11 research outputs found

    5D Covariance Tracing for Efficient Defocus and Motion Blur

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    The rendering of effects such as motion blur and depth-of-field requires costly 5D integrals. We dramatically accelerate their computation through adaptive sampling and reconstruction based on the prediction of the anisotropy and bandwidth of the integrand. For this, we develop a new frequency analysis of the 5D temporal light-field, and show that first-order motion can be handled through simple changes of coordinates in 5D. We further introduce a compact representation of the spectrum using the co- variance matrix and Gaussian approximations. We derive update equations for the 5 × 5 covariance matrices for each atomic light transport event, such as transport, occlusion, BRDF, texture, lens, and motion. The focus on atomic operations makes our work general, and removes the need for special-case formulas. We present a new rendering algorithm that computes 5D covariance matrices on the image plane by tracing paths through the scene, focusing on the single-bounce case. This allows us to reduce sampling rates when appropriate and perform reconstruction of images with complex depth-of-field and motion blur effects

    Fast and detailed approximate global illumination by irradiance decomposition

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    In this paper we present an approximate method for accelerated computation of the final gathering step in a global illumination algorithm. Our method operates by decomposing the radiance field close to surfaces into separate far- and near-field components that can be approximated individually. By computing surface shading using these approximations, instead of directly querying the global illumination solution, we have been able to obtain rendering time speed ups on the order of 10 × compared to previous acceleration methods. Our approximation schemes rely mainly on the assumptions that radiance due to distant objects will exhibit low spatial and angular variation, and that the visibility between a surface and nearby surfaces can be reasonably predicted by simple locationand orientation-based heuristics. Motivated by these assumptions, our far-field scheme uses scattered-data interpolation with spherical harmonics to represent spatial and angular variation, and our near-field scheme employs an aggressively simple visibility heuristic. For our test scenes, the errors introduced when our assumptions fail do not result in visually objectionable artifacts or easily noticeable deviation from a ground-truth solution. We also discuss how our near-field approximation can be used with standard local illumination algorithms to produce significantly improved images at only negligible additional cost

    Applied Visualization in the Neurosciences and the Enhancement of Visualization through Computer Graphics

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    The complexity and size of measured and simulated data in many fields of science is increasing constantly. The technical evolution allows for capturing smaller features and more complex structures in the data. To make this data accessible by the scientists, efficient and specialized visualization techniques are required. Maximum efficiency and value for the user can only be achieved by adapting visualization to the specific application area and the specific requirements of the scientific field. Part I: In the first part of my work, I address the visualization in the neurosciences. The neuroscience tries to understand the human brain; beginning at its smallest parts, up to its global infrastructure. To achieve this ambitious goal, the neuroscience uses a combination of three-dimensional data from a myriad of sources, like MRI, CT, or functional MRI. To handle this diversity of different data types and sources, the neuroscience need specialized and well evaluated visualization techniques. As a start, I will introduce an extensive software called \"OpenWalnut\". It forms the common base for developing and using visualization techniques with our neuroscientific collaborators. Using OpenWalnut, standard and novel visualization approaches are available to the neuroscientific researchers too. Afterwards, I am introducing a very specialized method to illustrate the causal relation of brain areas, which was, prior to that, only representable via abstract graph models. I will finalize the first part of my work with an evaluation of several standard visualization techniques in the context of simulated electrical fields in the brain. The goal of this evaluation was clarify the advantages and disadvantages of the used visualization techniques to the neuroscientific community. We exemplified these, using clinically relevant scenarios. Part II: Besides the data preprocessing, which plays a tremendous role in visualization, the final graphical representation of the data is essential to understand structure and features in the data. The graphical representation of data can be seen as the interface between the data and the human mind. The second part of my work is focused on the improvement of structural and spatial perception of visualization -- the improvement of the interface. Unfortunately, visual improvements using computer graphics methods of the computer game industry is often seen sceptically. In the second part, I will show that such methods can be applied to existing visualization techniques to improve spatiality and to emphasize structural details in the data. I will use a computer graphics paradigm called \"screen space rendering\". Its advantage, amongst others, is its seamless applicability to nearly every visualization technique. I will start with two methods that improve the perception of mesh-like structures on arbitrary surfaces. Those mesh structures represent second-order tensors and are generated by a method named \"TensorMesh\". Afterwards I show a novel approach to optimally shade line and point data renderings. With this technique it is possible for the first time to emphasize local details and global, spatial relations in dense line and point data.In vielen Bereichen der Wissenschaft nimmt die GrĂ¶ĂŸe und KomplexitĂ€t von gemessenen und simulierten Daten zu. Die technische Entwicklung erlaubt das Erfassen immer kleinerer Strukturen und komplexerer Sachverhalte. Um solche Daten dem Menschen zugĂ€nglich zu machen, benötigt man effiziente und spezialisierte Visualisierungswerkzeuge. Nur die Anpassung der Visualisierung auf ein Anwendungsgebiet und dessen Anforderungen erlaubt maximale Effizienz und Nutzen fĂŒr den Anwender. Teil I: Im ersten Teil meiner Arbeit befasse ich mich mit der Visualisierung im Bereich der Neurowissenschaften. Ihr Ziel ist es, das menschliche Gehirn zu begreifen; von seinen kleinsten Teilen bis hin zu seiner Gesamtstruktur. Um dieses ehrgeizige Ziel zu erreichen nutzt die Neurowissenschaft vor allem kombinierte, dreidimensionale Daten aus vielzĂ€hligen Quellen, wie MRT, CT oder funktionalem MRT. Um mit dieser Vielfalt umgehen zu können, benötigt man in der Neurowissenschaft vor allem spezialisierte und evaluierte Visualisierungsmethoden. ZunĂ€chst stelle ich ein umfangreiches Softwareprojekt namens \"OpenWalnut\" vor. Es bildet die gemeinsame Basis fĂŒr die Entwicklung und Nutzung von Visualisierungstechniken mit unseren neurowissenschaftlichen Kollaborationspartnern. Auf dieser Basis sind klassische und neu entwickelte Visualisierungen auch fĂŒr Neurowissenschaftler zugĂ€nglich. Anschließend stelle ich ein spezialisiertes Visualisierungsverfahren vor, welches es ermöglicht, den kausalen Zusammenhang zwischen Gehirnarealen zu illustrieren. Das war vorher nur durch abstrakte Graphenmodelle möglich. Den ersten Teil der Arbeit schließe ich mit einer Evaluation verschiedener Standardmethoden unter dem Blickwinkel simulierter elektrischer Felder im Gehirn ab. Das Ziel dieser Evaluation war es, der neurowissenschaftlichen Gemeinde die Vor- und Nachteile bestimmter Techniken zu verdeutlichen und anhand klinisch relevanter FĂ€lle zu erlĂ€utern. Teil II: Neben der eigentlichen Datenvorverarbeitung, welche in der Visualisierung eine enorme Rolle spielt, ist die grafische Darstellung essenziell fĂŒr das VerstĂ€ndnis der Strukturen und Bestandteile in den Daten. Die grafische ReprĂ€sentation von Daten bildet die Schnittstelle zum Gehirn des Menschen. Der zweite Teile meiner Arbeit befasst sich mit der Verbesserung der strukturellen und rĂ€umlichen Wahrnehmung in Visualisierungsverfahren -- mit der Verbesserung der Schnittstelle. Leider werden viele visuelle Verbesserungen durch Computergrafikmethoden der Spieleindustrie mit Argwohn beĂ€ugt. Im zweiten Teil meiner Arbeit werde ich zeigen, dass solche Methoden in der Visualisierung angewendet werden können um den rĂ€umlichen Eindruck zu verbessern und Strukturen in den Daten hervorzuheben. Dazu nutze ich ein in der Computergrafik bekanntes Paradigma: das \"Screen Space Rendering\". Dieses Paradigma hat den Vorteil, dass es auf nahezu jede existierende Visualiserungsmethode als Nachbearbeitunsgschritt angewendet werden kann. ZunĂ€chst fĂŒhre ich zwei Methoden ein, die die Wahrnehmung von gitterartigen Strukturen auf beliebigen OberflĂ€chen verbessern. Diese Gitter reprĂ€sentieren die Struktur von Tensoren zweiter Ordnung und wurden durch eine Methode namens \"TensorMesh\" erzeugt. Anschließend zeige ich eine neuartige Technik fĂŒr die optimale Schattierung von Linien und Punktdaten. Mit dieser Technik ist es erstmals möglich sowohl lokale Details als auch globale rĂ€umliche ZusammenhĂ€nge in dichten Linien- und Punktdaten zu erfassen

    Efficient Many-Light Rendering of Scenes with Participating Media

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    We present several approaches based on virtual lights that aim at capturing the light transport without compromising quality, and while preserving the elegance and efficiency of many-light rendering. By reformulating the integration scheme, we obtain two numerically efficient techniques; one tailored specifically for interactive, high-quality lighting on surfaces, and one for handling scenes with participating media

    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

    Perceptually-motivated, interactive rendering and editing of global illumination

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    This thesis proposes several new perceptually-motivated techniques to synthesize, edit and enhance depiction of three-dimensional virtual scenes. Finding algorithms that fit the perceptually economic middle ground between artistic depiction and full physical simulation is the challenge taken in this work. First, we will present three interactive global illumination rendering approaches that are inspired by perception to efficiently depict important light transport. Those methods have in common to compute global illumination in large and fully dynamic scenes allowing for light, geometry, and material changes at interactive or real-time rates. Further, this thesis proposes a tool to edit reflections, that allows to bend physical laws to match artistic goals by exploiting perception. Finally, this work contributes a post-processing operator that depicts high contrast scenes in the same way as artists do, by simulating it "seen'; through a dynamic virtual human eye in real-time.Diese Arbeit stellt eine Anzahl von Algorithmen zur Synthese, Bearbeitung und verbesserten Darstellung von virtuellen drei-dimensionalen Szenen vor. Die Herausforderung liegt dabei in der Suche nach Ausgewogenheit zwischen korrekter physikalischer Berechnung und der kĂŒnstlerischen, durch die Gesetze der menschlichen Wahrnehmung motivierten Praxis. ZunĂ€chst werden drei Verfahren zur Bild-Synthese mit globaler Beleuchtung vorgestellt, deren Gemeinsamkeit in der effizienten Handhabung großer und dynamischer virtueller Szenen liegt, in denen sich Geometrie, Materialen und Licht frei verĂ€ndern lassen. Darauffolgend wird ein Werkzeug zum Editieren von Reflektionen in virtuellen Szenen das die menschliche Wahrnehmung ausnutzt um kĂŒnstlerische Vorgaben umzusetzen, vorgestellt. Die Arbeit schließt mit einem Filter am Ende der Verarbeitungskette, der den wahrgenommen Kontrast in einem Bild erhöht, indem er die Entstehung von Glanzeffekten im menschlichen Auge nachbildet
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