30-Issue 3

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https://diglib.eg.org/handle/10.2312/163

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An Evaluation of Visualization Techniques to Illustrate Statistical Deformation Models
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Caban, Jesus J.; Rheingans, Penny; Yoo, T.; H. Hauser, H. Pfister, and J. J. van Wijk
As collections of 2D/3D images continue to grow, interest in effective ways to visualize and explore the statistical morphological properties of a group of images has surged. Recently, deformation models have emerged as simple methods to capture the variability and statistical properties of a collection of images. Such models have proven to be effective in tasks such as image classification, generation, registration, segmentation, and analysis of modes of variation. A crucial element missing from most statistical models has been an effective way to summarize and visualize the statistical morphological properties of a group of images. This paper evaluates different visualization techniques that can be extended and used to illustrate the information captured by such statistical models. First, four illustration techniques are described as methods to summarize the statistical morphological properties as captured by deformation models. Second, results of a user study conducted to compare the effectiveness of each visualization technique are presented. After comparing the performance of 40 subjects, we found that statistical annotation techniques present significant benefits when analyzing the structural properties of a group of images.
A Visual Analytics Approach for Peak-Preserving Prediction of Large Seasonal Time Series
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Hao, M. C.; Janetzko, H.; Mittelstädt, S.; Hill, W.; Dayal, U.; Keim, D. A.; Marwah, M.; Sharma, R. K.; H. Hauser, H. Pfister, and J. J. van Wijk
Time series prediction methods are used on a daily basis by analysts for making important decisions. Most of these methods use some variant of moving averages to reduce the number of data points before prediction. However, to reach a good prediction in certain applications (e.g., power consumption time series in data centers) it is important to preserve peaks and their patterns. In this paper, we introduce automated peak-preserving smoothing and prediction algorithms, enabling a reliable long term prediction for seasonal data, and combine them with an advanced visual interface: (1) using high resolution cell-based time series to explore seasonal patterns, (2) adding new visual interaction techniques (multi-scaling, slider, and brushing & linking) to incorporate human expert knowledge, and (3) providing both new visual accuracy color indicators for validating the predicted results and certainty bands communicating the uncertainty of the prediction. We have integrated these techniques into a wellfitted solution to support the prediction process, and applied and evaluated the approach to predict both power consumption and server utilization in data centers with 70-80% accuracy.
Anatomy-Guided Multi-Level Exploration of Blood Flow in Cerebral Aneurysms
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Neugebauer, Mathias; Janiga, Gabor; Beuing, Oliver; Skalej, Martin; Preim, Bernhard; H. Hauser, H. Pfister, and J. J. van Wijk
For cerebral aneurysms, the ostium, the area of inflow, is an important anatomic landmark, since it separates the pathological vessel deformation from the healthy parent vessel. A better understanding of the inflow characteristics, the flow inside the aneurysm and the overall change of pre- and post-aneurysm flow in the parent vessel provide insights for medical research and the development of new risk-reduced treatment options. We present an approach for a qualitative, visual flow exploration that incorporates the ostium and derived anatomical landmarks. It is divided into three scopes: a global scope for exploration of the in- and outflow, an ostium scope that provides characteristics of the flow profile close to the ostium and a local scope for a detailed exploration of the flow in the parent vessel and the aneurysm. The approach was applied to five representative datasets, including measured and simulated blood flow. Informal interviews with two board-certified radiologists confirmed the usefulness of the provided exploration tools and delivered input for the integration of the ostium-based flow analysis into the overall exploration workflow.
In-situ Sampling of a Large-Scale Particle Simulation for Interactive Visualization and Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Woodring, Jonathan; Ahrens, J.; Figg, J.; Wendelberger, J.; Habib, S.; Heitmann, K.; H. Hauser, H. Pfister, and J. J. van Wijk
We describe a simulation-time random sampling of a large-scale particle simulation, the RoadRunner Universe MC3 cosmological simulation, for interactive post-analysis and visualization. Simulation data generation rates will continue to be far greater than storage bandwidth rates by many orders of magnitude. This implies that only a very small fraction of data generated by a simulation can ever be stored and subsequently post-analyzed. The limiting factors in this situation are similar to the problem in many population surveys: there aren't enough human resources to query a large population. To cope with the lack of resources, statistical sampling techniques are used to create a representative data set of a large population. Following this analogy, we propose to store a simulationtime random sampling of the particle data for post-analysis, with level-of-detail organization, to cope with the bottlenecks. A sample is stored directly from the simulation in a level-of-detail format for post-visualization and analysis, which amortizes the cost of post-processing and reduces workflow time. Additionally by sampling during the simulation, we are able to analyze the entire particle population to record full population statistics and quantify sample error.
Energy-scale Aware Feature Extraction for Flow Visualization
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Pobitzer, A.; Tutkun, M.; Andreassen, Ø.; Fuchs, R.; Peikert, R.; Hauser, H.; H. Hauser, H. Pfister, and J. J. van Wijk
In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high-energy scales leads to a reduction of the flow field while retaining the underlying physical process. The presented method acknowledges the intrinsic structures of the flow according to its energy and therefore allows to focus on the energetically most interesting aspects of the flow. Our analysis shows that this approach can be used for methods based on both local feature extraction and particle integration and we provide a discussion of the error caused by the approximation. Finally, we illustrate the use of the proposed approach for both a local and a global feature detector and in the context of numerical flow simulations.
Progressive Splatting of Continuous Scatterplots and Parallel Coordinates
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Heinrich, Julian; Bachthaler, S.; Weiskopf, Daniel; H. Hauser, H. Pfister, and J. J. van Wijk
Continuous scatterplots and parallel coordinates are used to visualize multivariate data defined on a continuous domain. With the existing techniques, rendering such plots becomes prohibitively slow, especially for large scientific datasets. This paper presents a scalable and progressive rendering algorithm for continuous data plots that allows exploratory analysis of large datasets at interactive framerates. The algorithm employs splatting to produce a series of plots that are combined using alpha blending to achieve a progressively improving image. For each individual frame, splats are obtained by transforming Gaussian density kernels from the 3-D domain of the input dataset to the respective data domain. A closed-form analytic description of the resulting splat footprints is derived to allow pre-computation of splat textures for efficient GPU rendering. The plotting method is versatile because it supports arbitrary reconstruction or interpolation schemes for the input data and the splatting technique is scalable because it chooses splat samples independently from the size of the input dataset. Finally, the effectiveness of the method is compared to existing techniques regarding rendering performance and quality.
PaperVis: Literature Review Made Easy
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Chou, Jia -Kai; Yang, C. -K.; H. Hauser, H. Pfister, and J. J. van Wijk
Reviewing literatures for a certain research field is always important for academics. One could use Google-like information seeking tools, but oftentimes he/she would end up obtaining too many possibly related papers, as well as the papers in the associated citation network. During such a process, a user may easily get lost after following a few links for searching or cross-referencing. It is also difficult for the user to identify relevant/important papers from the resulting huge collection of papers. Our work, called PaperVis, endeavors to provide a user-friendly interface to help users quickly grasp the intrinsic complex citation-reference structures among a specific group of papers. We modify the existing Radial Space Filling (RSF) and Bullseye View techniques to arrange involved papers as a node-link graph that better depicts the relationships among them while saving the screen space at the same time. PaperVis applies visual cues to present node attributes and their transitions among interactions, and it categorizes papers into semantically meaningful hierarchies to facilitate ensuing literature exploration. We conduct experiments on the InfoVis 2004 Contest Dataset to demonstrate the effectiveness of PaperVis.
Topology-based Visualization of Transformation Pathways in Complex Chemical Systems
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Beketayev, Kenes; Weber, G. H.; Haranczyk, M.; Bremer, P.-T.; Hlawitschka, M.; Hamann, B.; H. Hauser, H. Pfister, and J. J. van Wijk
Studying transformation in a chemical system by considering its energy as a function of coordinates of the system's components provides insight and changes our understanding of this process. Currently, a lack of effective visualization techniques for high-dimensional energy functions limits chemists to plot energy with respect to one or two coordinates at a time. In some complex systems, developing a comprehensive understanding requires new visualization techniques that show relationships between all coordinates at the same time. We propose a new visualization technique that combines concepts from topological analysis, multi-dimensional scaling, and graph layout to enable the analysis of energy functions for a wide range of molecular structures. We demonstrate our technique by studying the energy function of a dimer of formic and acetic acids and a LTA zeolite structure, in which we consider diffusion of methane.
Semantic-Preserving Word Clouds by Seam Carving
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Wu, Yingcai; Provan, Thomas; Wei, Furu; Liu, Shixia; Ma, Kwan-Liu; H. Hauser, H. Pfister, and J. J. van Wijk
Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a document collection quickly, their ability to visually compare documents is limited. This paper introduces a new method to create semantic-preserving word clouds by leveraging tailored seam carving, a well-established content-aware image resizing operator. The method can optimize a word cloud layout by removing a left-to-right or top-to-bottom seam iteratively and gracefully from the layout. Each seam is a connected path of low energy regions determined by a Gaussian-based energy function. With seam carving, we can pack the word cloud compactly and effectively, while preserving its overall semantic structure. Furthermore, we design a set of interactive visualization techniques for the created word clouds to facilitate visual text analysis and comparison. Case studies are conducted to demonstrate the effectiveness and usefulness of our techniques.
Complete Tensor Field Topology on 2D Triangulated Manifolds embedded in 3D
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Auer, Cornelia; Hotz, Ingrid; H. Hauser, H. Pfister, and J. J. van Wijk
This paper is concerned with the extraction of the surface topology of tensor fields on 2D triangulated manifolds embedded in 3D. In scientific visualization topology is a meaningful instrument to get a hold on the structure of a given dataset. Due to the discontinuity of tensor fields on a piecewise planar domain, standard topology extraction methods result in an incomplete topological skeleton. In particular with regard to the high computational costs of the extraction this is not satisfactory. This paper provides a method for topology extraction of tensor fields that leads to complete results. The core idea is to include the locations of discontinuity into the topological analysis. For this purpose the model of continuous transition bridges is introduced, which allows to capture the entire topology on the discontinuous field. The proposed method is applied to piecewise linear three-dimensional tensor fields defined on the vertices of the triangulation and for piecewise constant two or three-dimensional tensor fields given per triangle, e.g. rate of strain tensors of piecewise linear flow fields.
Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Berger, Wolfgang; Piringer, H.; Filzmoser, P.; Gröller, Eduard; H. Hauser, H. Pfister, and J. J. van Wijk
Systems projecting a continuous n-dimensional parameter space to a continuous m-dimensional target space play an important role in science and engineering. If evaluating the system is expensive, however, an analysis is often limited to a small number of sample points. The main contribution of this paper is an interactive approach to enable a continuous analysis of a sampled parameter space with respect to multiple target values. We employ methods from statistical learning to predict results in real-time at any user-defined point and its neighborhood. In particular, we describe techniques to guide the user to potentially interesting parameter regions, and we visualize the inherent uncertainty of predictions in 2D scatterplots and parallel coordinates. An evaluation describes a realworld scenario in the application context of car engine design and reports feedback of domain experts. The results indicate that our approach is suitable to accelerate a local sensitivity analysis of multiple target dimensions, and to determine a sufficient local sampling density for interesting parameter regions.
A Shader Framework for Rapid Prototyping of GPU-Based Volume Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Rieder, Christian; Palmer, Stephan; Link, Florian; Hahn, Horst K.; H. Hauser, H. Pfister, and J. J. van Wijk
In this paper, we present a rapid prototyping framework for GPU-based volume rendering. Therefore, we propose a dynamic shader pipeline based on the SuperShader concept and illustrate the design decisions. Also, important requirements for the development of our system are presented. In our approach, we break down the rendering shader into areas containing code for different computations, which are defined as freely combinable, modularized shader blocks. Hence, high-level changes of the rendering configuration result in the implicit modification of the underlying shader pipeline. Furthermore, the prototyping system allows inserting custom shader code between shader blocks of the pipeline at run-time. A suitable user interface is available within the prototyping environment to allow intuitive modification of the shader pipeline. Thus, appropriate solutions for visualization problems can be interactively developed. We demonstrate the usage and the usefulness of our framework with implementations of dynamic rendering effects for medical applications.
WaveMap: Interactively Discovering Features From Protein Flexibility Matrices Using Wavelet-based Visual Analytics
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Barlowe, Scott; Liu, Yujie; Yang, Jing; Livesay, Dennis R.; Jacobs, Donald J.; Mottonen, James; Verma, Deeptak; H. Hauser, H. Pfister, and J. J. van Wijk
The knowledge gained from biology datasets can streamline and speed-up pharmaceutical development. However, computational models generate so much information regarding protein behavior that large-scale analysis by traditional methods is almost impossible. The volume of data produced makes the transition from data to knowledge difficult and hinders biomedical advances. In this work, we present a novel visual analytics approach named WaveMap for exploring data generated by a protein flexibility model. WaveMap integrates wavelet analysis, visualizations, and interactions to facilitate the browsing, feature identification, and comparison of protein attributes represented by two-dimensional plots. We have implemented a fully working prototype of WaveMap and illustrate its usefulness through expert evaluation and an example scenario.
Visualising Errors in Animal Pedigree Genotype Data
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Graham, Martin; Kennedy, Jessie; Paterson, Trevor; Law, Andy; H. Hauser, H. Pfister, and J. J. van Wijk
Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experimental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, introducing inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of genotype inheritance patterns in the context of the pedigree structure. Existing pedigree visualisations are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, table-based viewers of genotype marker data can highlight where errors become apparent but lack the functionality and interactive visual feedback to allow users to locate the origin of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why even-tually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the 'sandwich view', is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task.
Stable Morse Decompositions for Piecewise Constant Vector Fields on Surfaces
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Szymczak, Andrzej; H. Hauser, H. Pfister, and J. J. van Wijk
Numerical simulations and experimental observations are inherently imprecise. Therefore, most vector fields of interest in scientific visualization are known only up to an error. In such cases, some topological features, especially those not stable enough, may be artifacts of the imprecision of the input. This paper introduces a technique to compute topological features of user-prescribed stability with respect to perturbation of the input vector field. In order to make our approach simple and efficient, we develop our algorithms for the case of piecewise constant (PC) vector fields. Our approach is based on a super-transition graph, a common graph representation of all PC vector fields whose vector value in a mesh triangle is contained in a convex set of vectors associated with that triangle. The graph is used to compute a Morse decomposition that is coarse enough to be correct for all vector fields satisfying the constraint. Apart from computing stable Morse decompositions, our technique can also be used to estimate the stability of Morse sets with respect to perturbation of the vector field or to compute topological features of continuous vector fields using the PC framework.
Curve Density Estimates
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Lampe, Ove Daae; Hauser, Helwig; H. Hauser, H. Pfister, and J. J. van Wijk
In this work, we present a technique based on kernel density estimation for rendering smooth curves. With this approach, we produce uncluttered and expressive pictures, revealing frequency information about one, or, multiple curves, independent of the level of detail in the data, the zoom level, and the screen resolution. With this technique the visual representation scales seamlessly from an exact line drawing, (for low-frequency/low-complexity curves) to a probability density estimate for more intricate situations. This scale-independence facilitates displays based on non-linear time, enabling high-resolution accuracy of recent values, accompanied by long historical series for context. We demonstrate the functionality of this approach in the context of prediction scenarios and in the context of streaming data.
Visualizing High-Dimensional Structures by Dimension Ordering and Filtering using Subspace Analysis
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Ferdosi, Bilkis J.; H. Hauser, H. Pfister, and J. J. van Wijk
High-dimensional data visualization is receiving increasing interest because of the growing abundance of highdimensional datasets. To understand such datasets, visualization of the structures present in the data, such as clusters, can be an invaluable tool. Structures may be present in the full high-dimensional space, as well as in its subspaces. Two widely used methods to visualize high-dimensional data are the scatter plot matrix (SPM) and the parallel coordinate plot (PCP). SPM allows a quick overview of the structures present in pairwise combinations of dimensions. On the other hand, PCP has the potential to visualize not only bi-dimensional structures but also higher dimensional ones. A problem with SPM is that it suffers from crowding and clutter which makes interpretation hard. Approaches to reduce clutter are available in the literature, based on changing the order of the dimensions. However, usually this reordering has a high computational complexity. For effective visualization of high-dimensional structures, also PCP requires a proper ordering of the dimensions. In this paper, we propose methods for reordering dimensions in PCP in such a way that high-dimensional structures (if present) become easier to perceive. We also present a method for dimension reordering in SPM which yields results that are comparable to those of existing approaches, but at a much lower computational cost. Our approach is based on finding relevant subspaces for clustering using a quality criterion and cluster information. The quality computation and cluster detection are done in image space, using connected morphological operators. We demonstrate the potential of our approach for synthetic and astronomical datasets, and show that our method compares favorably with a number of existing approaches.
Lagrangian Coherent Structures with Guaranteed Material Separation
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Germer, Tobias; Otto, Mathias; Peikert, R.; Theisel, H.; H. Hauser, H. Pfister, and J. J. van Wijk
Given an unsteady flow field, one common way to compute Lagrangian Coherent Structures (LCS) is to extract extremal structures of the Finite Time Lyapunov Exponent (FTLE). Experience has shown that the resulting structures are often close to material structures (i.e., material lines or material surfaces). Moreover, it has been proven that for an integration time converging to infinity, they converge to exact material structures. However, due to the finite integration time in FTLE, they are generally not exact material structures. In this paper we introduce a modification of the FTLE method which is guaranteed to produce separating material structures as features of a scalar field. We achieve this by incorporating the complete available integration time both in forward and backward direction, and by choosing an appropriate definition for separating structures. We apply our method to two test data sets and show the differences to classical FTLE.
Visual Exploration of Time-Series Data with Shape Space Projections
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Ward, Matthew O.; Guo, Zhenyu; H. Hauser, H. Pfister, and J. J. van Wijk
Time-series data is a common target for visual analytics, as they appear in a wide range of application domains. Typical tasks in analyzing time-series data include identifying cyclic behavior, outliers, trends, and periods of time that share distinctive shape characteristics. Many methods for visualizing time series data exist, generally mapping the data values to positions or colors. While each can be used to perform a subset of the above tasks, none to date is a complete solution. In this paper we present a novel approach to time-series data visualization, namely creating multivariate data records out of short subsequences of the data and then using multivariate visualization methods to display and explore the data in the resulting shape space. We borrow ideas from text analysis, where the use of N-grams is a common approach to decomposing and processing unstructured text. By mapping each temporal N-gram to a glyph, and then positioning the glyphs via PCA (basically a projection in shape space), many different kinds of patterns in the sequence can be readily identified. Interactive selection via brushing, in conjunction with linking to other visualizations, provides a wide range of tools for exploring the data. We validate the usefulness of this approach with examples from several application domains and tasks, comparing our methods with traditional time-series visualizations.
Depth of Field Effects for Interactive Direct Volume Rendering
(The Eurographics Association and Blackwell Publishing Ltd., 2011) Schott, Mathias; Grosset, A. V. Pascal; Martin, Tobias; Pegoraro, Vincent; Smith, Sean T.; Hansen, Charles D.; H. Hauser, H. Pfister, and J. J. van Wijk
In this paper, a method for interactive direct volume rendering is proposed for computing depth of field effects, which previously were shown to aid observers in depth and size perception of synthetically generated images. The presented technique extends those benefits to volume rendering visualizations of 3D scalar fields from CT/MRI scanners or numerical simulations. It is based on incremental filtering and as such does not depend on any precomputation, thus allowing interactive explorations of volumetric data sets via on-the-fly editing of the shading model parameters or (multi-dimensional) transfer functions.

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