Harald Obermaier

University of California, Davis, Davis, California, United States

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Publications (25)19.25 Total impact

  • Harald Obermaier · Kenneth I Joy ·
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    ABSTRACT: Effective display and visual analysis of complex 3D data is a challenging task. Occlusions, overlaps, and projective distortions-as frequently caused by typical 3D rendering techniques-can be major obstacles to unambiguous and robust data analysis. Slicing planes are a ubiquitous tool to resolve several of these issues. They act as simple clipping geometry to provide clear cut-away views of the data. We propose to enhance the visualization and analysis process by providing methods for automatic placement of such slicing planes based on local optimization of gradient vector flow. The final obtained slicing planes maximize the total amount of information displayed with respect to a pre-specified importance function. We demonstrate how such automated slicing plane placement is able to support and enrich 3D data visualization and analysis in multiple scenarios, such as volume or surface rendering, and evaluate its performance in several benchmark data sets.
    IEEE Transactions on Visualization and Computer Graphics 11/2015; 21(12):1-1. DOI:10.1109/TVCG.2015.2414455 · 2.17 Impact Factor
  • Jennifer Chandler · Harald Obermaier · Kenneth I. Joy ·
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    ABSTRACT: Particle tracing in time-varying flow fields is traditionally performed by numerical integration of the underlying vector field. This procedure can become computationally expensive, especially in scattered, particle-based flow fields, which complicate interpolation due to the lack of an explicit neighborhood structure. If such a particle-based flow field allows for the identification of consecutive particle positions, an alternative approach to particle tracing can be employed: we substitute repeated numerical integration of vector data by geometric interpolation in the highly dynamic particle system as defined by the particle-based simulation. To allow for efficient and accurate location and interpolation of changing particle neighborhoods, we develop a modified k-d tree representation that is capable of creating a dynamic partitioning of even highly compressible data sets with strongly varying particle densities. With this representation we are able to efficiently perform pathline computation by identifying, tracking, and updating an enclosing, dynamic particle neighborhood as particles move overtime. We investigate and evaluate the complexity, accuracy, and robustness of this interpolation-based alternative approach to trajectory generation in compressible and incompressible particle systems generated by simulation techniques such as Smoothed Particle Hydrodynamics (SPH).
    IEEE Transactions on Visualization and Computer Graphics 09/2015; 21(1):68-80. DOI:10.1109/TVCG.2014.2325043 · 2.17 Impact Factor
  • A. Berres · H. Obermaier · K. Joy · H. Hagen ·
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    ABSTRACT: Time surfaces are a versatile tool to visualise advection and deformation in flow fields. Due to complex flow behaviours involving stretching, shearing, and folding, straightforward mesh-based representations of these surfaces can develop artefacts and degenerate quickly. Common counter-measures rely on refinement and adaptive insertion of new particles which lead to an unpredictable increase in memory requirements. We propose a novel time surface extraction technique that keeps the number of required flow particles constant, while providing a high level of fidelity and enabling straightforward load balancing. Our solution implements a 2D particle relaxation procedure that makes use of local surface metric tensors to model surface deformations. We combine this with an accurate bicubic surface representation to provide an artefact-free surface visualisation. We demonstrate and evaluate benefits of the proposed method with respect to surface accuracy and computational efficiency.
  • A. Agranovsky · H. Obermaier · C. Garth · K.I. Joy ·
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    ABSTRACT: Where the computation of particle trajectories in classic vector field representations includes computationally involved numerical integration, a Lagrangian representation in the form of a flow map opens up new alternative ways of trajectory extraction through interpolation. In our paper, we present a novel re-organization of the Lagrangian representation by sub-sampling a pre-computed set of trajectories into multiple levels of resolution, maintaining a bound over the amount of memory mapped by the file system. We exemplify the advantages of replacing integration with interpolation for particle trajectory calculation through a real-time, low memory cost, interactive exploration environment for the study of flow fields. Beginning with a base resolution, once an area of interest is located, additional trajectories from other levels of resolution are dynamically loaded, densely covering those regions of the flow field that are relevant for the extraction of the desired feature. We show that as more trajectories are loaded, the accuracy of the extracted features converges to the accuracy of the flow features extracted from numerical integration with the added benefit of real-time, non-iterative, multi-resolution path and time surface extraction.
    Proceedings of SPIE - The International Society for Optical Engineering 01/2015; 9397. DOI:10.1117/12.2083253 · 0.20 Impact Factor
  • Harald Obermaier · Kenneth I. Joy ·
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    ABSTRACT: Simulating complex events is a challenge and often requires carefully selecting simulation parameters. As vast computation resources become available, researchers can run alternative parameter settings or simulation models in parallel, creating an ensemble of possible outcomes for a given event of interest. The visual analysis of ensembles is one of visualization's most important new areas and should greatly affect the field in the next few years. The goal is to develop expressive visualizations of an ensemble's properties to support scientists in this demanding parameter-space exploration.
    IEEE Computer Graphics and Applications 05/2014; 34(3):8-11. DOI:10.1109/MCG.2014.52 · 0.91 Impact Factor
  • Mathias Hummel · Harald Obermaier · Christoph Garth · Kenneth I Joy ·
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    ABSTRACT: Sets of simulation runs based on parameter and model variation, so-called ensembles, are increasingly used to model physical behaviors whose parameter space is too large or complex to be explored automatically. Visualization plays a key role in conveying important properties in ensembles, such as the degree to which members of the ensemble agree or disagree in their behavior. For ensembles of time-varying vector fields, there are numerous challenges for providing an expressive comparative visualization, among which is the requirement to relate the effect of individual flow divergence to joint transport characteristics of the ensemble. Yet, techniques developed for scalar ensembles are of little use in this context, as the notion of transport induced by a vector field cannot be modeled using such tools. We develop a Lagrangian framework for the comparison of flow fields in an ensemble. Our techniques evaluate individual and joint transport variance and introduce a classification space that facilitates incorporation of these properties into a common ensemble visualization. Variances of Lagrangian neighborhoods are computed using pathline integration and Principal Components Analysis. This allows for an inclusion of uncertainty measurements into the visualization and analysis approach. Our results demonstrate the usefulness and expressiveness of the presented method on several practical examples.
    12/2013; 19(12):2743-52. DOI:10.1109/TVCG.2013.141
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    ABSTRACT: Numerical ensemble forecasting is a powerful tool that drives many risk analysis efforts and decision making tasks. These ensembles are composed of individual simulations that each uniquely model a possible outcome for a common event of interest: e.g., the direction and force of a hurricane, or the path of travel and mortality rate of a pandemic. This paper presents a new visual strategy to help quantify and characterize a numerical ensemble's predictive uncertainty: i.e., the ability for ensemble constituents to accurately and consistently predict an event of interest based on ground truth observations. Our strategy employs a Bayesian framework to first construct a statistical aggregate from the ensemble. We extend the information obtained from the aggregate with a visualization strategy that characterizes predictive uncertainty at two levels: at a global level, which assesses the ensemble as a whole, as well as a local level, which examines each of the ensemble's constituents. Through this approach, modelers are able to better assess the predictive strengths and weaknesses of the ensemble as a whole, as well as individual models. We apply our method to two datasets to demonstrate its broad applicability.
    12/2013; 19(12):2703-12. DOI:10.1109/TVCG.2013.138
  • Iuri Prilepov · Harald Obermaier · Eduard Deines · Christoph Garth · Kenneth I Joy ·
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    ABSTRACT: Multifluid simulations often create volume fraction data, representing fluid volumes per region or cell of a fluid data set. Accurate and visually realistic extraction of fluid boundaries is a challenging and essential task for efficient analysis of multifluid data. In this work, we present a new material interface reconstruction method for such volume fraction data. Within each cell of the data set, our method utilizes a gradient field approximation based on trilinearly blended Coons-patches to generate a volume fraction function, representing the change in volume fractions over the cells. A continuously varying isovalue field is applied to this function to produce a smooth interface that preserves the given volume fractions well. Further, the method allows user-controlled balance between volume accuracy and physical plausibility of the interface. The method works on two- and three-dimensional Cartesian grids, and handles multiple materials. Calculations are performed locally and utilize only the one-ring of cells surrounding a given cell, allowing visualizations of the material interfaces to be easily generated on a GPU or in a large-scale distributed parallel environment. Our results demonstrate the robustness, accuracy, and flexibility of the developed algorithms.
    10/2013; 19(10):1687-99. DOI:10.1109/TVCG.2013.16
  • Fang Chen · Harald Obermaier · Hans Hagen · Bernd Hamann · Julien Tierny · Valerio Pascucci ·
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    ABSTRACT: Liquid–liquid extraction is a typical multi-fluid problem in chemical engineering where two types of immiscible fluids are mixed together. Mixing of two-phase fluids results in a time-varying fluid density distribution, quantitatively indicating the presence of liquid phases. For engineers who design extraction devices, it is crucial to understand the density distribution of each fluid, particularly flow regions that have a high concentration of the dispersed phase. The propagation of regions of high density can be studied by examining the topology of isosurfaces of the density data. We present a topology-based approach to track the splitting and merging events of these regions using the Reeb graphs. Time is used as the third dimension in addition to two-dimensional (2D) point-based simulation data. Due to low time resolution of the input data set, a physics-based interpolation scheme is required in order to improve the accuracy of the proposed topology tracking method. The model used for interpolation produces a smooth time-dependent density field by applying Lagrangian-based advection to the given simulated point cloud data, conforming to the physical laws of flow evolution. Using the Reeb graph, the spatial and temporal locations of bifurcation and merging events can be readily identified supporting in-depth analysis of the extraction process.
    Computer Aided Geometric Design 07/2013; 30(6):557–566. DOI:10.1016/j.cagd.2012.03.019 · 1.64 Impact Factor
  • Harald Obermaier · Martin Hering-Bertram · Hans Hagen ·
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    ABSTRACT: The input–output behavior or flow transfer function of typical mixing processes is highly relevant to the analysis of the dynamic system and its mixing quality. We aim to visualize this behavior by extracting topologically relevant flow volumes from statistics accumulated during particle traversal of the flow field. To guarantee a sufficiently dense sampling of the flow field, we use adaptive time-surfaces for the computation of these trajectory statistics. The proposed volume extraction technique operates in parameter space of the computed time-surfaces and facilitates fast extraction of boundary geometry at different levels of detail. Our results visualize flow transfer functions in the form of volumes for extrema of different time-surface statistics and demonstrate their benefit for flow analysis.
    Computer Aided Geometric Design 07/2013; 30(6):567–576. DOI:10.1016/j.cagd.2012.03.018 · 1.64 Impact Factor

  • Eurographics Conference on Visualization (EuroVis 2013) Short Papers; 01/2013
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    ABSTRACT: A fundamental characteristic of fluid flow is that it causes mixing: introduce a dye into a flow, and it will disperse. Mixing can be used as a method to visualize and characterize flow. Because mixing is a process that occurs over time, it is a 4D problem that presents a challenge for computation, visualization, and analysis. Motivated by a mixing problem in geophysics, we introduce a combination of methods to analyze, transform, and finally visualize mixing in simulations of convection in a self-gravitating 3D spherical shell representing convection in the Earth's mantle. Geophysicists use tools such as the finite element model CitcomS to simulate convection, and introduce massless, passive tracers to model mixing. The output of geophysical flow simulation is hard to analyze for domain experts because of overall data size and complexity. In addition, information overload and occlusion are problems when visualizing a whole-earth model. To address the large size of the data, we rearrange the simulation data using intelligent indexing for fast file access and efficient caching. To address information overload and interpret mixing, we compute tracer concentration statistics, which are used to characterize mixing in mantle convection models. Our visualization uses a specially tailored version of Direct Volume Rendering. The most important adjustment is the use of constant opacity. Because of this special area of application, i. e. the rendering of a spherical shell, many computations for volume rendering can be optimized. These optimizations are essential to a smooth animation of the time-dependent simulation data. Our results show how our system can be used to quickly assess the simulation output and test hypotheses regarding Earth's mantle convection. The integrated processing pipeline helps geoscientists to focus on their main task of analyzing mantle homogenization.
    IEEE Transactions on Visualization and Computer Graphics 12/2012; 18(12):2198-2207. DOI:10.1109/TVCG.2012.283 · 2.17 Impact Factor
  • Harald Obermaier · Kenneth I. Joy ·
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    ABSTRACT: Integral flow surfaces constitute a widely used flow visualization tool due to their capability to convey important flow information such as fluid transport, mixing, and domain segmentation. Current flow surface rendering techniques limit their expressiveness, however, by focusing virtually exclusively on displacement visualization, visually neglecting the more complex notion of deformation such as shearing and stretching that is central to the field of continuum mechanics. To incorporate this information into the flow surface visualization and analysis process, we derive a metric tensor field that encodes local surface deformations as induced by the velocity gradient of the underlying flow field. We demonstrate how properties of the resulting metric tensor field are capable of enhancing present surface visualization and generation methods and develop novel surface querying, sampling, and visualization techniques. The provided results show how this step towards unifying classic flow visualization and more advanced concepts from continuum mechanics enables more detailed and improved flow analysis.
    IEEE Transactions on Visualization and Computer Graphics 12/2012; 18(12):2149-2158. DOI:10.1109/TVCG.2012.211 · 2.17 Impact Factor

  • IEEE Transactions on Visualization and Computer Graphics 10/2012; 18(12):2198-2207. · 2.17 Impact Factor
  • Harald Obermaier · Jan Mohring · Eduard Deines · Martin Hering-Bertram · Hans Hagen ·
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    ABSTRACT: Crease surfaces describe extremal structures of 3D scalar fields. We present a new region-growing-based approach to the meshless extraction of adaptive nonmanifold valley and ridge surfaces that overcomes limitations of previous approaches by decoupling point seeding and triangulation of the surface. Our method is capable of extracting valley surface skeletons as connected minimum structures. As our algorithm is inherently mesh-free and curvature adaptive, it is suitable for surface construction in fields with an arbitrary neighborhood structure. As an application for insightful visualization with valley surfaces, we choose a low frequency acoustics simulation. We use our valley surface construction approach to visualize the resulting complex-valued scalar pressure field for arbitrary frequencies to identify regions of sound cancellation. This provides an expressive visualization of the topology of wave node and antinode structures in simulated acoustics.
    02/2012; 18(2):270-82. DOI:10.1109/TVCG.2011.98
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    ABSTRACT: Moment tensors are indefinite tensors derived from seismic measurements and encode important information about earthquakes and surface displacement in the earth’s mantle. Appropriate analysis of scattered moment tensor fields requires multi-scale visualization to identify related seismic events. For this matter we provide a visualization of the tensor field at different scales based on multivariate tensor clustering. The resulting visualization allows interactive analysis of individual tensors, analysis of tensor groups and clustering behavior as well as examination of the complete tensor field. Our results show the benefit of multi-scale earthquake and displacement analysis and demonstrate the advantages over classic tensor visualization and univariate, static cluster visualization.
    Information Visualization 01/2012; 11(1):43-59. DOI:10.1177/1473871611425869 · 0.54 Impact Factor
  • Simon Schröder · Harald Obermaier · Christoph Garth · Kenneth I Joy ·
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    ABSTRACT: Feature-based visualization of flow fields has proven as an effective tool for flow analysis. While most flow visualization techniques operate on vector field data, our visualization techniques make use of a different simulation output: Particle Tracers. Our approach solely relies on integral lines that can be easily obtained from most simulation software. The task is the visualization of dense integral line data. We combine existing methods for streamline visualization, i. e. illumination, transparency, and halos, and add ambient occlusion for lines. But, this only solves one part of the problem: because of the high density of lines, visualization has to fight with occlusion, high frequency noise, and overlaps. As a solution we propose non-automated choices of transfer functions on curve properties that help highlighting important flow features like vortices or turbulent areas. These curve properties resemble some of the original flow properties. With the new combination of existing line drawing methods and the addition of ambient occlusion we improve the visualization of lines by adding better shape and depth cues. The intelligent use of transfer functions on curve properties reduces visual clutter and helps focusing on important features while still retaining context, as demonstrated in the examples given in this work.
    Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011; 01/2012
  • Harald Obermaier · Fang Chen · Hans Hagen · Kenneth I. Joy ·
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    ABSTRACT: Material interfaces and free surfaces are a topic of increasing interest in the field of computational fluid dynamics. In parts, reconstructed interfaces from such multi-fluid simulations behave like classic integral surfaces as known in the visualization community, while other regions of the surface undergo topological changes or behave orthogonally to what is expected by the underlying flow field. Thus, the analysis of the flow field in connection with material interface shape and topology is a challenging task. We develop a technique that facilitates visualization and analysis of such complex material interface behavior over time. For this matter, we track a surface parametrization of time-varying material interfaces and identify locations of interaction between material interfaces and fluid particles. Splatting and surface visualization techniques produce an intuitive representation of the derived interface stability. Our results demonstrate, how the interaction of the flow field with the material interface can be highlighted by appropriate extraction and visualization techniques and how the developed techniques can aid analysis of mixing and material interface consistency.
    01/2012; DOI:10.1109/PacificVis.2012.6183595
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    ABSTRACT: Understanding the complex behavior of mixing in the Earth's mantle remains a challenge in geoscience. One means to both interpret mantle flow models and enable comparisons with observations of the scale of mantle heterogeneity is by assessing the homogenization of passive tracers in models. Computer simulations of mantle mixing often yield both divergent and convergent regions which homogenize the mantle, as well as isolated pockets where almost no mixing occurs. Analyzing and understanding this complex behavior requires appropriate simulation and visualization tools. To reach this goal, we introduce new visualization techniques that allow geophysicists to effectively analyze this simulation data. Our visualization tool takes, as input, the velocity field and tracers generated by CitcomS, a well-established finite-element model of mantle convection in a spherical shell. By visualization of particle statistics, e.g. average traveled distance of tracers inside a pre-defined region, we provide a better understanding of homogenization in the mixing process. To reduce the amount of data generated by CitcomS, we only compute a few tracers during simulation time compared to the overall size of the data set. Statistics defined on this set of tracers allow an initial low detail analysis of the flow field while providing only limited preliminary insights into the data set. For further refinement in a specific region of interest we offer capabilities to locally add and integrate new tracers directly inside the visualization tool, facilitating interactive resolution control. This results in more detailed local statistics and is faster than resimulating tracers inside CitcomS by restarting the complete simulation run. Furthermore, we take well-known concepts from computer graphics to reduce visual clutter and help focus on a specific region of interest, such as slicing and volume rendering. Our results are suitable to gain a better understanding about homogenization of mixing processes in mantle convection. More specifically, we tested how homogeneous mixing between several mantle layers is. Further, by visualization of tracer paths some insight into the properties of the flow field is given. Using these techniques, geophysicists are able to test their hyphotheses regarding scales of mantle heterogeneity.
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    ABSTRACT: The evolution of strain and development of material anisotropy in models of the Earth’s mantle flow convey important information about how to interpret the geometric relationship between observation of seismic anisotropy and the actual mantle flow field. By combining feature extraction techniques such as path line integration and tensor accumulation, we compute time‐varying strain vector fields that build the foundation for a number of feature extraction and visualization techniques. The proposed field segmentation, clustering, histograms and multi‐volume visualization techniques facilitate an intuitive understanding of three‐dimensional strain in such flow fields, overcoming limitations of previous methods such as 2‐D line plots and slicing. We present applications of our approach to an artificial time varying flow data set and a real world example of stationary flow in a subduction zone and discuss the challenges of processing these geophysical data sets as well as the insights gained.
    Computer Graphics Forum 12/2011; 30(8):2301-2313. DOI:10.1111/j.1467-8659.2011.02036.x · 1.64 Impact Factor