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Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects.

Representações computacionais de formas podem ser criadas em ferramentas CAD ou geradas a partir de um objeto físico já existente. Esta última abordagem oferece como vantagens rapidez e fidelidade ao objeto original, que são os aspectos fundamentais em muitas aplicações, como Simulações Numéricas de Equações Diferenciais Parciais e Imagens Médicas. A reconstrução (ou geração de malhas superficiais) a partir de pontos amostrados de uma superfície de um objeto é um problema clássico de representação de formas. Nesta dissertação apresentamos um vasto levantamento bibliográfico deste tipo de reconstrução, classificando e descrevendo os principais trabalhos presentes na literatura. A partir do levantamento bibliográfico, selecionamos um conjunto de algoritmos sobre os quais foram realizadas comparações teóricas e empíricas cujos resultados são apresentados. Para finalizar, apresentamos aplicações de nossas implementações em Simulação Numérica de Equações Diferenciais Parciais e processamento de Imagens / Computational representations of shapes can be developed using CAD applications or created from data acquired from a real physical object. This latter is advantageous with respect to time and fidelity to the original object which are essential to several applications, such as Numerical Simulation of Partial Differential Equations and Medical Imaging. A classical shape representation problem is that of reconstruction (or superficial mesh generation) from points sampled over the surface of an object. In this Master\'s thesis we describe a broad survey of these reconstruction methods. We focus in the classification and characterization of the main algorithms proposed in the literature. From this survey, we selected some algorithms and conducted some theoretical and practical comparisons. We conclude this work describing applications of the algorithms implemented in Numerical Simulations of Differential Partial Equations and Image Processing

We consider the problem of reconstructing a surface from noisy samples by approximating the point set with non-uniform rational B-spline surfaces. We focus on the fact that the knot sequences should also be part of the unknown variables that include the control points and the weights in order to find their optimal positions. We show how to set up the free knot problem such that constrained nonlinear optimization can be applied efficiently. We describe in detail a parallel implementation of our approach that give almost linear speedup. Finally, we provide numerical results obtained on the Chemnitzer Linux Cluster supercomputer.

In the workflow of computational fluid dynamics, geometry preparation is commonly the most time-consuming step. For a fast CFD simulation, automatic surface reconstruction to obtain 3D city models for a chosen area is essential. To address this need, a literature study was conducted to map available data suitable for 3D city models. The properties investigated included geographical coverage, resolution, accuracy and licensing. A surface reconstruction using different topographical data was conducted using the 3D finite element mesh generator Gmsh and various GIS analysis tools. The findings of the literature study found no global data enabling a fully automatic solution with sufficient results. However, the open geographic database OpenStreetMap has potential for future work. Today, the method developed in this project is restricted to country-by-country applications and uses a terrain model, LiDAR data and building footprints as input data. The generated 3D city model has a level of detail 1.2, consisting of valid geometries without self-intersection, overlapping or gaps. The method is a semi-automatic workflow with a time consumption of less than one hour, from the extraction of data to a simulation-ready 3D city model. The model shows satisfactory agreement with the reference material but needs improvements regarding the detail of height setting, for more accurate airflow simulations. The method contributes to the field of automatic 3D city model reconstruction. Future work includes improvement regarding level of detail and automation of data attainment.

No description available.

De nombreux scanners laser permettent d'obtenir la surface 3D a partir d'un objet. Néanmoins, la surface reconstruite est souvent lisse, ce qui est du au débruitage interne du scanner et aux décalages entre les scans. Cette these utilise des scans haute precision et choisit de ne pas perdre ni alterer les echantillons initiaux au cours du traitement afin de les visualiser. C'est en effet la seule façon de decouvrir les imperfections (trous, decalages de scans). De plus, comme les donnees haute precision capturent meme le plus leger detail, tout debruitage ou sous-echantillonnage peut amener a perdre ces details.La these s'attache a prouver que l'on peut trianguler le nuage de point initial en ne perdant presque aucun echantillon. Le probleme de la visualisation exacte sur des donnees de plus de 35 millions de points et de 300 scans differents est ainsi resolu. Deux problemes majeurs sont traites: le premier est l'orientation du nuage de point brut complet et la creation d'un maillage. Le second est la correction des petits decalages entre les scans qui peuvent creer un tres fort aliasing et compromettre la visualisation de la surface. Le second developpement de la these est une decomposition des nuages de points en hautes/basses frequences. Ainsi, des methodes classiques pour l'analyse d'image, l'arbre des ensembles de niveau et la representation MSER, sont etendues aux maillages, ce qui donne une methode intrinseque de segmentation de maillages. Une analyse mathematiques d'operateurs differentiels discrets, proposes dans la litterature et operant sur des nuages de points est realisee. En considerant les developpements asymptotiques de ces operateurs sur une surface reguliere, ces operateurs peuvent etre classifies. Cette analyse amene au developpement d'un operateur discret consistant avec Ie mouvement par courbure moyenne (l'equation de la chaleur intrinseque) definissant ainsi un espace-echelle numerique simple et remarquablement robuste. Cet espace-echelle permet de resoudre de maniere unifiee tous les problemes mentionnes auparavant (orientation et triangulation du nuage de points, fusion de scans, segmentation de maillages) qui sont ordinairement traites avec des techniques distinctes. / Many laser devices acquire directly 3D objects and reconstruct their surface. Nevertheless, the final reconstructed surface is usually smoothed out as a result of the scanner internal de-noising process and the offsets between different scans. This thesis, working on results from high precision scans, adopts the somewhat extreme conservative position, not to loose or alter any raw sample throughout the whole processing pipeline, and to attempt to visualize them. Indeed, it is the only way to discover all surface imperfections (holes, offsets). Furthermore, since high precision data can capture the slightest surface variation, any smoothing and any sub-sampling can incur in the loss of textural detail.The thesis attempts to prove that one can triangulate the raw point cloud with almost no sample loss. It solves the exact visualization problem on large data sets of up to 35 million points made of 300 different scan sweeps and more. Two major problems are addressed. The first one is the orientation of the complete raw point set, an the building of a high precision mesh. The second one is the correction of the tiny scan misalignments which can cause strong high frequency aliasing and hamper completely a direct visualization.The second development of the thesis is a general low-high frequency decomposition algorithm for any point cloud. Thus classic image analysis tools, the level set tree and the MSER representations, are extended to meshes, yielding an intrinsic mesh segmentation method.The underlying mathematical development focuses on an analysis of a half dozen discrete differential operators acting on raw point clouds which have been proposed in the literature. By considering the asymptotic behavior of these operators on a smooth surface, a classification by their underlying curvature operators is obtained.This analysis leads to the development of a discrete operator consistent with the mean curvature motion (the intrinsic heat equation) defining a remarkably simple and robust numerical scale space. By this scale space all of the above mentioned problems (point set orientation, raw point set triangulation, scan merging, segmentation), usually addressed by separated techniques, are solved in a unified framework.

De nombreuses applications en vision par ordinateur comme le filtrage, la segmentation d'images, et la stéréovision peuvent être formulées comme des problèmes d'optimisation. Récemment les méthodes discrètes, convexes, globalement optimales ont reçu beaucoup d'attention. La méthode des "graph cuts'", très utilisée en vision par ordinateur est basée sur la résolution d'un problème de flot maximum discret, mais les solutions souffrent d'un effet de blocs,notamment en segmentation d'images. Une nouvelle formulation basée sur le problème continu est introduite dans le premier chapitre et permet d'éviter cet effet. La méthode de point interieur employée permet d'optimiser le problème plus rapidement que les méthodes existantes, et la convergence est garantie. Dans le second chapitre, la formulation proposée est efficacement étendue à la restauration d'image. Grâce à une approche du à la contrainte et à un algorithme proximal parallèle, la méthode permet de restaurer (débruiter, déflouter, fusionner) des images rapidement et préserve un meilleur contraste qu'avec la méthode de variation totale classique. Le chapitre suivant met en évidence l'existence de liens entre les méthodes de segmentation "graph-cuts'", le "randomwalker'', et les plus courts chemins avec un algorithme de segmentation par ligne de partage des eaux (LPE). Ces liens ont inspiré un nouvel algorithme de segmentation multi-labels rapide produisant une ligne de partage des eaux unique, moins sensible aux fuites que la LPE classique. Nous avons nommé cet algorithme "LPE puissance''. L'expression de la LPE sous forme d'un problème d'optimisation a ouvert la voie à de nombreuses applications possibles au delà de la segmentation d'images, par exemple dans le dernier chapitre en filtrage pour l'optimisation d'un problème non convexe, en stéréovision, et en reconstruction rapide de surfaces lisses délimitant des objets à partir de nuages de points bruités / Many computer vision applications such as image filtering, segmentation and stereovision can be formulated as optimization problems. Recently discrete, convex, globally optimal methods have received a lot of attention. Many graph-based methods suffer from metrication artefacts, segmented contours are blocky in areas where contour information is lacking. In the first part of this work, we develop a discrete yet isotropic energy minimization formulation for the continuous maximum flow problem that prevents metrication errors. This new convex formulation leads us to a provably globally optimal solution. The employed interior point method can optimize the problem faster than the existing continuous methods. The energy formulation is then adapted and extended to multi-label problems, and shows improvements over existing methods. Fast parallel proximal optimization tools have been tested and adapted for the optimization of this problem. In the second part of this work, we introduce a framework that generalizes several state-of-the-art graph-based segmentation algorithms, namely graph cuts, random walker, shortest paths, and watershed. This generalization allowed us to exhibit a new case, for which we developed a globally optimal optimization method, named "Power watershed''. Our proposed power watershed algorithm computes a unique global solution to multi labeling problems, and is very fast. We further generalize and extend the framework to applications beyond image segmentation, for example image filtering optimizing an L0 norm energy, stereovision and fast and smooth surface reconstruction from a noisy cloud of 3D points

La thèse est dédiée au problème de la stéréophotométrie non-Lambertienne sans connaissance a priori sur les conditions d’illumination et son application aux images de boîte de Pétri. Pour obtenir une bonne reconstruction de surfaces non-Lambertiennes, il est proposé de traiter une séquence d’entrée en deux étapes: premièrement il faut supprimer les effets spéculaires et obtenir ainsi des images de surface ’pseudo-Lambertienne’. Ensuite dans une deuxième étape à partir de ces images une reconstruction stéréophotométrique Lambertienne sans aucune information préalable sur les directions d’illumination est effectuée. Dans ce travail nous proposons deux méthodes originales respectivement pour la suppression de spécularités et la reconstruction de surface sans information a priori. Les méthodes proposées sont appliquées pour la caractérisation des colonies microbiennes.La spécularités est un effet optique lié à la nature physique complexe des objets. Il est utile pour la perception humaine des objets 3D mais il gêne le processus de traitement automatique d’images. Pour pouvoir appliquer le modèle Lambertien à la stéréophotométrie, les spécularités doivent être supprimées des images d’entrée. Nous proposons donc une méthode originale pour la correction des zones spéculaires adaptée pour une reconstruction ultérieure. L’algorithme proposé est capable de détecter les spécularités comme des valeurs anormalement élevées d’intensité dans une image de la séquence d’entrée, et de les corriger en utilisant les informations des autres images de la séquence et une fonction de correction continue. Cette méthode permet de faire la suppression des spécularités en préservant toutes les autres particularités de distribution de lumière qui sont importantes pour la reconstruction de surface.Après nous proposons une technique de reconstruction stéréophotométrique de surface Lambertienne sans connaissance a priori sur l’illumination. Le modèle mis en œuvre consiste en quatre composantes, deux composantes (albédo et normales) permettent de d´écrire des propriétés de surface et deux autres (intensités des sources de lumière et leurs directions) décrivent illumination. L’algorithme proposé de reconstruction utilise le principe de l’optimisation alternée. Chaque composante du modèle est trouvée itérativement en fixant toutes les variables sauf une et en appliquant des contraintes de structures, valeurs et qualité pour la fonction d’optimisation. Un schéma original de résolution permet de séparer les différents types d’information inclus dans les images d’entrée. Grâce à cette factorisation de matrices, la reconstruction de surface est faite sans connaissance préalable sur les directions de lumière et les propriétés de l’objet reconstruit. L’applicabilité de l’algorithme est prouvée pour des donnés artificielles et des images de bases publiques pour lesquelles la vérité terrain sur les surfaces des objets est disponible.La dernière partie de la thèse est dédiée à l’application de la chaine complète proposée pour le traitement d’images de boîte de Pétri. Ces images sont obtenues en utilisant les sources de lumières complexes qui sont supposées être inconnues pour le processus de reconstruction. L’évaluation de surfaces de colonies microbiennes s’est révélée être une étape importante pour l'analyse visuelle et automatique des colonies. La chaine proposée est efficace pour ce type de données et permet de compléter les informations d'images par de la surface 3D. / The PhD thesis work is dedicated to the problem of uncalibrated non-Lambertian photometric stereo surface reconstruction. The proposed approach consists in two phases: first we correct images of the input sequence from specularities in order to obtain images of pseudo-Lambertian surfaces, and then realize Lambertian photometric stereo reconstruction. In this work we proposed two original methods, respectively, for specularity correction and surface reconstruction with no prior information neither on light sources nor on surface properties. We apply the novel processing to Petri dish images for microbial colonies surface reconstruction.Specularity is an optical effect of a complex physical nature. This effect is useful for human 3D objects perception but it affects automated image processing. In order to be able to apply the Lambertian photometric stereo model, specularities should be removed from the input images. We propose an original method for specular zones correction adapted to estimation of pseudo-Lambertian surface images and further reconstruction. This algorithm is able to detect specularities as abnormally elevated pixel intensity values in an image of the input sequence and to correct the found zones using information from all other images of the sequence and a specific continuous correcting function. This method allows removing specularities while still preserving all other particularities of shading important for the further surface reconstruction.We then propose an original stereo photometric method for Lambertian surface reconstruction with no prior on illuminations. The implemented photometric stereo model consists of four components, two of them (albedo and normals) describe surface properties and the others (light sources intensities and directions) describe illumination. The proposed algorithm of the photometric stereo reconstruction uses the alternating optimization principle. Each model component is found iteratively fixing all variables but one and applying value and quality constraints for the optimization function. The original scheme of resolution allows separating of different information types included in input images. Thanks to such matrix factorization, the surface reconstruction is made with no prior information on lighting directions and the reconstructed objects properties. The applicability of the algorithm is proved using artificially created and open data-sets for which the ground truth information is available.The last part of the thesis is dedicated to the application of the proposed uncalibrated non- Lambertian photometric stereo approach to the Petri dish images. Images are obtained using illuminating sources which are supposed to be unknown for the reconstruction process. Moreover, the reconstructed microbial colonies are very diverse, generally have small size, can be Lambertian or not, and their surface properties are not defined in advance. The results of reconstruction for such complex real-world data add value and importance to the developed approach.

Métodos de representação de superfícies a partir de pontos não-organizados se mantêm como uma das principais vertentes científicas que aquecem o estado-da-arte em Computação Gráfica e, significativamente, estão sendo reconhecidos como uma ferramenta interessante para definição de interfaces móveis no contexto de simulações numéricas de escoamento de fluidos. Não é difícil encontrar motivos para tais fatos: pelo lado da computação gráfica, por exemplo, a manipulação de conjuntos de pontos massivos com geometrias complexas e sujeitos a informações ruidosas ainda abre margem para novas metodologias. Já no âmbito da mecânica dos fluidos, onde os dados não são originados de \\emph tridimensionais, mas sim de interfaces entre fluidos imiscíveis, mecanismos de representação de superfícies a partir de pontos não-organizados podem apresentar características computacionais e propriedades geométricas que os tornem atrativos para aplicações em simulação de fenômenos físicos. O objetivo principal dessa tese de doutorado foi, portanto, o desenvolvimento de técnicas de representação de superfícies a partir de pontos não-organizados, que sejam capazes de suprir restrições de importantes trabalhos prévios. Nesse sentido, primeiramente focalizamos a elaboração de técnicas baseadas em formulações de mínimos-quadrados-móveis e de uma técnica robusta de partição da unidade implícita adaptativa em duas vias. Além de mecanismos de representação de superfícies a partir de pontos não-organizados, também propusemos um método promissor para representação de interfaces em simulação numérica de escoamento de fluidos multifásicos. Para isso, embasamo-nos numa abordagem Lagrangeana (livre-de-malhas), fundamentada no método dos mínimos-quadrados-móveis algébricos e apresentamos diversos resultados numéricos, estudos de convergências e comparações que evidenciam o potencial dessa metodologia para simulações numéricas de fenômenos físicos. Apesar de a contribuição principal deste trabalho ser o desenvolvimento de métodos para representação de superfícies a partir de pontos não-organizados, a experiência que adquirimos no desenvolvimento dessas técnicas nos conduziu à elaboração de mecanismos para representação de dados volumétricos não-organizados. Por conta disso, apresentamos dois mecanismos de representação a partir de dados volumétricos não-organizados com o intuito de serem aplicáveis a informações oriundas de malhas contendo células arbitrárias, isto é, propusemos a definição de um método de rendering unificado / Surface reconstruction from unorganized points has been one of the most promising scientific research areas in Computer Graphics. In addition, it has been used successfully for the definition of fluid interface in numerical simulation of fluid flow. There are several reasons to that fact: for instance, considering Computer Graphics, we have the handling of out-of-core data from complicated geometries and subject to noisy information that brings out opportunities for the development of new techniques. Further, considering Numerical Fluid Mechanics, where the input data does not come from tridimensional scanners, but from fluid interfaces, schemes that define the surface from unorganized points can offer geometrical and computational properties useful to numerical fluid flow simulation. The main goal of this project was the development of novel techniques for reconstructing surfaces from unorganized points with the capability to overcome the main drawbacks of important previous work. To that end, first we focused on the development of techniques based on moving-least-squares and on a robust twofold partition of unity Implicits. Added to the development of surface reconstruction from unorganized points, we proposed a novel scheme for defining fluid flow interfaces. We approach a meshless Lagrangian based on algebraic moving-least-squares surfaces. In addition, we presented several numerical results, convergence tests and comparisons, which state the power of the method to numerical simulation of physical phenomena. Although our main contributions were focused on surface reconstruction from points, we proposed methods to function reconstruction from unorganized volumetric data. Thus, we present two schemes to represent volumetric data from arbitrary meshes, i.e., a unified rendering scheme