13 Zentrale Universitätseinrichtungen
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14
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Item Open Access Interactive visual analysis of vector fields(2013) Bachthaler, Sven; Weiskopf, Daniel (Prof. Dr.)Visualization is a very active research area due to several reasons. For years, data sets have been getting larger and more complex, increasing the difficulty of handling this data. Furthermore, in technical application areas, visualization is an essential part of the engineering process. These developments drive the need for improvements of all aspects of scientific visualization, as well as the integration of information visualization techniques. This thesis focuses on the development of visualization and analysis techniques for different types of vector fields - vector fields representing the flow of air or water, but also magnetic fields and vector fields derived computationally from scalar fields. The different techniques that were developed to handle such fields are organized in three parts: the first part presents methods that visualize vector fields in dense manner. The second part discusses methods that rely on topological approaches - the complexity of the visualization is reduced by concentrating on features of the data. In the third and final part, continuous scatterplots are introduced, which are designed to analyze correlations in multivariate data sets. In the first part, the goal is to show as much information as possible and using every available pixel of the viewport to do so. However, one of the challenges of dense visualization methods is to maintain interactivity for high resolution visualizations. A cluster environment is used here to offer increased rendering performance and memory size for large and complex data sets. Additionally, an animation-based approach is presented that allows one to decouple the line-like patterns of LIC from the direction of animation. This decoupling is desirable since perception research suggests that LIC-based techniques combined with animation are non-optimal for local motion detection of the human visual system. The second part focuses on topological methods to filter the data and hence, reduce the complexity of the resulting visualization. For time-dependent vector fields, Lagrangian coherent structures are used to visualize space-time manifolds that represent the topology of these fields. Furthermore, the dynamic of such fields is visualized directly on these space-time manifolds, allowing us to quantify the hyperbolicity close to the topological skeleton. In addition, another technique is presented in the second part that allows one to visualize the topology of magnetic fields based on dipoles. Here, traditional topological methods are non-optimal, hence, an alternative topology is developed that visualizes the existence and magnitude of magnetic flux between dipoles. In the final part, the mathematical basis and several computational approaches are presented to compute continuous scatterplots. These plots are designed to work with data sets defined on a continuous domain, which is typical for scientific visualization data. In contrast to traditional scatterplots, they visualize the density in the data domain, instead of merely plotting data attached at discrete sampling positions. The additional computational approaches are an improvement of the original approach in terms of flexibility - they allow a trade-off between output quality and rendering performance, as well as the use of generic interpolation methods.