TY - GEN A1 - Kratz, Andrea A1 - Meyer, Björn A1 - Hotz, Ingrid T1 - A Visual Approach to Analysis of Stress Tensor Fields N2 - We present a visual approach for the exploration of stress tensor fields. Therefore, we introduce the idea of multiple linked views to tensor visualization. In contrast to common tensor visualization methods that only provide a single view to the tensor field, we pursue the idea of providing various perspectives onto the data in attribute and object space. Especially in the context of stress tensors, advanced tensor visualization methods have a young tradition. Thus, we propose a combination of visualization techniques domain experts are used to with statistical views of tensor attributes. The application of this concept to tensor fields was achieved by extending the notion of shape space. It provides an intuitive way of finding tensor invariants that represent relevant physical properties. Using brushing techniques, the user can select features in attribute space, which are mapped to displayable entities in a three-dimensional hybrid visualization in object space. Volume rendering serves as context, while glyphs encode the whole tensor information in focus regions. Tensorlines can be included to emphasize directionally coherent features in the tensor field. We show that the benefit of such a multi-perspective approach is manifold. Foremost, it provides easy access to the complexity of tensor data. Moreover, including wellknown analysis tools, such as Mohr diagrams, users can familiarize themselves gradually with novel visualization methods. Finally, by employing a focus-driven hybrid rendering, we significantly reduce clutter, which was a major problem of other three-dimensional tensor visualization methods. T3 - ZIB-Report - 10-26 KW - Visualisierung KW - Datenanalyse KW - Tensorfelder Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-11915 ER - TY - GEN A1 - Kratz, Andrea A1 - Reininghaus, Jan A1 - Hadwiger, Markus A1 - Hotz, Ingrid T1 - Adaptive Screen-Space Sampling for Volume Ray-Casting N2 - This work is concerned with adaptive screen-space sampling for volume ray-casting. The goal is to reduce the number of rays being cast into the scene and, thus, the overall number of sampling points. We guarantee reliable images through explicit error control using an error estimator that is founded in the field of finite element methods (FEM). FEM theory further provides a well-founded theory to prove the efficiency of the presented algorithm via convergence analysis. We, therefore, compare the convergence behavior of our method against uniform subdivisions and a refinement scheme that was presented in the context of CPU volume ray-casting. Minimizing the number of sampling points is of interest for rendering large datasets where each evaluation might need an expensive decompression. Furthermore, with increasing screen resolutions high-resolution images are created more efficiently with our method. T3 - ZIB-Report - 11-04 Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12446 ER -