Open Access

Volumen Rendering ist ein eigenes Thema der Computergrafik und wurde in den letzten Jahren fortlaufend optimiert. Neben verschiedenen Ansätzen, die in Software implementiert sind, gibt es auch einige spezielle Methoden, die die Grafikhardware geeignet nutzen. 2003 wurde ein erstes Paper von J. Krüger und R. Westermann veröffentlicht, in dem eine Hardwareimplementierung eines Raycasting Volumen Renderers gezeigt wurde, ein Ansatz, der bislang nicht geeignet in Hardware umgesetzt werden konnte. Die Vorteile von diesem Ansatz bestehen in zwei Beschleunigungstechniken, die entweder bei fast opaken Darstellungen der Datensätze oder bei Darstellungen mit wenig sichtbaren Daten ausgespielt werden können. Diese Arbeit zeigt und erläutert, neben der theoretischen Einführung in das Thema, die Implementierung eines interaktiven raycasting-basierten Volumen Renderers auf neuester Grafikhardware mit Hilfe von Shaderprogrammen. Wesentliche Schritte folgen der Veröffentlichung von J. Krüger und R. Westermann, welche aber viele Details und Problemstellen verschweigt. Die Ergebnisse werden mit einem 3D-Textur Volumenrenderverfahren verglichen, wobei durch charakteristische Testdatensätze die beiden Beschleunigungstechniken des Raycasters untersucht werden. Weil beide Techniken bei fast allen Datensätzen eine Beschleunigung des Rendervorgangs hervorrufen sollten, werden die erzielten Ergebnisse miteinander verglichen und kritisch besprochen, um zu beurteilen, ob das hier implementierte Verfahren schneller als das bisher oft verwendete 3D-Texturverfahren ist.

Augmented Reality (AR) findet heutzutage sehr viele Anwendungsbereiche. Durch die Überlagerung von virtuellen Informationen mit der realen Umgebung eignet sich diese Technologie besonders für die Unterstützung der Benutzer bei technischen Wartungs- oder Reparaturvorgängen. Damit die virtuellen Daten korrekt mit der realen Welt überlagert werden, müssen Position und Orientierung der Kamera durch ein Trackingverfahren ermittelt werden. In dieser Arbeit wurde für diesen Zweck ein markerloses, modellbasiertes Trackingsystem implementiert. Während einer Initialisierungs-Phase wird die Kamerapose mithilfe von kalibrierten Referenzbildern, sogenannten Keyframes, bestimmt. In einer darauffolgenden Tracking-Phase wird das zu trackende Objekt weiterverfolgt. Evaluiert wurde das System an dem 1:1 Trainingsmodell des biologischen Forschungslabors Biolab, welches von der Europäischen Weltraumorganisation ESA zur Verfügung gestellt wurde.

Computer graphics research strives to synthesize images of a high visual realism that are indistinguishable from real visual experiences. While modern image synthesis approaches enable to create digital images of astonishing complexity and beauty, processing resources remain a limiting factor. Here, rendering efficiency is a central challenge involving a trade-off between visual fidelity and interactivity. For that reason, there is still a fundamental difference between the perception of the physical world and computer-generated imagery. At the same time, advances in display technologies drive the development of novel display devices. The dynamic range, the pixel densities, and refresh rates are constantly increasing. Display systems enable a larger visual field to be addressed by covering a wider field-of-view, due to either their size or in the form of head-mounted devices. Currently, research prototypes are ranging from stereo and multi-view systems, head-mounted devices with adaptable lenses, up to retinal projection, and lightfield/holographic displays. Computer graphics has to keep step with, as driving these devices presents us with immense challenges, most of which are currently unsolved. Fortunately, the human visual system has certain limitations, which means that providing the highest possible visual quality is not always necessary. Visual input passes through the eye’s optics, is filtered, and is processed at higher level structures in the brain. Knowledge of these processes helps to design novel rendering approaches that allow the creation of images at a higher quality and within a reduced time-frame. This thesis presents the state-of-the-art research and models that exploit the limitations of perception in order to increase visual quality but also to reduce workload alike - a concept we call perception-driven rendering. This research results in several practical rendering approaches that allow some of the fundamental challenges of computer graphics to be tackled. By using different tracking hardware, display systems, and head-mounted devices, we show the potential of each of the presented systems. The capturing of specific processes of the human visual system can be improved by combining multiple measurements using machine learning techniques. Different sampling, filtering, and reconstruction techniques aid the visual quality of the synthesized images. An in-depth evaluation of the presented systems including benchmarks, comparative examination with image metrics as well as user studies and experiments demonstrated that the methods introduced are visually superior or on the same qualitative level as ground truth, whilst having a significantly reduced computational complexity.

Despite their age, ray-based rendering methods are still a very active field of research with many challenges when it comes to interactive visualization. In this thesis, we present our work on Guided High-Quality Rendering, Foveated Ray Tracing for Head Mounted Displays and Hash-based Hierarchical Caching and Layered Filtering. Our system for Guided High-Quality Rendering allows for guiding the sampling rate of ray-based rendering methods by a user-specified Region of Interest (RoI). We propose two interaction methods for setting such an RoI when using a large display system and a desktop display, respectively. This makes it possible to compute images with a heterogeneous sample distribution across the image plane. Using such a non-uniform sample distribution, the rendering performance inside the RoI can be significantly improved in order to judge specific image features. However, a modified scheduling method is required to achieve sufficient performance. To solve this issue, we developed a scheduling method based on sparse matrix compression, which has shown significant improvements in our benchmarks. By filtering the sparsely sampled image appropriately, large brightness variations in areas outside the RoI are avoided and the overall image brightness is similar to the ground truth early in the rendering process. When using ray-based methods in a VR environment on head-mounted display de vices, it is crucial to provide sufficient frame rates in order to reduce motion sickness. This is a challenging task when moving through highly complex environments and the full image has to be rendered for each frame. With our foveated rendering sys tem, we provide a perception-based method for adjusting the sample density to the user’s gaze, measured with an eye tracker integrated into the HMD. In order to avoid disturbances through visual artifacts from low sampling rates, we introduce a reprojection-based rendering pipeline that allows for fast rendering and temporal accumulation of the sparsely placed samples. In our user study, we analyse the im pact our system has on visual quality. We then take a closer look at the recorded eye tracking data in order to determine tracking accuracy and connections between different fixation modes and perceived quality, leading to surprising insights. For previewing global illumination of a scene interactively by allowing for free scene exploration, we present a hash-based caching system. Building upon the concept of linkless octrees, which allow for constant-time queries of spatial data, our frame work is suited for rendering such previews of static scenes. Non-diffuse surfaces are supported by our hybrid reconstruction approach that allows for the visualization of view-dependent effects. In addition to our caching and reconstruction technique, we introduce a novel layered filtering framework, acting as a hybrid method between path space and image space filtering, that allows for the high-quality denoising of non-diffuse materials. Also, being designed as a framework instead of a concrete filtering method, it is possible to adapt most available denoising methods to our layered approach instead of relying only on the filtering of primary hitpoints.

The Java Virtual Machine (JVM) executes the compiled bytecode version of a Java program and acts as a layer between the program and the operating system. The JVM provides additional features such as Process, Thread, and Memory Management to manage the execution of these programs. The Garbage Collection (GC) is part of the memory management and has an impact on the overall runtime performance because it is responsible for removing dead objects from the heap. Currently, the execution of a program needs to be halted during every GC run. The problem of this stop-the-world approach is that all threads in the JVM need to be suspended. It would be desirable to have a thread-local GC that only blocks the current thread and does not affect any other threads. In particular, this would improve the execution of multi-threaded Java programs. An object that is accessible by more than one thread is called escaped. It is not possible to thread-locally determine if escaped objects are still alive so that they cannot be handled in a thread-local GC. To gain significant performance improvements with a thread-local GC, it is therefore necessary to determine if it is possible to reliably predict if a given object will escape. Experimental results show that the escaping of objects can be predicted with high accuracy based on the line of code the object was allocated from. A thread-local GC was developed to minimize the number of stop-the-world GCs. The prototype implementation delivers a proof-of-concept that shows that this goal can be achieved in certain scenarios.