@misc{RosanwoPetzProhaskaetal., author = {Rosanwo, Olufemi and Petz, Christoph and Prohaska, Steffen and Hotz, Ingrid and Hege, Hans-Christian}, title = {Dual Streamline Seeding - Method and Implementation}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11032}, number = {08-49}, abstract = {This work introduces a novel streamline seeding technique based on dual streamlines that are orthogonal to the vector field, instead of tangential. The greedy algorithm presented here produces a net of orthogonal streamlines that is iteratively refined resulting in good domain coverage and a high degree of continuity and uniformity. The algorithm is easy to implement and efficient, and it naturally extends to curved surfaces.}, language = {en} } @misc{KratzMeyerHotz2010, author = {Kratz, Andrea and Meyer, Bj{\"o}rn and Hotz, Ingrid}, title = {A Visual Approach to Analysis of Stress Tensor Fields}, doi = {/10.4230/DFU.Vol2.SciViz.2011.188}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11915}, number = {10-26}, year = {2010}, abstract = {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.}, language = {en} } @misc{ReininghausKastenWeinkaufetal., author = {Reininghaus, Jan and Kasten, Jens and Weinkauf, Tino and Hotz, Ingrid}, title = {Combinatorial Feature Flow Fields: Tracking Critical Points in Discrete Scalar Fields}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-12151}, number = {11-02}, abstract = {We propose a combinatorial algorithm to track critical points of 2D time-dependent scalar fields. Existing tracking algorithms such as Feature Flow Fields apply numerical schemes utilizing derivatives of the data, which makes them prone to noise and involve a large number of computational parameters. In contrast, our method is robust against noise since it does not require derivatives, interpolation, and numerical integration. Furthermore, we propose an importance measure that combines the spatial persistence of a critical point with its temporal evolution. This leads to a time-aware feature hierarchy, which allows us to discriminate important from spurious features. Our method requires only a single, easy-to-tune computational parameter and is naturally formulated in an out-of-core fashion, which enables the analysis of large data sets. We apply our method to a number of data sets and compare it to the stabilized continuous Feature Flow Field tracking algorithm.}, language = {en} } @misc{KastenReininghausHotzetal., author = {Kasten, Jens and Reininghaus, Jan and Hotz, Ingrid and Hege, Hans-Christian and Noack, Bernd and Daviller, Guillaume and Morzyński, Marek}, title = {Acceleration feature points of unsteady shear flows}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-58397}, abstract = {A framework is proposed for extracting features in 2D transient flows, based on the acceleration field to ensure Galilean invariance. The minima of the acceleration magnitude, i.e. a superset of the acceleration zeros, are extracted and discriminated into vortices and saddle points --- based on the spectral properties of the velocity Jacobian. The extraction of topological features is performed with purely combinatorial algorithms from discrete computational topology. The feature points are prioritized with persistence, as a physically meaningful importance measure. These features are tracked in time with a robust algorithm for tracking features. Thus a space-time hierarchy of the minima is built and vortex merging events are detected. The acceleration feature extraction strategy is applied to three two-dimensional shear flows: (1) an incompressible periodic cylinder wake, (2) an incompressible planar mixing layer and (3) a weakly compressible planar jet. The vortex-like acceleration feature points are shown to be well aligned with acceleration zeros, maxima of the vorticity magnitude, minima of pressure field and minima of λ2.}, language = {en} } @misc{KuhnEngelkeFlatkenetal., author = {Kuhn, Alexander and Engelke, Wito and Flatken, Markus and Hege, Hans-Christian and Hotz, Ingrid}, title = {Topology-based Analysis for Multimodal Atmospheric Data of Volcano Eruptions}, issn = {1438-0064}, doi = {10.1007/978-3-319-44684-4_2}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-57043}, abstract = {Many scientific applications deal with data from a multitude of different sources, e.g., measurements, imaging and simulations. Each source provides an additional perspective on the phenomenon of interest, but also comes with specific limitations, e.g. regarding accuracy, spatial and temporal availability. Effectively combining and analyzing such multimodal and partially incomplete data of limited accuracy in an integrated way is challenging. In this work, we outline an approach for an integrated analysis and visualization of the atmospheric impact of volcano eruptions. The data sets comprise observation and imaging data from satellites as well as results from numerical particle simulations. To analyze the clouds from the volcano eruption in the spatiotemporal domain we apply topological methods. Extremal structures reveal structures in the data that support clustering and comparison. We further discuss the robustness of those methods with respect to different properties of the data and different parameter setups. Finally we outline open challenges for the effective integrated visualization using topological methods.}, language = {en} } @misc{KratzReininghausHadwigeretal.2011, author = {Kratz, Andrea and Reininghaus, Jan and Hadwiger, Markus and Hotz, Ingrid}, title = {Adaptive Screen-Space Sampling for Volume Ray-Casting}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-12446}, number = {11-04}, year = {2011}, abstract = {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.}, language = {en} }