Real-time Realistic Rendering Of Nature Scenes With Dynamic Lighting

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

Advanced methods for relightable scene representations in image space

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

An Analysis of the factors influencing paper selection for books of reproduced fine art

Toner-based digital presses are now capable of matching offset lithographic presses in image and print quality. Current trends show increased interest in printing fine art books on digital presses. It is necessary to understand the extent to which digital printing systems are capable of accurately rendering fine-art reproductions. This research analyzed paper properties that maximize image quality and preference for digitally printed fine art reproductions. Four images, representing four art media, were printed on twelve papers using two digital presses. The twelve papers represented different combinations of color, print-show-through, roughness and gloss. A psychophysical experiment was conducted in which observers ranked the twelve papers for each image on the basis of image quality, color rendering quality, and surface appearance quality. The results were analyzed and a model was developed to predict the probability that a paper was ranked in the top three. Paper color (coolness), basis weight, roughness, and gloss were model parameters. Unlike gloss, roughness, and print-show-through, there was no previous metric for quantifying coolness. Therefore, an additional experiment was conducted to develop a model to predict the perception of coolness using colorimetry. An alternative experiment model was also developed that included parameters such as caliper, print gloss, line raggedness, and dot circularity. The resulting models allowed for the optimization of paper parameters that maximize the probability a paper will produce preferred and high quality images. It was concluded that the probability a book was judged as having high image quality was optimized for papers with high coolness, low roughness and low gloss. Neither print show-through, line raggedness, nor mottle were significant factors. An additional lexical analysis was performed for observer descriptions of their ranking behavior. This analysis provided complementary data to the psychophysical results. Observers\u27 descriptions of their ranking strategies did not match the rank data, suggesting a possible disconnect between observers\u27 conscious and subconscious ranking behaviors

Scalable visualization of spatial data in 3D terrain

Designing visualizations of spatial data in 3D terrain is challenging because various heterogeneous data aspects need to be considered, including the terrain itself, multiple data attributes, and data uncertainty. It is hardly possible to visualize these data at full detail in a single image. Therefore, this thesis devises a scalable visualization approach that focuses on relevant information to be emphasized, while less-relevant information can be attenuated. In this context, a noval concept of visualizing spatial data in 3D terrain and different soft- and hardware solutions are proposed.Die Erstellung von Visualisierungen für räumliche Daten im 3D-Gelände ist schwierig, da viele heterogene Datenaspekte wie das Gelände selbst, die verschiedenen Datenattribute sowie Unsicherheiten bei der Darstellung zu berücksichtigen sind. Im Allgemeinen ist es nicht möglich, diese Datenaspekte gleichzeitig in einer Visualisierung darzustellen. Daher werden in der Arbeit skalierbare Visualisierungsstrategien entwickelt, welche die wichtigen Informationen hervorheben und trotzdem gleichzeitig Kontextinformationen liefern. Hierfür werden neue Systematisierungen und Konzepte vorgestellt

Sculpting Unrealities: Using Machine Learning to Control Audiovisual Compositions in Virtual Reality

This thesis explores the use of interactive machine learning (IML) techniques to control audiovisual compositions within the emerging medium of virtual reality (VR). Accompanying the text is a portfolio of original compositions and open-source software. These research outputs represent the practical elements of the project that help to shed light on the core research question: how can IML techniques be used to control audiovisual compositions in VR? In order to find some answers to this question, it was broken down into its constituent elements. To situate the research, an exploration of the contemporary field of audiovisual art locates the practice between the areas of visual music and generative AV. This exploration of the field results in a new method of categorising the constituent practices. The practice of audiovisual composition is then explored, focusing on the concept of equality. It is found that, throughout the literature, audiovisual artists aim to treat audio and visual material equally. This is interpreted as a desire for balance between the audio and visual material. This concept is then examined in the context of VR. A feeling of presence is found to be central to this new medium and is identified as an important consideration for the audiovisual composer in addition to the senses of sight and sound. Several new terms are formulated which provide the means by which the compositions within the portfolio are analysed. A control system, based on IML techniques, is developed called the Neural AV Mapper. This is used to develop a compositional methodology through the creation of several studies. The outcomes from these studies are incorporated into two live performance pieces, Ventriloquy I and Ventriloquy II. These pieces showcase the use of IML techniques to control audiovisual compositions in a live performance context. The lessons learned from these pieces are incorporated into the development of the ImmersAV toolkit. This open-source software toolkit was built specifically to allow for the exploration of the IML control paradigm within VR. The toolkit provides the means by which the immersive audiovisual compositions, Obj_#3 and Ag Fás Ar Ais Arís are created. Obj_#3 takes the form of an immersive audiovisual sculpture that can be manipulated in real-time by the user. The title of the thesis references the physical act of sculpting audiovisual material. It also refers to the ability of VR to create alternate realities that are not bound to the physics of real-life. This exploration of unrealities emerges as an important aspect of the medium. The final piece in the portfolio, Ag Fás Ar Ais Arís takes the knowledge gained from the earlier work and pushes the boundaries to maximise the potential of the medium and the material

Efficient image-based rendering

Recent advancements in real-time ray tracing and deep learning have significantly enhanced the realism of computer-generated images. However, conventional 3D computer graphics (CG) can still be time-consuming and resource-intensive, particularly when creating photo-realistic simulations of complex or animated scenes. Image-based rendering (IBR) has emerged as an alternative approach that utilizes pre-captured images from the real world to generate realistic images in real-time, eliminating the need for extensive modeling. Although IBR has its advantages, it faces challenges in providing the same level of control over scene attributes as traditional CG pipelines and accurately reproducing complex scenes and objects with different materials, such as transparent objects. This thesis endeavors to address these issues by harnessing the power of deep learning and incorporating the fundamental principles of graphics and physical-based rendering. It offers an efficient solution that enables interactive manipulation of real-world dynamic scenes captured from sparse views, lighting positions, and times, as well as a physically-based approach that facilitates accurate reproduction of the view dependency effect resulting from the interaction between transparent objects and their surrounding environment. Additionally, this thesis develops a visibility metric that can identify artifacts in the reconstructed IBR images without observing the reference image, thereby contributing to the design of an effective IBR acquisition pipeline. Lastly, a perception-driven rendering technique is developed to provide high-fidelity visual content in virtual reality displays while retaining computational efficiency.Jüngste Fortschritte im Bereich Echtzeit-Raytracing und Deep Learning haben den Realismus computergenerierter Bilder erheblich verbessert. Konventionelle 3DComputergrafik (CG) kann jedoch nach wie vor zeit- und ressourcenintensiv sein, insbesondere bei der Erstellung fotorealistischer Simulationen von komplexen oder animierten Szenen. Das bildbasierte Rendering (IBR) hat sich als alternativer Ansatz herauskristallisiert, bei dem vorab aufgenommene Bilder aus der realen Welt verwendet werden, um realistische Bilder in Echtzeit zu erzeugen, so dass keine umfangreiche Modellierung erforderlich ist. Obwohl IBR seine Vorteile hat, ist es eine Herausforderung, das gleiche Maß an Kontrolle über Szenenattribute zu bieten wie traditionelle CG-Pipelines und komplexe Szenen und Objekte mit unterschiedlichen Materialien, wie z.B. transparente Objekte, akkurat wiederzugeben. In dieser Arbeit wird versucht, diese Probleme zu lösen, indem die Möglichkeiten des Deep Learning genutzt und die grundlegenden Prinzipien der Grafik und des physikalisch basierten Renderings einbezogen werden. Sie bietet eine effiziente Lösung, die eine interaktive Manipulation von dynamischen Szenen aus der realen Welt ermöglicht, die aus spärlichen Ansichten, Beleuchtungspositionen und Zeiten erfasst wurden, sowie einen physikalisch basierten Ansatz, der eine genaue Reproduktion des Effekts der Sichtabhängigkeit ermöglicht, der sich aus der Interaktion zwischen transparenten Objekten und ihrer Umgebung ergibt. Darüber hinaus wird in dieser Arbeit eine Sichtbarkeitsmetrik entwickelt, mit der Artefakte in den rekonstruierten IBR-Bildern identifiziert werden können, ohne das Referenzbild zu betrachten, und die somit zur Entwicklung einer effektiven IBR-Erfassungspipeline beiträgt. Schließlich wird ein wahrnehmungsgesteuertes Rendering-Verfahren entwickelt, um visuelle Inhalte in Virtual-Reality-Displays mit hoherWiedergabetreue zu liefern und gleichzeitig die Rechenleistung zu erhalten

Work 2004/2005

WORK is an annual publication of the Department of Architecture that documents student work in design studios and courses in the Master of Architecture and Post-Professional programs, as well as events, faculty news and student awards. It also includes abstracts of PhD dissertations defended that year. It provides an opportunity to explore the creative work of our students and is a permanent record of work in the Department

Developing a flexible and expressive realtime polyphonic wave terrain synthesis instrument based on a visual and multidimensional methodology

The Jitter extended library for Max/MSP is distributed with a gamut of tools for the generation, processing, storage, and visual display of multidimensional data structures. With additional support for a wide range of media types, and the interaction between these mediums, the environment presents a perfect working ground for Wave Terrain Synthesis. This research details the practical development of a realtime Wave Terrain Synthesis instrument within the Max/MSP programming environment utilizing the Jitter extended library. Various graphical processing routines are explored in relation to their potential use for Wave Terrain Synthesis