenas imagens médicas obtidas em exames padrões. Para isso, nós revisamos diversos métodos existentes para segmentação de volumes médicos. Isso nos levou a definir os problemas com as técnicas existentes, e a desenvolver um método que não sofra destes problemas, utilizando pouca interação humana e não tendo dependências de mais dados que não o exame do paciente. Nosso alvo para obter malhas especificas foram órgãos de tecido mole, que são um caso especialmente complicado da área, graças a várias questões relacionadas às imagens médicas e à anatomia humana. Atacamos esse problema aplicando modificações geométricas em malhas especiais, que deformam até atingir a forma dos órgãos que se deseja segmentar. Os resultados mostram que nossa técnica conseguiu obter malhas específicas de pacientes a partir de volumes médicos com qualidade superior a de outros algoritmos de mesma classe. Graças a simplicidade do método desenvolvido, nossos resultados são facilmente implementáveis e reproduzidos. / This work presents a study about medical-volume segmentation and a solution to generate patient-specific meshes to use in patient-specific surgery simulations. Patientspecific meshes are useful assets for surgery planning and to allow better visualization of certain pathological conditions of a given patient, which are not obtainable by artistically designed meshes. We analyzed what are the complications to obtain a patient-specific mesh using only standard medical imagery exams. For that, we reviewed several medical volume segmentation techniques. It led us to define the problems within the existing techniques and to develop a method that does not suffer from these problems, with the least possible user interaction or relying on any other data other then the patient exam. Our target for obtaining specific meshes were soft tissue organs, which are a specially complicated case due to various issues related to the medical images and human anatomy. This is accomplished by geometrical operations over special meshes that deform until achieving the shape of the desired organ. Results show that our technique was able to obtain patient-specific meshes from medical images with superior quality than algorithms of the same class. Thanks to the simplicity of the developed approach, its also easy to implement and to reproduce our obtained results.

Este trabalho apresenta um estudo sobre segmentação de volumes médicos e uma solução para se obter malhas poligonais de pacientes específicos para uso em simulações de cirurgia. Malhas de pacientes específicos são importantes para planejamento de intervenções cirúrgicas e permitem uma melhor visualização de condições patológicas em um paciente, coisa não obtível em malhas geradas artisticamente. Nós analisamos quais são os fatores complicantes para se obter estas malhas de um paciente específico usando apenas imagens médicas obtidas em exames padrões. Para isso, nós revisamos diversos métodos existentes para segmentação de volumes médicos. Isso nos levou a definir os problemas com as técnicas existentes, e a desenvolver um método que não sofra destes problemas, utilizando pouca interação humana e não tendo dependências de mais dados que não o exame do paciente. Nosso alvo para obter malhas especificas foram órgãos de tecido mole, que são um caso especialmente complicado da área, graças a várias questões relacionadas às imagens médicas e à anatomia humana. Atacamos esse problema aplicando modificações geométricas em malhas especiais, que deformam até atingir a forma dos órgãos que se deseja segmentar. Os resultados mostram que nossa técnica conseguiu obter malhas específicas de pacientes a partir de volumes médicos com qualidade superior a de outros algoritmos de mesma classe. Graças a simplicidade do método desenvolvido, nossos resultados são facilmente implementáveis e reproduzidos. / This work presents a study about medical-volume segmentation and a solution to generate patient-specific meshes to use in patient-specific surgery simulations. Patientspecific meshes are useful assets for surgery planning and to allow better visualization of certain pathological conditions of a given patient, which are not obtainable by artistically designed meshes. We analyzed what are the complications to obtain a patient-specific mesh using only standard medical imagery exams. For that, we reviewed several medical volume segmentation techniques. It led us to define the problems within the existing techniques and to develop a method that does not suffer from these problems, with the least possible user interaction or relying on any other data other then the patient exam. Our target for obtaining specific meshes were soft tissue organs, which are a specially complicated case due to various issues related to the medical images and human anatomy. This is accomplished by geometrical operations over special meshes that deform until achieving the shape of the desired organ. Results show that our technique was able to obtain patient-specific meshes from medical images with superior quality than algorithms of the same class. Thanks to the simplicity of the developed approach, its also easy to implement and to reproduce our obtained results.

Cílem mé disertační práce je analyzovat a vyvinout parametrizační metodu pro 2D a 3D tvarové optimalizace v kontextu průmyslového aerodynamického návrhu letounu založeném na CFD simulacích. Aerodynamická tvarová optimalizace je efektivní nástroj, který si klade za cíl snížení nákladů na návrh letounů. Nástroj založený na automatickém hledání optimálního tvaru. Klíčovou částí úspěšného optimalizačního procesu je použití vhodné parametrizační metody, metody schopné garantovat možnost dosažení optimálního tvaru. Parametrizační metody obecně používané v oblasti aerodynamické tvarové optimalizace momentálně nejsou připravený na komplikované průmyslové aplikace vyskytující se u moderních dopravních letounů, které mají šípová zalomená křídla s winglety a motorovými gondolami, přechodové prvky spojující např. trup s křídlem atd.. Existuje tedy potřeba nalezení obecné parametrizační metody, která bude aplikovatelná na širokou škálu různých geometrických tvarů. Free-Form Deformation (FFD[1]) parametrizace může, vzhledem ke svým schopnostem při zacházení s geometrií, být odpovědí na tuto potřebu. Adaptivní parametrizace by se měla být schopna automaticky přizpůsobit danému tvaru tak, aby byly její kontrolní body vhodně rozmístěny. Což umožní dostatečnou kontrolu deformací objektu, která zaručí možnost vytvoření optimálního tvaru objektu a splnění geometrických omezení. Primární aplikací takové parametrizační metody je deformace tvaru objektu. Dalším navrhovaným cílem je modifikace FFD parametrizační metody pro současné deformace tvaru objektu a CFD výpočetní sítě, umožnující velké deformace objektu při zachování kvality výpočetní sítě.

A ring mesh is a large-scale manufacturable structure with versatile applications in architecture and for protective systems. However, the static and dynamic numerical simulation of a large-scale ring mesh is a resource-intensive task due to the many nonlinear contact points between the individual rings. To characterize the rigid body behavior of the ring mesh, in this paper, a representative volume element is loaded under different in-plane directions. The Green-Lagrangian strain tensor components are obtained as a result. An implicit one-step algorithm is used for this dynamic relaxation issue, modified by the use of stiff springs. Static convergence positions of a representative volume element are determined in several multiaxial tensile directions. The obtained deformation parameters can be used to simulate large deformations of large-scaled ring meshes.

Cette thèse porte sur le développement d’un modèle numérique de l’affouillement causée par des obstacles montes sur le lit, combinant les processus hydrodynamiques et morphologiques. Le modèle numérique est basé sur le solveur de champ d’écoulement polyphasique de l’outil CFD open-source OpenFOAMR qui est distribue par OpenCFD Ltd. Le module hydrodynamique du modèle résout les équations de Navier-Stokes avec moyennes de Reynolds (RANS) et les modèles des turbulences k-ε ou k-ω. Il existe deux interfaces dans le domaine de simulation: la surface libre entre l’eau et l’air, qui est suivi par la méthode de Volume de Fluide (VOF); et l’interface entre l’eau et le lit du sédiment, qui est représentée par un maillage de surface finie déformable construit à partir de la limite en bas du maillage de volume fini. En outre, un module morphologique qui a été développé dans le cadre du projet se compose de trois composantes: un modèle de transport de sédiments comprenant la charge suspendue et le charriage; l’équation d’Exner pour mesurer la déformation du lit; et un mécanisme de glissement du sable pour limiter la pente du lit à être plus petite que l’angle de repos du sédiment. Le changement morphologique est incorporé dans le modèle hydrodynamique par la déformation du maillage. Des conditions limites spéciales et des corrections nécessaires pour le calcul en parallèle sont également ajoutées au modèle. Chaque partie du modèle est validée séparément avec les tests préliminaires correspondants, y compris les fonctions de paroi rugueuse, les performances de la méthode VOF, le modèle de transport de charge suspendu et le mécanisme de glissement de sable. Le modèle numérique est ensuite appliqué pour étudier un affouillent bidimensionnelle cause par un jet immerge provenant d’une ouverture sous écluse. Comparaison des résultats de la simulation avec des données expérimentales prouve la capacité du modèle. Et les limites du modèle sont également discutées. Enfin, le modèle est appliqué à l’étude du champ d’écoulement tridimensionnel et de la formation d’affouillement autour d’un obstacle dans l’écoulement. Tout d’abord, la déformation du lit n’est pas activée. Le tourbillon en fer à cheval devant un obstacle et le champ d’écoulement turbulent autour d’un cylindre sur un lit lisse ou rugueux sont simulés. Deux types de simulation pour le module hydrodynamique sont effectués: une simulation qui utilise une surface fixe et rigide pour représenter l’interface air-eau, et une simulation incluant à la fois les domaines de l’eau et de l’air avec la surface libre suivie par la méthode VOF. Les influences de la surface libre sur le champ d’écoulement sont identifiées et discutées. La comparaison avec les données expérimentales confirme l’importance de la déformation de la surface libre sur le champ d’écoulement. Ensuite, le lit est autorisé à se déformer et le développement temporel de l’affouillement tridimensionnelle autour d’un cylindre sur le lit est simule. Le développement temporel d’affouillement et la profondeur maximale du trou calcule devant et derrière le cylindre conviennent assez bien avec les mesures expérimentales. Les influences de l’affouillement sur le champ d’écoulement sont aussi étudiées et la performance du modèle numérique développé est discutée. / This thesis describes the development of a numerical model for local scour caused by bed-mounted obstacles, combining the hydrodynamic and morphological processes. The basis of the numerical model is the multiphase flow field solver in the open-source CFD toolbox OpenFOAMR which is released by OpenCFD Ltd. The hydrodynamic module of the model solves the Reynolds Averaged Navier-Stokes (RANS) equations with either a k-ε or a k-ω model. There are two interfaces in the simulation domain: the free surface between water and air, which is tracked using the Volume of Fluid (VOF) method, and the interface between the water and the sediment, which is represented by a finite area mesh constructed from the bottom boundary of the finite volume mesh. A morphological module which has been developed as part of the project consists of three components: a sediment transport model which includes suspended load and bed load transport; the Exner equation to compute the bed deformation, and a sand-sliding mechanism to restrict the bed slope angle to be smaller than the angle of repose. The morphological changes are incorporated into the hydrodynamic field through deformation of the computational mesh. Additional boundary conditions and parallel computing corrections are also added into the model. Each individual part of the model has been validated separately with corresponding preliminary test cases including the rough wall functions, the performance of the VOF method, the suspended load transport model and the sand-sliding mechanism. The numerical model is then applied to study two-dimensional scour caused by a submerged jet issuing from an opening under sluice gate. Comparison of the simulation results with the experimental measurements proves the ability of the model for conducting two-dimensional simulations and the limitations of the model are also discussed. Finally, the model is applied to study the three-dimensional flow field and scour formation around an obstacle in flow. Initially, the bed deformation is not activated in the model. The horseshoe vortex formed in front of an obstacle in water and the turbulent flow field around a cylinder on smooth and rough beds are simulated. Two types of simulations for the hydrodynamic module are used: a rigid lid simulation with a slip boundary condition to represent the air-water interface, and a free surface simulation including both the water and air domains with the free surface tracked by the VOF method. The influences of the variation of the water depth on the flow field are identified and discussed. Comparison with the experimental data also confirms the importance of the water surface variation on the flow field. Next, the bed is allowed to deform in the model. The temporal development of three-dimensional scour around a cylinder on live-bed in a steady current is simulated. The development of the scour with time and the computed maximum scour depths in front of and behind the cylinder agree quite well with the experimental measurements. The influences of the scour process on the flow field are also studied and the performance of the numerical model is discussed.

Mit 3D-Netzmodellen werden Objekte der materiellen Welt oder unserer Vorstellung computergestützt abgebildet. In digitalen Produktentwicklungsprozessen werden mit ihnen sowohl die Objektgestalt als auch anwendungsspezifische Informationen von Objekten und von Prozessen definiert. Mit flächenhaften Netzen (z. B. Dreiecksnetze) wird die Oberfläche von Objekten in diskreter Form repräsentiert, mit volumenhaften Netzen (z. B. Tetraedernetze) zusätzlich das Objektinnere. 3D-Netzmodelle werden bei der Erzeugung und der Manipulation, der Analyse und der Validierung, in fertigungsvorbereitenden Prozessen sowie zur Präsentation digitaler 3D-Objekte angewandt.

Nous présentons une nouvelle méthode pour la restauration d'images sismiques. Quand on l'observe, une image sismique est le résultat d'un système de dépôt initial qui a été transformé par un ensemble de déformations géologiques successives (flexions, glissement de la faille, etc) qui se sont produites sur une grande période de temps. L'objectif de la restauration sismique consiste à inverser les déformations pour fournir une image résultante qui représente le système de dépôt géologique tel qu'il était dans un état antérieur. Classiquement, ce procédé permet de tester la cohérence des hypothèses d'interprétations formulées par les géophysiciens sur les images initiales. Dans notre contribution, nous fournissons un outil qui permet de générer rapidement des images restaurées et qui aide donc les géophysiciens à reconnaître et identifier les caractéristiques géologiques qui peuvent être très fortement modifiées et donc difficilement identifiables dans l'image observée d'origine. Cette application permet alors d'assister ces géophysiciens pour la formulation d'hypothèses d'interprétation des images sismiques. L'approche que nous introduisons est basée sur un processus de minimisation qui exprime les déformations géologiques en termes de contraintes géométriques. Nous utilisons une approche itérative de Gauss-Newton qui converge rapidement pour résoudre le système. Dans une deuxième partie de notre travail nous montrons différents résultats obtenus dans des cas concrets afin d'illustrer le processus de restauration d'image sismique sur des données réelles et de montrer comment la version restaurée peut être utilisée dans un cadre d'interprétation géologique. / We present a new method for seismic image restoration. When observed, a seismic image is the result of an initial deposit system that has been transformed by a set of successive geological deformations (folding, fault slip, etc) that occurred over a large period of time. The goal of seismic restoration consists in inverting the deformations to provide a resulting image that depicts the geological deposit system as it was in a previous state. With our contribution, providing a tool that quickly generates restored images helps the geophysicists to recognize geological features that may be too strongly altered in the observed image. The proposed approach is based on a minimization process that expresses geological deformations in terms of geometrical constraints. We use a quickly-converging Gauss-Newton approach to solve the system. We provide results to illustrate the seismic image restoration process on real data and present how the restored version can be used in a geological interpretation framework.