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Institute
In scientific data visualization huge amounts of data are generated, which implies the task of analyzing these in an efficient way. This includes the reliable detection of important parts and a low expenditure of time and effort. This is especially important for the big-sized seismic volume datasets, that are required for the exploration of oil and gas deposits. Since the generated data is complex and a manual analysis is very time-intensive, a semi-automatic approach could on one hand reduce the time required for the analysis and on the other hand offer more flexibility, than a fully automatic approach.
This master's thesis introduces an algorithm, which is capable of locating regions of interest in seismic volume data automatically by detecting anomalies in local histograms. Furthermore the results are visualized and a variety of tools for the exploration and interpretation of the detected regions are developed. The approach is evaluated by experiments with synthetic data and in interviews with domain experts on the basis of real-world data. Conclusively further improvements to integrate the algorithm into the seismic interpretation workflow are suggested.
Statistical Shape Models (SSMs) are one of the most successful tools in 3Dimage analysis and especially medical image segmentation. By modeling the variability of a population of training shapes, the statistical information inherent in such data are used for automatic interpretation of new images. However, building a high-quality SSM requires manually generated ground truth data from clinical experts. Unfortunately, the acquisition of such data is a time-consuming, error-prone and subjective process. Due to this effort, the majority of SSMs is often based on a limited set of this ground truth training data, which makes the models less statistically meaningful. On the other hand, image data itself is abundant in clinics from daily routine. In this work, methods for automatically constructing a reliable SSM without the need of manual image interpretation from experts are proposed. Thus, the training data is assumed to be the result of any segmentation algorithm or may originate from other sources, e.g. non-expert manual delineations. Depending on the algorithm, the output segmentations will contain errors to a higher or lower degree. In order to account for these errors, areas of low probability of being a boundary should be excluded from the training of the SSM. Therefore, the probabilities are estimated with the help of image-based approaches. By including many shape variations, the corrupted parts can be statistically reconstructed. Two approaches for reconstruction are proposed - an Imputation method and Weighted Robust Principal Component Analysis (WRPCA). This allows the inclusion of many data sets from clinical routine, covering a lot more variations of shape examples. To assess the quality of the models, which are robust against erroneous training shapes, an evaluation compares the generalization and specificity ability to a model build from ground truth data. The results show, that especially WRPCA is a powerful tool to handle corrupted parts and yields to reasonable models, which have a higher quality than the initial segmentations.
Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.
In this thesis the possibilities for real-time visualization of OpenVDB
files are investigated. The basics of OpenVDB, its possibilities, as well
as NanoVDB and its GPU port, were studied. A system was developed
using PNanoVDB, the graphics API port of OpenVDB. Techniques were
explored to improve and accelerate a single ray approach of ray tracing.
To prove real-time capability, two single scattering approaches were
also implemented. One of these was selected, further investigated and
optimized to achieve interactive real-time rendering.
It is important to give artists immediate feedback on their adjustments, as
well as the possibility to change all parameters to ensure a user friendly
creation process.
In addition to the optical rendering, corresponding benchmarks were
collected to compare different improvement approaches and to prove
their relevance. Attention was paid to the rendering times and memory
consumption on the GPU to ensure optimal use. A special focus, when
rendering OpenVDB files, was put on the integrability and extensibility of
the program to allow easy integration into an existing real-time renderer
like U-Render.
In order to plan the interior of a room, various programs for computers,
smart phones or head-mounted displays are available. The transfer to the
real environment is a difficult task. Therefore an augmented reality approach
is developed to illustrate the planning in the real room. If several
people want to contribute their ideas, conventional systems require to
work on one device together. The aim of this master thesis is to design and
develop a collaborative spatial planning application in augmented reality.
The application is developed in Unity with ARCore and C#.
In this thesis, we deal with the question if challenge, flow and fun in computer games are related to each other, and which influence the motivational, psychological components motivation of success, motivation of failure and the chance of success do have. In addition, we want to know if a free choice in the level of difficulty is the optimal way to flow. To examine these theories, a study based on an online survey was executed, in which the participants played the game “flOw“. The results were evaluated with the help of a two-factorial analysis of variance with repeated measurement and tests on correlation. Thereby we found out that there actually exists a relation between challenge, flow and fun and that motivation does matter indirectly.
Clubs, such as Scouts, rely on the work of their volunteer members, who have a variety of tasks to accomplish. Often there are sudden changes in their organization teams and offices, whereby planning steps are lost and inexperience in planning occurs. Since the special requirements are not covered by already existing tools, ScOuT, a planning tool for the organization administration, is designed and developed in this work to support clubs with regard to the mentioned problems. The focus was on identifying and using various suitable guidelines and heuristic methods to create a usable interface. The developed product was evaluated empirically by a user survey in terms of usability.
The result of this study shows that already a high degree of the desired goal could be reached by the inclusion of the guidelines and methods. From this it can be concluded that with the help of user-specific concept ideas and the application of suitable guidelines and methods, a suitable basis for a usable application to support clubs can be created.
Zusätzlich zum Rendern wird die Rechenleistung moderner Grafikkarten immer häufiger auch für allgemeine Berechnungen (GPGPU) genutzt. Für die Umsetzung stehen verschiedene Möglichkeiten zur Verfügung, die von der Verwendung der Renderingpipeline bis zu eigenständigen Schnittstellen reichen. In dieser Arbeit werden mit Render-To-Texture, Transform Feedback, Compute Shader und OpenCL vier verschiedene GPGPU-Methoden untersucht. Anhand von Partikelsystemen werden sie hinsichtlich der benötigten Berechnungszeit, der GPU-Auslastung, Lines of Code und Portierbarkeit miteinander verglichen. Dazu wurden sowohl das N-Körper Problem, Smoothed Particle Hydrodynamics und ein Partikelschwarm als Partikelsysteme umgesetzt. Es konnte gezeigt werden, dass insbesondere OpenCL und Compute Shader sehr gute Ergebnisse liefern.
The goal of simulations in computergraphics is the simulation of realistic phenomena of materials. Therefore, internal and external acting forces are accumulated in each timestep. From those, new velocities get calculated that ultimately change the positions of geometry or particles. Position Based Dynamics omits thie velocity layer and directly works on the positions. Constraints are a set of rules defining the simulated material. Those rules must not be violated throughout the simulation. If this happens, the violating positions get changed so that the constraints get fullfilled once again. In this work a PBD-framework gets implemented, that allows simulations of solids and fluids. Constraints get solved using GPU implementations of Gauss-Seidel and Gauss-Jakobi solvers. Results are physically plausible simulations that are real-time capable.
With the emergence of current generation head-mounted displays (HMDs), virtual reality (VR) is regaining much interest in the field of medical imaging and diagnosis. Room-scale exploration of CT or MRI data in virtual reality feels like an intuitive application. However in VR retaining a high frame rate is more critical than for conventional user interaction seated in front of a screen. There is strong scientific evidence suggesting that low frame rates and high latency have a strong influence on the appearance of cybersickness. This thesis explores two practical approaches to overcome the high computational cost of volume rendering for virtual reality. One lies within the exploitation of coherency properties of the especially costly stereoscopic rendering setup. The main contribution is the development and evaluation of a novel acceleration technique for stereoscopic GPU ray casting. Additionally, an asynchronous rendering approach is pursued to minimize the amount of latency in the system. A selection of image warping techniques has been implemented and evaluated methodically, assessing the applicability for VR volume rendering.