DevLan/vispubs huggingface dataset:
Fused Multi-Volume DVR using Binary Space Partitioning
Authors: Stefan Lindholm, Patric Ljung, Markus Hadwiger, Anders Ynnerman
Published at EuroVis, 2009

Multiple‐volume visualization is a growing field in medical imaging providing simultaneous exploration of volumes acquired from varying modalities. However, high complexity results in an increased strain on performance compared to single volume rendering as scenes may consist of volumes with arbitrary orientations and rendering is performed with varying sample densities. Expensive image order techniques such as depth peeling have previously been used to perform the necessary calculations. In this work we present a view‐independent region based scene description for multi‐volume pipelines. Using Binary Space Partitioning we are able to create a simple interface providing all required information for advanced multi‐volume renderings while introducing a minimal overhead for scenes with few volumes. The modularity of our solution is demonstrated by the use of visual development and performance is documented with benchmarks and real‐time simulations.
Hierarchical Vortex Regions in Swirling Flow
Authors: Christoph Petz, Jens Kasten, Steffen Prohaska, Hans-Christian Hege
Published at EuroVis, 2009

We propose a new criterion to characterize hierarchical two‐dimensional vortex regions induced by swirling motion. Central to the definition are closed loops that intersect the flow field at a constant angle. The union of loops belonging to the same area of swirling motion defines a vortex region. These regions are disjunct but may be nested, thus introducing a spatial hierarchy of vortex regions. We present a parameter free algorithm for the identification of these regions. Since they are not restricted to star‐ or convex‐shaped geometries, we are able to identify also intricate regions, e.g., of elongated vortices. Computing an integrated value for each loop and mapping these values to a vortex region, introduces new ways for visualizing or filtering the vortex regions. Exemplary, an application based on the Rankine vortex model is presented. We apply our method to several CFD datasets and compare our results to existing approaches.
High-Quality Volumetric Reconstruction on Optimal Lattices for Computed Tomography
Authors: Bernhard Finkbeiner, Usman R. Alim, Dimitri Van De Ville, Torsten Möller
Published at EuroVis, 2009

Within the context of emission tomography, we study volumetric reconstruction methods based on the Expectation Maximization (EM) algorithm. We show, for the first time, the equivalence of the standard implementation of the EM‐based reconstruction with an implementation based on hardware‐accelerated volume rendering for nearest‐neighbor (NN) interpolation. This equivalence suggests that higher‐order kernels should be used with caution and do not necessarily lead to better performance. We also show that the EM algorithm can easily be adapted for different lattices, the body‐centered cubic (BCC) one in particular. For validation purposes, we use the 3D version of the Shepp‐Logan synthetic phantom, for which we derive closed‐form analytical expressions of the projection data. The experimental results show the theoretically‐predicted optimality of NN interpolation in combination with the EM algorithm, for both the noiseless and the noisy case. Moreover, reconstruction on the BCC lattice leads to superior accuracy, more compact data representation, and better noise reduction compared to the Cartesian one. Finally, we show the usefulness of the proposed method for optical projection tomography of a mouse embryo.
Illuminated 3D Scatterplots
Authors: Harald Sanftmann, Daniel Weiskopf
Published at EuroVis, 2009

In contrast to 2D scatterplots, the existing 3D variants have the advantage of showing one additional data dimension, but suffer from inadequate spatial and shape perception and therefore are not well suited to display structures of the underlying data. We improve shape perception by applying a new illumination technique to the pointcloud representation of 3D scatterplots. Points are classified as locally linear, planar, and volumetric structures—according to the eigenvalues of the inverse distance‐weighted covariance matrix at each data element. Based on this classification, different lighting models are applied: codimension‐2 illumination, surface illumination, and emissive volumetric illumination. Our technique lends itself to efficient GPU point rendering and can be combined with existing methods like semi‐transparent rendering, halos, and depth or attribute based color coding. The user can interactively navigate in the dataset and manipulate the classification and other visualization parameters. We demonstrate our visualization technique by showing examples of multi‐dimensional data and of generic pointcloud data.
Instant Volume Visualization using Maximum Intensity Difference Accumulation
Authors: Stefan Bruckner, M. Eduard Gröller
Published at EuroVis, 2009

It has long been recognized that transfer function setup for Direct Volume Rendering (DVR) is crucial to its usability. However, the task of finding an appropriate transfer function is complex and time‐consuming even for experts. Thus, in many practical applications simpler techniques which do not rely on complex transfer functions are employed. One common example is Maximum Intensity Projection (MIP) which depicts the maximum value along each viewing ray. In this paper, we introduce Maximum Intensity Difference Accumulation (MIDA), a new approach which combines the advantages of DVR and MIP. Like MIP, MIDA exploits common data characteristics and hence does not require complex transfer functions to generate good visualization results. It does, however, feature occlusion and shape cues similar to DVR. Furthermore, we show that MIDA – in addition to being a useful technique in its own right – can be used to smoothly transition between DVR and MIP in an intuitive manner. MIDA can be easily implemented using volume raycasting and achieves real‐time performance on current graphics hardware.
Interactive Visualization of Function Fields by Range-Space Segmentation
Authors: John C. Anderson, Luke J. Gosink, Mark A. Duchaineau, Kenneth I. Joy
Published at EuroVis, 2009

We present a dimension reduction and feature extraction method for the visualization and analysis of function field data. Function fields are a class of high‐dimensional, multi‐variate data in which data samples are one‐dimensional scalar functions. Our approach focuses upon the creation of high‐dimensional range‐space segmentations, from which we can generate meaningful visualizations and extract separating surfaces between features. We demonstrate our approach on high‐dimensional spectral imagery, and particulate pollution data from air quality simulations.
iPCA: An Interactive System for PCA-based Visual Analytics
Authors: Dong Hyun Jeong, Caroline Ziemkiewicz, Brian D. Fisher, William Ribarsky, Remco Chang
Published at EuroVis, 2009

Principle Component Analysis (PCA) is a widely used mathematical technique in many fields for factor and trend analysis, dimension reduction, etc. However, it is often considered to be a “black box” operation whose results are difficult to interpret and sometimes counter‐intuitive to the user. In order to assist the user in better understanding and utilizing PCA, we have developed a system that visualizes the results of principal component analysis using multiple coordinated views and a rich set of user interactions. Our design philosophy is to support analysis of multivariate datasets through extensive interaction with the PCA output. To demonstrate the usefulness of our system, we performed a comparative user study with a known commercial system, SAS/INSIGHT's Interactive Data Exploration. Participants in our study solved a number of high‐level analysis tasks with each interface and rated the systems on ease of learning and usefulness. Based on the participants' accuracy, speed, and qualitative feedback, we observe that our system helps users to better understand relationships between the data and the calculated eigenspace, which allows the participants to more accurately analyze the data. User feedback suggests that the interactivity and transparency of our system are the key strengths of our approach.
Lifted Domain Coloring
Authors: Konstantin Poelke, Konrad Polthier
Published at EuroVis, 2009

Complex‐valued functions are fundamental objects in complex analysis, algebra, differential geometry and in many other areas such as numerical mathematics and physics. Visualizing complex functions is a non‐trivial task since maps between two‐dimensional spaces are involved whose graph would be an unhandy submanifold in four‐dimensional space. The present paper improves the technique of “domain coloring” in several aspects: First, we lift domain coloring from the complex plane to branched Riemann surfaces, which are essentially the correct domain for most complex functions. Second, we extend domain coloring to the visualization of general 2‐valued maps on surfaces. As an application of such general maps we visualize the Gauss map of surfaces as domain colored plots and establish a link to current surface parametrization techniques and texture maps. Third, we adjust the color pattern in domain and in image space to produce higher quality domain colorings. The new color schemes specifically enhance the display of singularities, symmetries and path integrals, and give better qualitative measures of the complex map.
Map Displays for the Analysis of Scalar Data on Cerebral Aneurysm Surfaces
Authors: Mathias Neugebauer, Rocco Gasteiger, Oliver Beuing, Volker Diehl, Martin Skalej, Bernhard Preim
Published at EuroVis, 2009

Cerebral aneurysms result from a congenital or evolved weakness of stabilizing parts of the vessel wall and potentially lead to rupture and a life‐threatening bleeding. Current medical research concentrates on the integration of blood flow simulation results for risk assessment of cerebral aneurysms. Scalar flow characteristics close to the aneurysm surface, such as wall shear stress, form an important part of the simulation results. Aneurysms exhibit variable surface shapes with only few landmarks. Therefore, the exploration and mental correlation of different surface regions is a difficult task. In this paper, we present an approach for the intuitive and interactive overview visualization of near wall flow data that is mapped onto the surface of a 3D model of a cerebral aneurysm. We combine a multi‐perspective 2D projection map with a standard 3D visualization and present techniques to facilitate the correlation between a 3D model and a related 2D map. An informal evaluation with 4 experienced radiologists has shown that the map‐based overview actually improves the surface exploration. Furthermore, different color schemes were discussed and, as a result, an appropriate color scheme for the visual analysis of the wall shear stress is presented.
MultiClusterTree: Interactive Visual Exploration of Hierarchical Clusters in Multidimensional Multivariate Data
Authors: Tran Van Long, Lars Linsen
Published at EuroVis, 2009

Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more than three dimensions. Frequently, the analysis goal is not to look into individual records but to understand the distribution of the records at large and to find clusters of records with similar attribute values. A large number of (typically hierarchical) clustering algorithms have been developed to group individual records to clusters of statistical significance. However, only few visualization techniques exist for further exploring and understanding the clustering results. We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy. We also provide a clustering method that operates on density rather than individual records. To not restrict our search for clusters, we compute density in the given multidimensional multivariate space. Clusters are formed by areas of high density. We present an approach that automatically computes a hierarchical tree of high density clusters. To visually represent the cluster hierarchy, we present a 2D radial layout that supports an intuitive understanding of the distribution structure of the multidimensional multivariate data set. Individual clusters can be explored interactively using parallel coordinates when being selected in the cluster tree. Furthermore, we integrate circular parallel coordinates into the radial hierarchical cluster tree layout, which allows for the analysis of the overall cluster distribution. This visual representation supports the comprehension of the relations between clusters and the original attributes. The combination of the 2D radial layout and the circular parallel coordinates is used to overcome the overplotting problem of parallel coordinates when looking into data sets with many records. We apply an automatic coloring scheme based on the 2D radial layout of the hierarchical cluster tree encoding hue, saturation, and value of the HSV color space. The colors support linking the 2D radial layout to other views such as the standard parallel coordinates or, in case data is obtained from multidimensional spatial data, the distribution in object space.
On Visualization and Reconstruction from Non-Uniform Point Sets using B-splines
Authors: Erald Vuçini, Torsten Möller, M. Eduard Gröller
Published at EuroVis, 2009

In this paper we present a novel framework for the visualization and reconstruction from non‐uniform point sets. We adopt a variational method for the reconstruction of 3D non‐uniform data to a uniform grid of chosen resolution. We will extend this reconstruction to an efficient multi‐resolution uniform representation of the underlying data. Our multi‐resolution representation includes a traditional bottom‐up approach and a novel top‐down hierarchy for adaptive hierarchical reconstruction. Using a hybrid regularization functional we can improve the reconstruction results. Finally, we discuss further application scenarios and show rendering results to emphasize the effectiveness and quality of our proposed framework. By means of qualitative results and error comparisons we demonstrate superiority of our method compared to competing methods.
Preconceptions and Individual Differences in Understanding Visual Metaphors
Authors: Caroline Ziemkiewicz, Robert Kosara
Published at EuroVis, 2009

Understanding information visualization is more than a matter of reading a series of data values; it is also a matter of incorporating a visual structure into one's own thinking about a problem. We have proposed visual metaphors as a framework for understanding high‐level visual structure and its effect on visualization use. Although there is some evidence that visual metaphors can affect visualization use, the nature of this effect is still ambiguous. We propose that a user's preconceived metaphors for data and other individual differences play an important role in her ability to think in a variety of visual metaphors, and subsequently in her ability to use a visualization. We test this hypothesis by conducting a study in which a participant's preconceptions and thinking style were compared with the degree to which she is affected by conflicting metaphors in a visualization and its task questions. The results show that metaphor compatibility has a significant effect on accuracy, but that factors such as spatial ability and personality can lessen this effect. We also find a complex influence of self‐reported metaphor preference on performance. These findings shed light on how people use visual metaphors to understand a visualization.
Quasi-interpolation on the Body Centered Cubic Lattice
Authors: Alireza Entezari, Mahsa Mirzargar, Leila Kalantari
Published at EuroVis, 2009

This paper introduces a quasi‐interpolation method for reconstruction of data sampled on the Body Centered Cubic (BCC) lattice. The reconstructions based on this quasi‐interpolation achieve the optimal approximation order offered by the shifts of the quintic box spline on the BCC lattice. We also present a local FIR filter that is used to filter the data for quasi‐interpolation. We document the improved quality and fidelity of reconstructions after employing the introduced quasi‐interpolation method. Finally the resulting quasi‐interpolation on the BCC sampled data are compared to the corresponding quasi‐interpolation method on the Cartesian sampled data.
Scalable, Versatile and Simple Constrained Graph Layout
Authors: Tim Dwyer
Published at EuroVis, 2009

We describe a new technique for graph layout subject to constraints. Compared to previous techniques the proposed method is much faster and scalable to much larger graphs. For a graph with n nodes, m edges and c constraints it computes incremental layout in time O(n log n+m+c) per iteration. Also, it supports a much more powerful class of constraint: inequalities or equalities over the Euclidean distance between nodes. We demonstrate the power of this technique by application to a number of diagramming conventions which previous constrained graph layout methods could not support. Further, the constraint‐satisfaction method—inspired by recent work in position‐based dynamics—is far simpler to implement than previous methods.
SDViz: A Context-Preserving Interactive Visualization System for Technical Diagrams
Authors: Insoo Woo, SungYe Kim, Ross Maciejewski, David S. Ebert, Timothy D. Ropp, Krystal M. Thomas
Published at EuroVis, 2009

When performing daily maintenance and repair tasks, technicians require access to a variety of technical diagrams. As technicians trace components and diagrams from page‐to‐page, within and across manuals, the contextual information of the components they are analyzing can easily be lost. To overcome these issues, we have developed a Schematic Diagram Visualization System (SDViz) designed for maintaining and highlighting contextual information in technical documents, such as schematic and wiring diagrams. Our system incorporates various features to aid in the navigation and diagnosis of faults, as well as maintaining contextual information when tracing components/connections through multiple diagrams. System features include highlighting relationships between components and connectors, diagram annotation tools, the animation of flow through the system, a novel contextual blending method, and a variety of traditional focus+context visualization techniques. We have evaluated the usefulness of our system through a qualitative user study in which subjects utilized our system in diagnosing faults during a standard aircraft maintenance exercise.
Selecting good views of high-dimensional data using class consistency
Authors: Mike Sips, Boris Neubert, John P. Lewis, Pat Hanrahan
Published at EuroVis, 2009

Many visualization techniques involve mapping high‐dimensional data spaces to lower‐dimensional views. Unfortunately, mapping a high‐dimensional data space into a scatterplot involves a loss of information; or, even worse, it can give a misleading picture of valuable structure in higher dimensions. In this paper, we propose class consistency as a measure of the quality of the mapping. Class consistency enforces the constraint that classes of n–D data are shown clearly in 2–D scatterplots. We propose two quantitative measures of class consistency, one based on the distance to the class's center of gravity, and another based on the entropies of the spatial distributions of classes. We performed an experiment where users choose good views, and show that class consistency has good precision and recall. We also evaluate both consistency measures over a range of data sets and show that these measures are efficient and robust.
Semi-Automatic Time-Series Transfer Functions via Temporal Clustering and Sequencing
Authors: Jonathan Woodring, Han-Wei Shen
Published at EuroVis, 2009

When creating transfer functions for time‐varying data, it is not clear what range of values to use for classification, as data value ranges and distributions change over time. In order to generate time‐varying transfer functions, we search the data for classes that have similar behavior over time, assuming that data points that behave similarly belong to the same feature. We utilize a method we call temporal clustering and sequencing to find dynamic features in value space and create a corresponding transfer function. First, clustering finds groups of data points that have the same value space activity over time. Then, sequencing derives a progression of clusters over time, creating chains that follow value distribution changes. Finally, the cluster sequences are used to create transfer functions, as sequences describe the value range distributions over time in a data set.
Smooth Stream Surfaces of Fourth Order Precision
Authors: Dominic Schneider, Alexander Wiebel, Gerik Scheuermann
Published at EuroVis, 2009

We introduce a novel technique for the construction of smooth stream surfaces of 4th order precision. While common stream surface techniques use linear interpolation for generating seed points for new streamlines in the refinement phase, we use Hermite interpolation. The derivatives needed for Hermite interpolation are obtained by integration along the streamlines. This yields stream surfaces of4th order precision. Additionally, we analyse the accuracy ofthe well known Hultquist approach and our new algorithm and proof that Hultquist's method is exact for linear vector fields. We compare both methods using the well known distance based and a novel error based refinement strategy. Our resulting surface is C1 ‐continuous, enabling improved rendering among other benefits.
Splatting the Lines in Parallel Coordinates
Authors: Hong Zhou 0004, Weiwei Cui, Huamin Qu, Yingcai Wu, Xiaoru Yuan, Wei Zhuo 0001
Published at EuroVis, 2009

In this paper, we propose a novel splatting framework for clutter reduction and pattern revealing in parallel coordinates. Our framework consists of two major components: a polyline splatter for cluster detection and a segment splatter for clutter reduction. The cluster detection is performed by splatting the lines one by one into the parallel coordinates plots, and for each splatted line we enhance its neighboring lines and suppress irrelevant ones. To reduce visual clutter caused by line crossings and overlappings in the clustered results, we provide a segment splatter which represents each polyline by one segment and splats these segments with different speeds, colors, and lengths from the leftmost axis to the rightmost axis. Users can interactively control both the polyline splatting and the segment splatting processes to emphasize the features they are interested in. The experimental results demonstrate that our framework can effectively reveal some hidden patterns in parallel coordinates.
The Chinese Room: Visualization and Interaction to Understand and Correct Ambiguous Machine Translation
Authors: Joshua Albrecht, Rebecca Hwa, G. Elisabeta Marai
Published at EuroVis, 2009

We present The Chinese Room, a visualization interface that allows users to explore and interact with a multitude of linguistic resources in order to decode and correct poor machine translations. The target users of The Chinese Room are not bilingual and are not familiar with machine translation technologies. We investigate the ability of our system to assist such users in decoding and correcting faulty machine translations. We found that by collaborating with our application, end‐users can overcome many difficult translation errors and disambiguate translated passages that were otherwise baffling. We also examine the utility of our system to machine translation researchers. Anecdotal evidence suggests that The Chinese Room can help such researchers develop better machine translation systems.