1,571 research outputs found

    Real-time Realistic Rendering Of Nature Scenes With Dynamic Lighting

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    Rendering of natural scenes has interested the scientific community for a long time due to its numerous applications. The targeted goal is to create images that are similar to what a viewer can see in real life with his/her eyes. The main obstacle is complexity: nature scenes from real life contain a huge number of small details that are hard to model, take a lot of time to render and require a huge amount of memory unavailable in current computers. This complexity mainly comes from geometry and lighting. The goal of our research is to overcome this complexity and to achieve real-time rendering of nature scenes while providing visually convincing dynamic global illumination. Our work focuses on grass and trees as they are commonly visible in everyday life. We handle geometry and lighting complexities for grass to render millions of grass blades interactively with dynamic lighting. As for lighting complexity, we address real-time rendering of trees by proposing a lighting model that handles indirect lighting. Our work makes extensive use of the current generation of Graphics Processing Units (GPUs) to meet the real-time requirement and to leave the CPU free to carry out other tasks

    Towards Predictive Rendering in Virtual Reality

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    The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

    Visual Prototyping of Cloth

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    Realistic visualization of cloth has many applications in computer graphics. An ongoing research problem is how to best represent and capture appearance models of cloth, especially when considering computer aided design of cloth. Previous methods can be used to produce highly realistic images, however, possibilities for cloth-editing are either restricted or require the measurement of large material databases to capture all variations of cloth samples. We propose a pipeline for designing the appearance of cloth directly based on those elements that can be changed within the production process. These are optical properties of fibers, geometrical properties of yarns and compositional elements such as weave patterns. We introduce a geometric yarn model, integrating state-of-the-art textile research. We further present an approach to reverse engineer cloth and estimate parameters for a procedural cloth model from single images. This includes the automatic estimation of yarn paths, yarn widths, their variation and a weave pattern. We demonstrate that we are able to match the appearance of original cloth samples in an input photograph for several examples. Parameters of our model are fully editable, enabling intuitive appearance design. Unfortunately, such explicit fiber-based models can only be used to render small cloth samples, due to large storage requirements. Recently, bidirectional texture functions (BTFs) have become popular for efficient photo-realistic rendering of materials. We present a rendering approach combining the strength of a procedural model of micro-geometry with the efficiency of BTFs. We propose a method for the computation of synthetic BTFs using Monte Carlo path tracing of micro-geometry. We observe that BTFs usually consist of many similar apparent bidirectional reflectance distribution functions (ABRDFs). By exploiting structural self-similarity, we can reduce rendering times by one order of magnitude. This is done in a process we call non-local image reconstruction, which has been inspired by non-local means filtering. Our results indicate that synthesizing BTFs is highly practical and may currently only take a few minutes for small BTFs. We finally propose a novel and general approach to physically accurate rendering of large cloth samples. By using a statistical volumetric model, approximating the distribution of yarn fibers, a prohibitively costly, explicit geometric representation is avoided. As a result, accurate rendering of even large pieces of fabrics becomes practical without sacrificing much generality compared to fiber-based techniques

    A Multi-scale Yarn Appearance Model with Fiber Details

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    Rendering realistic cloth has always been a challenge due to its intricate structure. Cloth is made up of fibers, plies, and yarns, and previous curved-based models, while detailed, were computationally expensive and inflexible for large cloth. To address this, we propose a simplified approach. We introduce a geometric aggregation technique that reduces ray-tracing computation by using fewer curves, focusing only on yarn curves. Our model generates ply and fiber shapes implicitly, compensating for the lack of explicit geometry with a novel shadowing component. We also present a shading model that simplifies light interactions among fibers by categorizing them into four components, accurately capturing specular and scattered light in both forward and backward directions. To render large cloth efficiently, we propose a multi-scale solution based on pixel coverage. Our yarn shading model outperforms previous methods, achieving rendering speeds 3-5 times faster with less memory in near-field views. Additionally, our multi-scale solution offers a 20% speed boost for distant cloth observation

    Flat Bidirectional Texture Functions

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    Highly-realistic materials in computer graphics are computationally and memory demanding. Currently, the most versatile techniques are based on Bidirectional Texture Functions (BTFs), an image-based approximation of appearance. Extremely realistic images may be quickly obtained with BTFs at the price of a huge amount of data. Even though a lot of BTF compression schemes have been introduced during the last years, the main remaining challenge arises from the fact that a BTF embeds many different optical phenomena generated by the underlying meso-geometry (parallax effects, masking, shadow casting, inter-reflections, etc.). We introduce a new representation for BTFs that isolates parallax effects. On one hand, we built a flattened BTF according to a global spatial parameterization of the underlying meso-geometry. On the other hand, we generate a set of view-dependent indirection maps on this spatial parameterization to encode all the parallax effects. We further analyze this representation on a various set of synthetic BTF data to show its benefits on view-dependent coherency, and to find the best sampling strategy. We also demonstrate that this representation is well suited for hardware acceleration on current GPUs.En Infographie, les matériaux hautement réalistes sont grand consommateurs de puissance de calculs ainsi que de mémoire. A l'heure actuelle, les techniques les plus versatiles reposent sur les fonctions de textures bidirectionnelles (BTFs) représentant une approximation à partir d'images de l'apparence des matériaux. Des images extrêmement réalistes peuvent être obtenues rapidement à l'aide de BTFs au prix d'une énorme quantité de données. Bien que de nombreux schémas de compression de BTFs aient été introduits au cours de ces dernières années, le principal challenge restant provient du fait qu'une BTF mélange différents phénomènes optiques générés par la meso-géométrie sous-jacente (effets de parallaxe ou de masquage, ombres portées, inter-réflexions, etc.), effets qui ne peuvent être que correctement gérés à l'aide d'approches appropriées. Nous introduisons une nouvelle représentation pour les BTFs qui isole les effets de parallaxes des autres effets. D'une part, nous construisons une BTF aplatie ("flattened") guidée par une paramétrisation spatiale et globale de la méso-géométrie sous-jacente. D'autre part, nous générons un ensemble de table d'indirections dans cette paramétrisation et pour chaque point de vue, afin d(encoder tous les effets de parallaxe. Nous analysons aussi cette représentation sur un ensemble de BTFs synthétiques afin de montrer l'avantage qu'elle apporte pour la cohérence dépendante du point de vue et pour trouver la meilleure stratégie d'échantillonnage. Nous montrons aussi que cette représentation est particulièrement bien adaptée pour bénéficier de l'accélération matérielle des processeurs graphiques actuels

    Advanced methods for relightable scene representations in image space

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    The realistic reproduction of visual appearance of real-world objects requires accurate computer graphics models that describe the optical interaction of a scene with its surroundings. Data-driven approaches that model the scene globally as a reflectance field function in eight parameters deliver high quality and work for most material combinations, but are costly to acquire and store. Image-space relighting, which constrains the application to create photos with a virtual, fix camera in freely chosen illumination, requires only a 4D data structure to provide full fidelity. This thesis contributes to image-space relighting on four accounts: (1) We investigate the acquisition of 4D reflectance fields in the context of sampling and propose a practical setup for pre-filtering of reflectance data during recording, and apply it in an adaptive sampling scheme. (2) We introduce a feature-driven image synthesis algorithm for the interpolation of coarsely sampled reflectance data in software to achieve highly realistic images. (3) We propose an implicit reflectance data representation, which uses a Bayesian approach to relight complex scenes from the example of much simpler reference objects. (4) Finally, we construct novel, passive devices out of optical components that render reflectance field data in real-time, shaping the incident illumination into the desired imageDie realistische Wiedergabe der visuellen Erscheinung einer realen Szene setzt genaue Modelle aus der Computergraphik für die Interaktion der Szene mit ihrer Umgebung voraus. Globale Ansätze, die das Verhalten der Szene insgesamt als Reflektanzfeldfunktion in acht Parametern modellieren, liefern hohe Qualität für viele Materialtypen, sind aber teuer aufzuzeichnen und zu speichern. Verfahren zur Neubeleuchtung im Bildraum schränken die Anwendbarkeit auf fest gewählte Kameras ein, ermöglichen aber die freie Wahl der Beleuchtung, und erfordern dadurch lediglich eine 4D - Datenstruktur für volle Wiedergabetreue. Diese Arbeit enthält vier Beiträge zu diesem Thema: (1) wir untersuchen die Aufzeichnung von 4D Reflektanzfeldern im Kontext der Abtasttheorie und schlagen einen praktischen Aufbau vor, der Reflektanzdaten bereits während der Messung vorfiltert. Wir verwenden ihn in einem adaptiven Abtastschema. (2) Wir führen einen merkmalgesteuerten Bildsynthesealgorithmus für die Interpolation von grob abgetasteten Reflektanzdaten ein. (3) Wir schlagen eine implizite Beschreibung von Reflektanzdaten vor, die mit einem Bayesschen Ansatz komplexe Szenen anhand des Beispiels eines viel einfacheren Referenzobjektes neu beleuchtet. (4) Unter der Verwendung optischer Komponenten schaffen wir passive Aufbauten zur Darstellung von Reflektanzfeldern in Echtzeit, indem wir einfallende Beleuchtung direkt in das gewünschte Bild umwandeln

    Intuitive and Accurate Material Appearance Design and Editing

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    Creating and editing high-quality materials for photorealistic rendering can be a difficult task due to the diversity and complexity of material appearance. Material design is the process by which artists specify the reflectance properties of a surface, such as its diffuse color and specular roughness. Even with the support of commercial software packages, material design can be a time-consuming trial-and-error task due to the counter-intuitive nature of the complex reflectance models. Moreover, many material design tasks require the physical realization of virtually designed materials as the final step, which makes the process even more challenging due to rendering artifacts and the limitations of fabrication. In this dissertation, we propose a series of studies and novel techniques to improve the intuitiveness and accuracy of material design and editing. Our goal is to understand how humans visually perceive materials, simplify user interaction in the design process and, and improve the accuracy of the physical fabrication of designs. Our first work focuses on understanding the perceptual dimensions for measured material data. We build a perceptual space based on a low-dimensional reflectance manifold that is computed from crowd-sourced data using a multi-dimensional scaling model. Our analysis shows the proposed perceptual space is consistent with the physical interpretation of the measured data. We also put forward a new material editing interface that takes advantage of the proposed perceptual space. We visualize each dimension of the manifold to help users understand how it changes the material appearance. Our second work investigates the relationship between translucency and glossiness in material perception. We conduct two human subject studies to test if subsurface scattering impacts gloss perception and examine how the shape of an object influences this perception. Based on our results, we discuss why it is necessary to include transparent and translucent media for future research in gloss perception and material design. Our third work addresses user interaction in the material design system. We present a novel Augmented Reality (AR) material design prototype, which allows users to visualize their designs against a real environment and lighting. We believe introducing AR technology can make the design process more intuitive and improve the authenticity of the results for both novice and experienced users. To test this assumption, we conduct a user study to compare our prototype with the traditional material design system with gray-scale background and synthetic lighting. The results demonstrate that with the help of AR techniques, users perform better in terms of objectively measured accuracy and time and they are subjectively more satisfied with their results. Finally, our last work turns to the challenge presented by the physical realization of designed materials. We propose a learning-based solution to map the virtually designed appearance to a meso-scale geometry that can be easily fabricated. Essentially, this is a fitting problem, but compared with previous solutions, our method can provide the fabrication recipe with higher reconstruction accuracy for a large fitting gamut. We demonstrate the efficacy of our solution by comparing the reconstructions with existing solutions and comparing fabrication results with the original design. We also provide an application of bi-scale material editing using the proposed method

    A graphics processing unit based method for dynamic real-time global illumination

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    Real-time realistic image synthesis for virtual environments has been one of the most actively researched areas in computer graphics for over a decade. Images that display physically correct illumination of an environment can be simulated by evaluating a multi-dimensional integral equation, called the rendering equation, over the surfaces of the environment. Many global illumination algorithms such as pathtracing, photon mapping and distributed ray-tracing can produce realistic images but are generally unable to cope with dynamic lighting and objects at interactive rates. It still remains one of most challenging problems to simulate physically correctly illuminated dynamic environments without a substantial preprocessing step. In this thesis we present a rendering system for dynamic environments by implementing a customized rasterizer for global illumination entirely on the graphics hardware, the Graphical Processing Unit. Our research focuses on a parameterization of discrete visibility field for efficient indirect illumination computation. In order to generate the visibility field, we propose a CUDA-based (Compute Unified Device Architecture) rasterizer which builds Layered Hit Buffers (LHB) by rasterizing polygons into multi-layered structural buffers in parallel. The LHB provides a fast visibility function for any direction at any point. We propose a cone approximation solution to resolve an aliasing problem due to limited directional discretization. We also demonstrate how to remove structure noises by adapting an interleaved sampling scheme and discontinuity buffer. We show that a gathering method amortized with a multi-level Quasi Mont Carlo method can evaluate the rendering equation in real-time. The method can realize real-time walk-through of a complex virtual environment that has a mixture of diffuse and glossy reflection, computing multiple indirect bounces on the fly. We show that our method is capable of simulating fully dynamic environments including changes of view, materials, lighting and objects at interactive rates on commodity level graphics hardware

    Realistic Visualization of Animated Virtual Cloth

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    Photo-realistic rendering of real-world objects is a broad research area with applications in various different areas, such as computer generated films, entertainment, e-commerce and so on. Within photo-realistic rendering, the rendering of cloth is a subarea which involves many important aspects, ranging from material surface reflection properties and macroscopic self-shadowing to animation sequence generation and compression. In this thesis, besides an introduction to the topic plus a broad overview of related work, different methods to handle major aspects of cloth rendering are described. Material surface reflection properties play an important part to reproduce the look & feel of materials, that is, to identify a material only by looking at it. The BTF (bidirectional texture function), as a function of viewing and illumination direction, is an appropriate representation of reflection properties. It captures effects caused by the mesostructure of a surface, like roughness, self-shadowing, occlusion, inter-reflections, subsurface scattering and color bleeding. Unfortunately a BTF data set of a material consists of hundreds to thousands of images, which exceeds current memory size of personal computers by far. This work describes the first usable method to efficiently compress and decompress a BTF data for rendering at interactive to real-time frame rates. It is based on PCA (principal component analysis) of the BTF data set. While preserving the important visual aspects of the BTF, the achieved compression rates allow the storage of several different data sets in main memory of consumer hardware, while maintaining a high rendering quality. Correct handling of complex illumination conditions plays another key role for the realistic appearance of cloth. Therefore, an upgrade of the BTF compression and rendering algorithm is described, which allows the support of distant direct HDR (high-dynamic-range) illumination stored in environment maps. To further enhance the appearance, macroscopic self-shadowing has to be taken into account. For the visualization of folds and the life-like 3D impression, these kind of shadows are absolutely necessary. This work describes two methods to compute these shadows. The first is seamlessly integrated into the illumination part of the rendering algorithm and optimized for static meshes. Furthermore, another method is proposed, which allows the handling of dynamic objects. It uses hardware-accelerated occlusion queries for the visibility determination. In contrast to other algorithms, the presented algorithm, despite its simplicity, is fast and produces less artifacts than other methods. As a plus, it incorporates changeable distant direct high-dynamic-range illumination. The human perception system is the main target of any computer graphics application and can also be treated as part of the rendering pipeline. Therefore, optimization of the rendering itself can be achieved by analyzing human perception of certain visual aspects in the image. As a part of this thesis, an experiment is introduced that evaluates human shadow perception to speedup shadow rendering and provides optimization approaches. Another subarea of cloth visualization in computer graphics is the animation of the cloth and avatars for presentations. This work also describes two new methods for automatic generation and compression of animation sequences. The first method to generate completely new, customizable animation sequences, is based on the concept of finding similarities in animation frames of a given basis sequence. Identifying these similarities allows jumps within the basis sequence to generate endless new sequences. Transmission of any animated 3D data over bandwidth-limited channels, like extended networks or to less powerful clients requires efficient compression schemes. The second method included in this thesis in the animation field is a geometry data compression scheme. Similar to the BTF compression, it uses PCA in combination with clustering algorithms to segment similar moving parts of the animated objects to achieve high compression rates in combination with a very exact reconstruction quality.Realistische Visualisierung von animierter virtueller Kleidung Das photorealistisches Rendering realer Gegenstände ist ein weites Forschungsfeld und hat Anwendungen in vielen Bereichen. Dazu zählen Computer generierte Filme (CGI), die Unterhaltungsindustrie und E-Commerce. Innerhalb dieses Forschungsbereiches ist das Rendern von photorealistischer Kleidung ein wichtiger Bestandteil. Hier reichen die wichtigen Aspekte, die es zu berücksichtigen gilt, von optischen Materialeigenschaften über makroskopische Selbstabschattung bis zur Animationsgenerierung und -kompression. In dieser Arbeit wird, neben der Einführung in das Thema, ein weiter Überblick über ähnlich gelagerte Arbeiten gegeben. Der Schwerpunkt der Arbeit liegt auf den wichtigen Aspekten der virtuellen Kleidungsvisualisierung, die oben beschrieben wurden. Die optischen Reflektionseigenschaften von Materialoberflächen spielen eine wichtige Rolle, um das so genannte look & feel von Materialien zu charakterisieren. Hierbei kann ein Material vom Nutzer identifiziert werden, ohne dass er es direkt anfassen muss. Die BTF (bidirektionale Texturfunktion)ist eine Funktion die abhängig von der Blick- und Beleuchtungsrichtung ist. Daher ist sie eine angemessene Repräsentation von Reflektionseigenschaften. Sie enthält Effekte wie Rauheit, Selbstabschattungen, Verdeckungen, Interreflektionen, Streuung und Farbbluten, die durch die Mesostruktur der Oberfläche hervorgerufen werden. Leider besteht ein BTF Datensatz eines Materials aus hunderten oder tausenden von Bildern und sprengt damit herkömmliche Hauptspeicher in Computern bei weitem. Diese Arbeit beschreibt die erste praktikable Methode, um BTF Daten effizient zu komprimieren, zu speichern und für Echtzeitanwendungen zum Visualisieren wieder zu dekomprimieren. Die Methode basiert auf der Principal Component Analysis (PCA), die Daten nach Signifikanz ordnet. Während die PCA die entscheidenen visuellen Aspekte der BTF erhält, können mit ihrer Hilfe Kompressionsraten erzielt werden, die es erlauben mehrere BTF Materialien im Hauptspeicher eines Consumer PC zu verwalten. Dies erlaubt ein High-Quality Rendering. Korrektes Verwenden von komplexen Beleuchtungssituationen spielt eine weitere, wichtige Rolle, um Kleidung realistisch erscheinen zu lassen. Daher wird zudem eine Erweiterung des BTF Kompressions- und Renderingalgorithmuses erläutert, die den Einsatz von High-Dynamic Range (HDR) Beleuchtung erlaubt, die in environment maps gespeichert wird. Um die realistische Erscheinung der Kleidung weiter zu unterstützen, muss die makroskopische Selbstabschattung integriert werden. Für die Visualisierung von Falten und den lebensechten 3D Eindruck ist diese Art von Schatten absolut notwendig. Diese Arbeit beschreibt daher auch zwei Methoden, diese Schatten schnell und effizient zu berechnen. Die erste ist nahtlos in den Beleuchtungspart des obigen BTF Renderingalgorithmuses integriert und für statische Geometrien optimiert. Die zweite Methode behandelt dynamische Objekte. Dazu werden hardwarebeschleunigte Occlusion Queries verwendet, um die Sichtbarkeitsberechnung durchzuführen. Diese Methode ist einerseits simpel und leicht zu implementieren, anderseits ist sie schnell und produziert weniger Artefakte, als vergleichbare Methoden. Zusätzlich ist die Verwendung von veränderbarer, entfernter HDR Beleuchtung integriert. Das menschliche Wahrnehmungssystem ist das eigentliche Ziel jeglicher Anwendung in der Computergrafik und kann daher selbst als Teil einer erweiterten Rendering Pipeline gesehen werden. Daher kann das Rendering selbst optimiert werden, wenn man die menschliche Wahrnehmung verschiedener visueller Aspekte der berechneten Bilder analysiert. Teil der vorliegenden Arbeit ist die Beschreibung eines Experimentes, das menschliche Schattenwahrnehmung untersucht, um das Rendern der Schatten zu beschleunigen. Ein weiteres Teilgebiet der Kleidungsvisualisierung in der Computergrafik ist die Animation der Kleidung und von Avataren für Präsentationen. Diese Arbeit beschreibt zwei neue Methoden auf diesem Teilgebiet. Einmal ein Algorithmus, der für die automatische Generierung neuer Animationssequenzen verwendet werden kann und zum anderen einen Kompressionsalgorithmus für eben diese Sequenzen. Die automatische Generierung von völlig neuen, anpassbaren Animationen basiert auf dem Konzept der Ähnlichkeitssuche. Hierbei werden die einzelnen Schritte von gegebenen Basisanimationen auf Ähnlichkeiten hin untersucht, die zum Beispiel die Geschwindigkeiten einzelner Objektteile sein können. Die Identifizierung dieser Ähnlichkeiten erlaubt dann Sprünge innerhalb der Basissequenz, die dazu benutzt werden können, endlose, neue Sequenzen zu erzeugen. Die Übertragung von animierten 3D Daten über bandbreitenlimitierte Kanäle wie ausgedehnte Netzwerke, Mobilfunk oder zu sogenannten thin clients erfordert eine effiziente Komprimierung. Die zweite, in dieser Arbeit vorgestellte Methode, ist ein Kompressionsschema für Geometriedaten. Ähnlich wie bei der Kompression von BTF Daten wird die PCA in Verbindung mit Clustering benutzt, um die animierte Geometrie zu analysieren und in sich ähnlich bewegende Teile zu segmentieren. Diese erkannten Segmente lassen sich dann hoch komprimieren. Der Algorithmus arbeitet automatisch und erlaubt zudem eine sehr exakte Rekonstruktionsqualität nach der Dekomprimierung

    Artistic Path Space Editing of Physically Based Light Transport

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    Die Erzeugung realistischer Bilder ist ein wichtiges Ziel der Computergrafik, mit Anwendungen u.a. in der Spielfilmindustrie, Architektur und Medizin. Die physikalisch basierte Bildsynthese, welche in letzter Zeit anwendungsübergreifend weiten Anklang findet, bedient sich der numerischen Simulation des Lichttransports entlang durch die geometrische Optik vorgegebener Ausbreitungspfade; ein Modell, welches für übliche Szenen ausreicht, Photorealismus zu erzielen. Insgesamt gesehen ist heute das computergestützte Verfassen von Bildern und Animationen mit wohlgestalteter und theoretisch fundierter Schattierung stark vereinfacht. Allerdings ist bei der praktischen Umsetzung auch die Rücksichtnahme auf Details wie die Struktur des Ausgabegeräts wichtig und z.B. das Teilproblem der effizienten physikalisch basierten Bildsynthese in partizipierenden Medien ist noch weit davon entfernt, als gelöst zu gelten. Weiterhin ist die Bildsynthese als Teil eines weiteren Kontextes zu sehen: der effektiven Kommunikation von Ideen und Informationen. Seien es nun Form und Funktion eines Gebäudes, die medizinische Visualisierung einer Computertomografie oder aber die Stimmung einer Filmsequenz -- Botschaften in Form digitaler Bilder sind heutzutage omnipräsent. Leider hat die Verbreitung der -- auf Simulation ausgelegten -- Methodik der physikalisch basierten Bildsynthese generell zu einem Verlust intuitiver, feingestalteter und lokaler künstlerischer Kontrolle des finalen Bildinhalts geführt, welche in vorherigen, weniger strikten Paradigmen vorhanden war. Die Beiträge dieser Dissertation decken unterschiedliche Aspekte der Bildsynthese ab. Dies sind zunächst einmal die grundlegende Subpixel-Bildsynthese sowie effiziente Bildsyntheseverfahren für partizipierende Medien. Im Mittelpunkt der Arbeit stehen jedoch Ansätze zum effektiven visuellen Verständnis der Lichtausbreitung, die eine lokale künstlerische Einflussnahme ermöglichen und gleichzeitig auf globaler Ebene konsistente und glaubwürdige Ergebnisse erzielen. Hierbei ist die Kernidee, Visualisierung und Bearbeitung des Lichts direkt im alle möglichen Lichtpfade einschließenden "Pfadraum" durchzuführen. Dies steht im Gegensatz zu Verfahren nach Stand der Forschung, die entweder im Bildraum arbeiten oder auf bestimmte, isolierte Beleuchtungseffekte wie perfekte Spiegelungen, Schatten oder Kaustiken zugeschnitten sind. Die Erprobung der vorgestellten Verfahren hat gezeigt, dass mit ihnen real existierende Probleme der Bilderzeugung für Filmproduktionen gelöst werden können
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