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We present a system that combines voxel and polygonal representations into a single octree acceleration structure that can be used for ray tracing. Voxels are well-suited to create good level-of-detail for high-frequency models where polygonal simplifications usually fail due to the complex structure of the model. However, polygonal descriptions provide the higher visual fidelity. In addition, voxel representations often oversample the geometric domain especially for large triangles, whereas a few polygons can be tested for intersection more quickly.
In dieser Arbeit wird eine Methode zur Darstellung und Generierung von natürlich wirkendem Bewuchs auf besonders großen Arealen und unter Berücksichtigung ökologischer Faktoren vorgestellt. Die Generierung und Visualisierung von Bewuchs ist aufgrund der Komplexität biologischer Systeme und des Detailreichtums von Pflanzenmodellen ein herausforderndes Gebiet der Computergrafik und ermöglicht es, den Realismus von Landschaftsvisualisierungen erheblich zu steigern. Aufbauend auf [DMS06] wird bei Silva der Bewuchs so generiert, dass die zur Darstellung benötigten Wang-Kacheln und die mit ihnen assoziierten Teilverteilungen wiederverwendet werden können. Dazu wird ein Verfahren vorgestellt, um Poisson Disk Verteilungen mit variablen Radien auf nahtlosen Wang-Kachelmengen ohne rechenintensive globale Optimierung zu erzeugen. Durch die Einbeziehung von Nachbarschaften und frei konfigurierbaren Generierungspipelines können beliebige abiotische und biotische Faktoren bei der Bewuchsgenerierung berücksichtigt werden. Die durch Silva auf Wang-Kacheln erzeugten Pflanzenverteilungen ermöglichen, die darauf aufgebauten beschleunigenden Datenstrukturen bei der Visualisierung wieder zu verwenden. Durch Multi-Level Instancing und eine Schachtelung von Kd-Bäumen ist eine Visualisierung von großen bewachsenen Arealen mit geringen Renderzeiten und geringem Memoryfootprint von Hunderten Quadratkilometern Größe möglich.
In contrast to projection-based systems, large, high resolution multi-display systems offer a high pixel density on a large visualization area. This enables users to step up to the displays and see a small but highly detailed area. If the users move back a few steps they don't perceive details at pixel level but will instead get an overview of the whole visualization. Rendering techniques for design evaluation and review or for visualizing large volume data (e.g. Big Data applications) often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates.
A view direction based (VDB) rendering technique renders the user's central field of view in high quality whereas the surrounding is rendered with a level-of-detail approach depending on the distance to the user's central field of view. This approach mimics the physiology of the human eye and conserves the advantage of highly detailed information when standing close to the multi-display system as well as the general overview of the whole scene. In this paper we propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.
Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real‐time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel (high dynamic range, wider color gamut/fidelity), increasing refresh rates (better motion depiction), and an increasing number of displayed views per pixel (stereo, multi‐view, all the way to holographic or lightfield displays). These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.
In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.
In order to achieve the highest possible performance, the ray traversal and intersection routines at the core of every high-performance ray tracer are usually hand-coded, heavily optimized, and implemented separately for each hardware platform—even though they share most of their algorithmic core. The results are implementations that heavily mix algorithmic aspects with hardware and implementation details, making the code non-portable and difficult to change and maintain.
In this paper, we present a new approach that offers the ability to define in a functional language a set of conceptual, high-level language abstractions that are optimized away by a special compiler in order to maximize performance. Using this abstraction mechanism we separate a generic ray traversal and intersection algorithm from its low-level aspects that are specific to the target hardware. We demonstrate that our code is not only significantly more flexible, simpler to write, and more concise but also that the compiled results perform as well as state-of-the-art implementations on any of the tested CPU and GPU platforms.
In order to achieve the highest possible performance, the ray traversal and intersection routines at the core of every high-performance ray tracer are usually hand-coded, heavily optimized, and implemented separately for each hardware platform—even though they share most of their algorithmic core. The results are implementations that heavily mix algorithmic aspects with hardware and implementation details, making the code non-portable and difficult to change and maintain.
In this paper, we present a new approach that offers the ability to define in a functional language a set of conceptual, high-level language abstractions that are optimized away by a special compiler in order to maximize performance. Using this abstraction mechanism we separate a generic ray traversal and intersection algorithm from its low-level aspects that are specific to the target hardware. We demonstrate that our code is not only significantly more flexible, simpler to write, and more concise but also that the compiled results perform as well as state-of-the-art implementations on any of the tested CPU and GPU platforms.
Rendering techniques for design evaluation and review or for visualizing large volume data often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates. A view direction based rendering technique renders the users central field of view in high quality whereas the surrounding is rendered with a level of detail approach depending on the distance to the users central field of view thus giving the opportunity to increase rendering efficiency. We propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.