34-Issue 3

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https://diglib.eg.org/handle/10.2312/12458

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Efficient Local Histogram Searching via Bitmap Indexing
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Wei, Tzu-Hsuan; Chen, Chun-Ming; Biswas, Ayan; H. Carr, K.-L. Ma, and G. Santucci
Representing features by local histograms is a proven technique in several volume analysis and visualization applications including feature tracking and transfer function design. The efficiency of these applications, however, is hampered by the high computational complexity of local histogram computation and matching. In this paper, we propose a novel algorithm to accelerate local histogram search by leveraging bitmap indexing. Our method avoids exhaustive searching of all voxels in the spatial domain by examining only the voxels whose values fall within the value range of user-defined local features and their neighborhood. Based on the idea that the value range of local features is in general much smaller than the dynamic range of the entire dataset, we propose a local voting scheme to construct the local histograms so that only a small number of voxels need to be examined. Experimental results show that our method can reduce much computational workload compared to the conventional approaches. To demonstrate the utility of our method, an interactive interface was developed to assist users in defining target features as local histograms and identify the locations of these features in the dataset.
Visual Assessment of Alleged Plagiarism Cases
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Riehmann, Patrick; Potthast, Martin; Stein, Benno; Froehlich, Bernd; H. Carr, K.-L. Ma, and G. Santucci
We developed a visual analysis tool to support the verification, assessment, and presentation of alleged cases of plagiarism. The analysis of a suspicious document typically results in a compilation of categorized ''finding spots''. The categorization reveals the way in which the suspicious text fragment was created from the source, e.g. by obfuscation, translation, or by shake and paste. We provide a three-level approach for exploring the finding spots in context. The overview shows the relationship of the entire suspicious document to the set of source documents. A glyph-based view reveals the structural and textual differences and similarities of a set of finding spots and their corresponding source text fragments. For further analysis and editing of the finding spot's assessment, the actual text fragments can be embedded side-by-side in the diffline view. The different views are tied together by versatile navigation and selection operations. Our expert reviewers confirm that our tool provides a significant improvement over existing static visualizations for assessing plagiarism cases.
Finite-Time Mass Separation for Comparative Visualizations of Inertial Particles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Günther, Tobias; Theisel, Holger; H. Carr, K.-L. Ma, and G. Santucci
The visual analysis of flows with inertial particle trajectories is a challenging problem because time-dependent particle trajectories additionally depend on mass, which gives rise to an infinite number of possible trajectories passing through every point in space-time. This paper presents an approach to a comparative visualization of the inertial particles' separation behavior. For this, we define the Finite-Time Mass Separation (FTMS), a scalar field that measures at each point in the domain how quickly inertial particles separate that were released from the same location but with slightly different mass. Extracting and visualizing the mass that induces the largest separation provides a simplified view on the critical masses. By using complementary coordinated views, we additionally visualize corresponding inertial particle trajectories in space-time by integral curves and surfaces. For a quantitative analysis, we plot Euclidean and arc length-based distances to a reference particle over time, which allows to observe the temporal evolution of separation events. We demonstrate our approach on a number of analytic and one real-world unsteady 2D field.
Adaptive Recommendations for Enhanced Non-linear Exploration of Annotated 3D Objects
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Rodriguez, Marcos Balsa; Agus, Marco; Marton, Fabio; Gobbetti, Enrico; H. Carr, K.-L. Ma, and G. Santucci
We introduce a novel approach for letting casual viewers explore detailed 3D models integrated with structured spatially associated descriptive information organized in a graph. Each node associates a subset of the 3D surface seen from a particular viewpoint to the related descriptive annotation, together with its author-defined importance. Graph edges describe, instead, the strength of the dependency relation between information nodes, allowing content authors to describe the preferred order of presentation of information. At run-time, users navigate inside the 3D scene using a camera controller, while adaptively receiving unobtrusive guidance towards interesting viewpoints and history- and location-dependent suggestions on important information, which is adaptively presented using 2D overlays displayed over the 3D scene. The capabilities of our approach are demonstrated in a real-world cultural heritage application involving the public presentation of sculptural complex on a large projection-based display. A user study has been performed in order to validate our approach.
Visual Analytics for Correlation-Based Comparison of Time Series Ensembles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Köthur, Patrick; Witt, Carl; Sips, Mike; Marwan, Norbert; Schinkel, Stefan; Dransch, Doris; H. Carr, K.-L. Ma, and G. Santucci
An established approach to studying interrelations between two non-stationary time series is to compute the 'windowed' cross-correlation (WCC). The time series are divided into intervals and the cross-correlation between corresponding intervals is calculated. The outcome is a matrix that describes the correlation between two time series for different intervals and varying time lags. This important technique can only be used to compare two single time series. However, many applications require the comparison of ensembles of time series. Therefore, we propose a visual analytics approach that extends the WCC to support a correlation-based comparison of two ensembles of time series. We compute the pairwise WCC between all time series from the two ensembles, which results in hundreds of thousands of WCC matrices. Statistical measures are used to derive a concise description of the time-varying correlations between the ensembles as well as the uncertainty of the correlation values. We further introduce a visually scalable overview visualization of the computed correlation and uncertainty information. These components are combined with multiple linked views into a visual analytics system to support configuration of the WCC as well as detailed analysis of correlation patterns between two ensembles. Two use cases from very different domains, cognitive science and paleoclimatology, demonstrate the utility of our approach.
Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Bach, Benjamin; Henry-Riche, Nathalie; Dwyer, Tim; Madhyastha, Tara; Fekete, Jean-Daniel; Grabowski, Thomas; H. Carr, K.-L. Ma, and G. Santucci
We introduce MultiPiles, a visualization to explore time-series of dense, weighted networks. MultiPiles is based on the physical analogy of piling adjacency matrices, each one representing a single temporal snapshot. Common interfaces for visualizing dynamic networks use techniques such as: flipping/animation; small multiples; or summary views in isolation. Our proposed 'piling' metaphor presents a hybrid of these techniques, leveraging each one's advantages, as well as offering the ability to scale to networks with hundreds of temporal snapshots. While the MultiPiles technique is applicable to many domains, our prototype was initially designed to help neuroscientists investigate changes in brain connectivity networks over several hundred snapshots. The piling metaphor and associated interaction and visual encodings allowed neuroscientists to explore their data, prior to a statistical analysis. They detected high-level temporal patterns in individual networks and this helped them to formulate and reject several hypotheses.
Visualization of Particle-based Data with Transparency and Ambient Occlusion
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Staib, Joachim; Grottel, Sebastian; Gumhold, Stefan; H. Carr, K.-L. Ma, and G. Santucci
Particle-based simulation techniques, like the discrete element method or molecular dynamics, are widely used in many research fields. In real-time explorative visualization it is common to render the resulting data using opaque spherical glyphs with local lighting only. Due to massive overlaps, however, inner structures of the data are often occluded rendering visual analysis impossible. Furthermore, local lighting is not sufficient as several important features like complex shapes, holes, rifts or filaments cannot be perceived well. To address both problems we present a new technique that jointly supports transparency and ambient occlusion in a consistent illumination model. Our approach is based on the emission-absorption model of volume rendering. We provide analytic solutions to the volume rendering integral for several density distributions within a spherical glyph. Compared to constant transparency our approach preserves the three-dimensional impression of the glyphs much better. We approximate ambient illumination with a fast hierarchical voxel cone-tracing approach, which builds on a new real-time voxelization of the particle data. Our implementation achieves interactive frame rates for millions of static or dynamic particles without any preprocessing. We illustrate the merits of our method on real-world data sets gaining several new insights.
Photoelasticity Raycasting
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Bußler, Michael; Ertl, Thomas; Sadlo, Filip; H. Carr, K.-L. Ma, and G. Santucci
We present a novel physically-based method to visualize stress tensor fields. By incorporating photoelasticity into traditional raycasting and extending it with reflection and refraction, taking into account polarization, we obtain the virtual counterpart to traditional experimental polariscopes. This allows us to provide photoelastic analysis of stress tensor fields in arbitrary domains. In our model, the optical material properties, such as stress-optic coefficient and refractive index, can either be chosen in compliance with the subject under investigation, or, in case of stress problems that do not model optical properties or that are not transparent, be chosen according to known or even new transparent materials. This enables direct application of established polariscope methodology together with respective interpretation. Using a GPU-based implementation, we compare our technique to experimental data, and demonstrate its utility with several simulated datasets.
A Multi-task Comparative Study on Scatter Plots and Parallel Coordinates Plots
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kanjanabose, Rassadarie; Abdul-Rahman, Alfie; Chen, Min; H. Carr, K.-L. Ma, and G. Santucci
Previous empirical studies for comparing parallel coordinates plots and scatter plots showed some uncertainty about their relative merits. Some of these studies focused on the task of value retrieval, where visualization usually has a limited advantage over reading data directly. In this paper, we report an empirical study that compares user performance, in terms of accuracy and response time, in the context of four different visualization tasks, namely value retrieval, clustering, outlier detection, and change detection. In order to evaluate the relative merits of the two types of plots with a common base line (i.e., reading data directly), we included three forms of stimuli, data tables, scatter plots, and parallel coordinate plots. Our results show that data tables are better suited for the value retrieval task, while parallel coordinates plots generally outperform the two other visual representations in three other tasks. Subjective feedbacks from the users are also consistent with the quantitative analyses. As visualization is commonly used for aiding multiple observational and analytical tasks, our results provided new evidence to support the prevailing enthusiasm for parallel coordinates plots in the field of visualization.
Learning Probabilistic Transfer Functions: A Comparative Study of Classifiers
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Soundararajan, Krishna Prasad; Schultz, Thomas; H. Carr, K.-L. Ma, and G. Santucci
Complex volume rendering tasks require high-dimensional transfer functions, which are notoriously difficult to design. One solution to this is to learn transfer functions from scribbles that the user places in the volumetric domain in an intuitive and natural manner. In this paper, we explicitly model and visualize the uncertainty in the resulting classification. To this end, we extend a previous intelligent system approach to volume rendering, and we systematically compare five supervised classification techniques - Gaussian Naive Bayes, k Nearest Neighbor, Support Vector Machines, Neural Networks, and Random Forests - with respect to probabilistic classification, support for multiple materials, interactive performance, robustness to unreliable input, and easy parameter tuning, which we identify as key requirements for the successful use in this application. Based on theoretical considerations, as well as quantitative and visual results on volume datasets from different sources and modalities, we conclude that, while no single classifier can be expected to outperform all others under all circumstances, random forests are a useful off-the-shelf technique that provides fast, easy, robust and accurate results in many scenarios.
Visual Analysis of Proximal Temporal Relationships of Social and Communicative Behaviors
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Han, Yi; Rozga, Agata; Dimitrova, Nevena; Abowd, Gregory D.; Stasko, John; H. Carr, K.-L. Ma, and G. Santucci
Developmental psychology researchers examine the temporal relationships of social and communicative behaviors, such as how a child responds to a name call, to understand early typical and atypical development and to discover early signs of autism and developmental delay. These related behaviors occur together or within close temporal proximity, forming unique patterns and relationships of interest. However, the task of finding these early signs, which are in the form of atypical behavioral patterns, becomes more challenging when behaviors of multiple children at different ages need to be compared with each other in search of generalizable patterns. The ability to visually explore the temporal relationships of behaviors, including flexible redefinition of closeness, over multiple social interaction sessions with children of different ages, can make such knowledge extraction easier. We have designed a visualization tool called TipoVis that helps psychology researchers visually explore the temporal patterns of social and communicative behaviors. We present two case studies to show how TipoVis helped two researchers derive new understandings of their data.
Visualization of Object-Centered Vulnerability to Possible Flood Hazards
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cornel, Daniel; Konev, Artem; Sadransky, Bernhard; Horvath, Zsolt; Gröller, Eduard; Waser, Jürgen; H. Carr, K.-L. Ma, and G. Santucci
As flood events tend to happen more frequently, there is a growing demand for understanding the vulnerability of infrastructure to flood-related hazards. Such demand exists both for flood management personnel and the general public. Modern software tools are capable of generating uncertainty-aware flood predictions. However, the information addressing individual objects is incomplete, scattered, and hard to extract. In this paper, we address vulnerability to flood-related hazards focusing on a specific building. Our approach is based on the automatic extraction of relevant information from a large collection of pre-simulated flooding events, called a scenario pool. From this pool, we generate uncertainty-aware visualizations conveying the vulnerability of the building of interest to different kinds of flooding events. On the one hand, we display the adverse effects of the disaster on a detailed level, ranging from damage inflicted on the building facades or cellars to the accessibility of the important infrastructure in the vicinity. On the other hand, we provide visual indications of the events to which the building of interest is vulnerable in particular. Our visual encodings are displayed in the context of urban 3D renderings to establish an intuitive relation between geospatial and abstract information. We combine all the visualizations in a lightweight interface that enables the user to study the impacts and vulnerabilities of interest and explore the scenarios of choice. We evaluate our solution with experts involved in flood management and public communication.
Vector Field Visualization of Advective-Diffusive Flows
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Hochstetter, Hendrik; Wurm, Maximilian; Kolb, Andreas; H. Carr, K.-L. Ma, and G. Santucci
We propose a framework for unified visualization of advective and diffusive concentration fluxes, which play a key role in many phenomena like, e.g. Marangoni convection and microscopic mixing. The main idea is the decomposition of fluxes into their concentration and velocity parts. Using this flux decomposition, we are able to convey advective-diffusive concentration transport using integral lines. In order to visualize superimposed flux effects, we introduce a new graphical metaphor, the stream feather, which adds extensions to stream tubes pointing in the directions of deviating fluxes. The resulting unified visualization of macroscopic advection and microscopic diffusion allows for deeper insight into complex flow scenarios that cannot be achieved with current volume and surface rendering techniques alone. Our approach for flux decomposition and visualization of advective-diffusive flows can be applied to any kind of (simulation) data if velocity and concentration data are available. We demonstrate that our techniques can easily be integrated into Smoothed Particle Hydrodynamics (SPH) based simulations.
Dual Adjacency Matrix: Exploring Link Groups in Dense Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Dinkla, Kasper; Henry-Riche, Nathalie; Westenberg, Michel A.; H. Carr, K.-L. Ma, and G. Santucci
Node grouping is a common way of adding structure and information to networks that aids their interpretation. However, certain networks benefit from the grouping of links instead of nodes. Link communities, for example, are a form of link groups that describe high-quality overlapping node communities. There is a conceptual gap between node groups and link groups that poses an interesting visualization challenge. We introduce the Dual Adjacency Matrix to bridge this gap. This matrix combines node and link group techniques via a generalization that also enables it to be coordinated with a node-link-contour diagram. These methods have been implemented in a prototype that we evaluated with an information scientist and neuroscientist via interviews and prototype walk- throughs. We demonstrate this prototype with the analysis of a trade network and an fMRI correlation network.
Rationale Visualization for Safety and Security
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Scheepens, Roeland; Michels, Steffen; Wetering, Huub van de; Wijk, Jarke J. van; H. Carr, K.-L. Ma, and G. Santucci
In safety and security domains where objects of interest (OOI), such as people, vessels, or transactions, are continuously monitored, automated reasoning is required due to their sheer number and volume of information. We present a method to visually explain the rationale of a reasoning engine that raises an alarm if a certain situation is reached. Based both on evidence from heterogeneous and possibly unreliable sources, and on a domain specific reasoning structure, this engine concludes with a certain probability that, e.g., the OOI is suspected of smuggling. To support decision making, we visualize the rationale, an abstraction of the complicated reasoning structure. The evidence is displayed in a color-coded matrix that easily reveals if and where observations contradict. In it, domain and operational experts can quickly understand and find complicated patterns and relate them to real-world situations. Also, two groups of these experts evaluate our system through maritime use cases based on real data.
Visualnostics: Visual Guidance Pictograms for Analyzing Projections of High-dimensional Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Lehmann, Dirk J.; Kemmler, Fritz; Zhyhalava, Tatsiana; Kirschke, Marco; Theisel, Holger; H. Carr, K.-L. Ma, and G. Santucci
The visual analysis of multivariate projections is a challenging task, because complex visual structures occur. This causes fatigue or misinterpretations, which distorts the analysis. In fact, the same projection can lead to different analysis results. We provide visual guidance pictograms to improve objectivity of the visual search. A visual guidance pictogram is an iconic visual density map encoding the visual structure of certain data properties. By using them to guide the analysis, structures in the projection can be better understood and mentally linked to properties in the data. We introduce a systematic scheme for designing such pictograms and provide a set of pictograms for standard visual tasks, such as correlation and distribution analysis, for standard projections like scatterplots, RadVis, and Star Coordinates. We conduct a study that compares the visual analysis of real data with and without the support of guidance pictograms. Our tests show that the training effort for a visual search can be decreased and the analysis bias can be reduced by supporting the user's visual search with guidance pictograms.
Mosaic Drawings and Cartograms
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cano, Rafael G.; Buchin, Kevin; Castermans, Thom; Pieterse, Astrid; Sonke, Willem; Speckmann, Bettina; H. Carr, K.-L. Ma, and G. Santucci
Cartograms visualize quantitative data about a set of regions such as countries or states. There are several different types of cartograms and - for some - algorithms to automatically construct them exist. We focus on mosaic cartograms: cartograms that use multiples of simple tiles - usually squares or hexagons - to represent regions. Mosaic cartograms communicate well data that consist of, or can be cast into, small integer units (for example, electorial college votes). In addition, they allow users to accurately compare regions and can often maintain a (schematized) version of the input regions' shapes. We propose the first fully automated method to construct mosaic cartograms. To do so, we first introduce mosaic drawings of triangulated planar graphs. We then show how to modify mosaic drawings into mosaic cartograms with low cartographic error while maintaining correct adjacencies between regions. We validate our approach experimentally and compare to other cartogram methods.
A Novel Framework for Visual Detection and Exploration of Performance Bottlenecks in Organic Photovoltaic Solar Cell Materials
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Aboulhassan, Amal; Baum, Daniel; Wodo, Olga; Ganapathysubramanian, Baskar; Amassian, Aram; Hadwiger, Markus; H. Carr, K.-L. Ma, and G. Santucci
Current characterization methods of the so-called Bulk Heterojunction (BHJ), which is the main material of Organic Photovoltaic (OPV) solar cells, are limited to the analysis of global fabrication parameters. This reduces the efficiency of the BHJ design process, since it misses critical information about the local performance bottlenecks in the morphology of the material. In this paper, we propose a novel framework that fills this gap through visual characterization and exploration of local structure-performance correlations. We also propose a formula that correlates the structural features with the performance bottlenecks. Since research into BHJ materials is highly multidisciplinary, our framework enables a visual feedback strategy that allows scientists to build intuition about the best choices of fabrication parameters. We evaluate the usefulness of our proposed system by obtaining new BHJ characterizations. Furthermore, we show that our approach could substantially reduce the turnaround time.
Visual Analytics for the Exploration of Tumor Tissue Characterization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Raidou, Renata Georgia; Heide, Uulke A. van der; Dinh, Cuong Viet; Ghobadi, Ghazaleh; Kallehauge, Jesper Follsted; Breeuwer, Marcel; Vilanova, Anna; H. Carr, K.-L. Ma, and G. Santucci
Tumors are heterogeneous tissues consisting of multiple regions with distinct characteristics. Characterization of these intra-tumor regions can improve patient diagnosis and enable a better targeted treatment. Ideally, tissue characterization could be performed non-invasively, using medical imaging data, to derive per voxel a number of features, indicative of tissue properties. However, the high dimensionality and complexity of this imaging-derived feature space is prohibiting for easy exploration and analysis - especially when clinical researchers require to associate observations from the feature space to other reference data, e.g., features derived from histopathological data. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visually comparing them and mentally reconstructing their relationships. This is a time consuming and tedious process, from which it is difficult to obtain the required insight. We propose a visual tool for: (1) easy exploration and visual analysis of the feature space of imaging-derived tissue characteristics and (2) knowledge discovery and hypothesis generation and confirmation, with respect to reference data used in clinical research. We employ, as central view, a 2D embedding of the imaging-derived features. Multiple linked interactive views provide functionality for the exploration and analysis of the local structure of the feature space, enabling linking to patient anatomy and clinical reference data. We performed an initial evaluation with ten clinical researchers. All participants agreed that, unlike current practice, the proposed visual tool enables them to identify, explore and analyze heterogeneous intra-tumor regions and particularly, to generate and confirm hypotheses, with respect to clinical reference data.
Map-based Visualizations Increase Recall Accuracy of Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Saket, Bahador; Scheidegger, Carlos; Kobourov, Stephen G.; Börner, Katy; H. Carr, K.-L. Ma, and G. Santucci
We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the results of an evaluation comparing the memorability of two different visualizations of the same relational data: node-link diagrams and map-based visualization. We find significant differences in the accuracy of the tasks performed, and these differences persist days after the original exposure to the visualizations. Specifically, participants in the study recalled the data better when exposed to map-based visualizations as opposed to node-link diagrams. We discuss the scope of the study and its limitations, possible implications, and future directions.

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