These pre-pages to the issue contain a table of contents, a list of supporting organizations, a message from the Editor-in-Chief, the preface, committee and reviewer listings, 2005 visualization awards, and the keynote and capstone addressess for Vis ...

These pre-pages to the issue contain a table of contents, a list of supporting organizations, a message from the Editor-in-Chief, the preface, committee and reviewer listings, 2005 visualization awards, and the keynote and capstone addressess for Vis and InfoVis.

We describe ASK-GraphView, a node-link-based graph visualization system that allows clustering and interactive navigation of large graphs, ranging in size up to 16 million edges. The system uses a scalable architecture and a series of increasingly sophisticated ...

We describe ASK-GraphView, a node-link-based graph visualization system that allows clustering and interactive navigation of large graphs, ranging in size up to 16 million edges. The system uses a scalable architecture and a series of increasingly sophisticated clustering algorithms to construct a hierarchy on an arbitrary, weighted undirected input graph. By lowering the interactivity requirements we can scale to substantially bigger graphs. The user is allowed to navigate this hierarchy in a top down manner by interactively expanding individual clusters. ASK-GraphView also provides facilities for filtering and coloring, annotation and cluster labeling.

MatrixExplorer is a network visualization system that uses two representations: node-link diagrams and matrices.Its design comes from a list of requirements formalized after several interviews and a participatory design session conducted with social ...

MatrixExplorer is a network visualization system that uses two representations: node-link diagrams and matrices.Its design comes from a list of requirements formalized after several interviews and a participatory design session conducted with social science researchers.Although matrices are commonly used in social networks analysis, very few systems support the matrix-based representations to visualize and analyze networks. MatrixExplorer provides several novel features to support the exploration of social networks with a matrix-based representation, in addition to the standard interactive filtering and clustering functions. It provides tools to reorder (layout) matrices, to annotate and compare findings across different layouts and find consensus among several clusterings.MatrixExplorer also supports Node-link diagram views which are familiar to most users and remain a convenient way to publish or communicate exploration results.Matrix and node-link representations are kept synchronized at all stages of the exploration process.

We present a new approach for the visual analysis of state transition graphs. We deal with multivariate graphs where a number of attributes are associated with every node. Our method provides an interactive attribute-based clustering facility. Clustering ...

We present a new approach for the visual analysis of state transition graphs. We deal with multivariate graphs where a number of attributes are associated with every node. Our method provides an interactive attribute-based clustering facility. Clustering results in metric, hierarchical and relational data, represented in a single visualization. To visualize hierarchically structured quantitative data, we introduce a novel technique: the bar tree. We combine this with a node-link diagram to visualize the hierarchy and an arc diagram to visualize relational data. Our method enables the user to gain significant insight into large state transition graphs containing tens of thousands of nodes. We illustrate the effectiveness of our approach by applying it to a real-world use case. The graph we consider models the behavior of an industrial wafer stepper and contains 55 043 nodes and 289 443 edges.

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks.However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend ...

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks.However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner.This results in exploration that is largely opportunistic.Our contributions are techniques to help structural analysts understand social networks more effectively.We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures.Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview.For each operation, a stable node layout is maintained in the network visualization so users can make comparisons.SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks.

In his text Visualizing Data, William Cleveland demonstrates how the aspect ratio of a line chart can affect an analyst's perception of trends in the data. Cleveland proposes an optimization technique for computing the aspect ratio such that the average ...

In his text Visualizing Data, William Cleveland demonstrates how the aspect ratio of a line chart can affect an analyst's perception of trends in the data. Cleveland proposes an optimization technique for computing the aspect ratio such that the average absolute orientation of line segments in the chart is equal to 45 degrees. This technique, called banking to 45 degrees, is designed to maximize the discriminability of the orientations of the line segments in the chart. In this paper, we revisit this classic result and describe two new extensions. First, we propose alternate optimization criteria designed to further improve the visual perception of line segment orientations. Second, we develop multi-scale banking, a technique that combines spectral analysis with banking to 45 degrees . Our technique automatically identifies trends at various frequency scales and then generates a banked chart for each of these scales. We demonstrate the utility of our techniques in a range of visualization tools and analysis examples.

Data abstraction techniques are widely used in multiresolution visualization systems to reduce visual clutter and facilitate analysis from overview to detail. However, analysts are usually unaware of how well the abstracted data represent the original ...

Data abstraction techniques are widely used in multiresolution visualization systems to reduce visual clutter and facilitate analysis from overview to detail. However, analysts are usually unaware of how well the abstracted data represent the original dataset, which can impact the reliability of results gleaned from the abstractions. In this paper, we define two data abstraction quality measures for computing the degree to which the abstraction conveys the original dataset: the Histogram Difference Measure and the Nearest Neighbor Measure. They have been integrated within XmdvTool, a public-domain multiresolution visualization system for multivariate data analysis that supports sampling as well as clustering to simplify data. Several interactive operations are provided, including adjusting the data abstraction level, changing selected regions, and setting the acceptable data abstraction quality level. Conducting these operations, analysts can select an optimal data abstraction level. Also, analysts can compare different abstraction methods using the measures to see how well relative data density and outliers are maintained, and then select an abstraction method that meets the requirement of their analytic tasks.

We have previously shown that random sampling is an effective clutter reduction technique and that a sampling lens can facilitate focus+context viewing of particular regions. This demands an efficient method of estimating the overlap or occlusion of ...

We have previously shown that random sampling is an effective clutter reduction technique and that a sampling lens can facilitate focus+context viewing of particular regions. This demands an efficient method of estimating the overlap or occlusion of large numbers of intersecting lines in order to automatically adjust the sampling rate within the lens. This paper proposes several ways for measuring occlusion in parallel coordinate plots. An empirical study into the accuracy and efficiency of the occlusion measures show that a probabilistic approach combined with a ÔbinningÕ technique is very fast and yet approaches the accuracy of the more expensive ÔtrueÕ complete measurement.

We propose a new metaphor for the visualization of prefixes propagation in the Internet.Such a metaphor is based on the concept of topographic map and allows to put in evidencethe relative importance of the Internet Service Providers (ISPs) involved ...

We propose a new metaphor for the visualization of prefixes propagation in the Internet.Such a metaphor is based on the concept of topographic map and allows to put in evidencethe relative importance of the Internet Service Providers (ISPs) involved in the routing of the prefix.Based on the new metaphor we propose an algorithm for computing layouts and experiment with such algorithm on a test suite taken from the real Internet. The paper extends the visualization approachof the BGPlay service, which is an Internet routing monitoring tool widely used by ISP operators.

Networks have remained a challenge for information visualization designersbecause of the complex issues of node and link layout coupled with the rich set of tasksthat users present.This paper offers a strategy based on two principles:(1) layouts are ...

Networks have remained a challenge for information visualization designersbecause of the complex issues of node and link layout coupled with the rich set of tasksthat users present.This paper offers a strategy based on two principles:(1) layouts are based on user-defined semantic substrates, which are non-overlappingregions in which node placement is based on node attributes, (2) users interactivelyadjust sliders to control link visibility to limit clutter and thus ensure comprehensibilityof source and destination. Scalability is further facilitated by user control of which nodesare visible. We illustrate our semantic substrates approach as implemented in NVSS 1.0with legal precedent data for up to 1122 court cases in three regions with 7645 legalcitations.

In many applications, data is collected and indexed by geo-spatial location. Discovering interesting patterns through visualization is an important way of gaining insight about such data. A previously proposed approach is to apply local placement functions ...

In many applications, data is collected and indexed by geo-spatial location. Discovering interesting patterns through visualization is an important way of gaining insight about such data. A previously proposed approach is to apply local placement functions such as PixelMaps that transform the input data set into a solution set that preserves certain constraints while making interesting patterns more obvious and avoid data loss from overplotting. In experience, this family of spatial transformations can reveal fine structures in large point sets, but it is sometimes difficult to relate those structures to basic geographic features such as cities and regional boundaries. Recent information visualization research has addressed other types of transformation functions that make spatially-transformed maps with recognizable shapes. These types of spatial-transformation are called global shape functions. In particular, cartogram-based map distortion has been studied.On the other hand, cartogram-based distortion does not handle point sets readily. In this study, we present a framework that allows the user to specify a global shape function and a local placement function. We combine cartogram-based layout (global shape) with PixelMaps (local placement), obtaining some of the benefits of each toward improved exploration of dense geo-spatial data sets.

This paper describes the Worldmapper Project, which makes use of novel visualization techniques to represent a broad variety of social and economic data about the countries of the world.The goal of the project is to use the map projections known as cartograms ...

This paper describes the Worldmapper Project, which makes use of novel visualization techniques to represent a broad variety of social and economic data about the countries of the world.The goal of the project is to use the map projections known as cartograms to depict comparisons and relations between different territories, and its execution raises many interesting design challenges that were not all apparent at the outset.We discuss the approaches taken towards these challenges, some of which may have considerably broad application. We conclude by commenting on the positive initial response to the worldmapper images published on the web, which we believe is due, at least in part, to the particular effectiveness of the cartogram as a tool for communicating quantitative geographic data.

People in different places talk about different things. This interest distribution is reflected by the newspaper articles circulated in a particular area. We use data from our large-scale newspaper analysis system (Lydia) to make entity datamaps, a spatial ...

People in different places talk about different things. This interest distribution is reflected by the newspaper articles circulated in a particular area. We use data from our large-scale newspaper analysis system (Lydia) to make entity datamaps, a spatial visualization of the interest in a given named entity. Our goal is to identify entities which display regional biases. We develop a model of estimating the frequency of reference of an entity in any given city from the reference frequency centered in surrounding cities, and techniques for evaluating the spatial significance of this distribution.

We address the problem of filtering, selecting and placing labels on a dynamic map, which is characterized by continuous zooming and panning capabilities.This consists of two interrelated issues.The first is to avoid label popping and other artifacts ...

We address the problem of filtering, selecting and placing labels on a dynamic map, which is characterized by continuous zooming and panning capabilities.This consists of two interrelated issues.The first is to avoid label popping and other artifacts that cause confusion and interrupt navigation, and the second is to label at interactive speed.In most formulations the static map labeling problem is $NP$-hard, and a fast approximation might have $O(n \log n)$ complexity.Even this is too slow during interaction, when the number of labels shown can be several orders of magnitude less than the number in the map. In this paper we introduce a set of desiderata for ``consistent'' dynamic map labeling, which has qualities desirable for navigation.We develop a new framework for dynamic labeling that achieves the desiderata and allows for fast interactive display by moving all of the selection and placement decisions into the preprocessing phase.This framework is general enough to accommodate a variety of selection and placement algorithms. It does not appear possible to achieve our desiderata using previous frameworks.Prior to this paper, there were no formal models of dynamic maps or of dynamic labels; our paper introduces both. We formulate a general optimization problem for dynamic map labeling and give a solution to a simple version of the problem. The simple version is based on label priorities and a versatile and intuitive class of dynamic label placements we call ``invariant point placements''.Despite these restrictions, our approach gives a useful and practical solution.Our implementation is incorporated into the G-Vis system which is a full-detail dynamic map of the continental USA.This demo is available through any browser.

Dynamical models that explain the formation of spatial structures of RNA molecules have reached a complexity that requires novel visualization methods that help to analyze the validity of these models. Here, we focus on the visualization of so-called ...

Dynamical models that explain the formation of spatial structures of RNA molecules have reached a complexity that requires novel visualization methods that help to analyze the validity of these models. Here, we focus on the visualization of so-called folding landscapes of a growing RNA molecule. Folding landscapes describe the energy of a molecule as a function of its spatial configuration; thus they are huge and high dimensional. Their most salient features, however, are encapsulated by their so-called barrier tree that reflects the local minima and their connecting saddle points. For each length of the growing RNA chain there exists a folding landscape. We visualize the sequence of folding landscapes by an animation of the corresponding barrier trees. To generate the animation, we adapt the foresight layout with tolerance algorithm for general dynamic graph layout problems. Since it is very general, we give a detailed description of each phase: constructing a supergraph for the trees, layout of that supergraph using a modified DOT algorithm, and presentation techniques for the final animation.

Business data is often presented using simple business graphics.These familiar visualizations are effective for providing overviews,but fall short for the presentation of large amounts of detailedinformation. Treemaps can provide such detail, but are ...

Business data is often presented using simple business graphics.These familiar visualizations are effective for providing overviews,but fall short for the presentation of large amounts of detailedinformation. Treemaps can provide such detail, but are often noteasy to understand. We present how standard treemap algorithms canbe adapted such that the results mimic familiar business graphics. Specifically, we present the use of different layout algorithms perlevel, a number of variations of the squarified algorithm, the useof variable borders, and the use of non-rectangular shapes. Thecombined use of these leads to histograms, pie charts and a varietyof other styles.

The dominant paradigm for searching and browsing large data stores is text-based: presenting a scrollable list of search results in response to textual search term input. While this works well for the Web, there is opportunity for improvement in the ...

The dominant paradigm for searching and browsing large data stores is text-based: presenting a scrollable list of search results in response to textual search term input. While this works well for the Web, there is opportunity for improvement in the domain of personal information stores, which tend to have more heterogeneous data and richer metadata. In this paper, we introduce FacetMap, an interactive, query-driven visualization, generalizable to a wide range of metadata-rich data stores. FacetMap uses a visual metaphor for both input (selection of metadata facets as filters) and output. Results of a user study provide insight into tradeoffs between FacetMap's graphical approach and the traditional text-oriented approach.

Many graph drawing and visualization algorithms, such as force-directed layout and line-dot rendering, work very well on relatively small and sparse graphs. However, they often produce extremely tangled results and exhibit impractical running times for ...

Many graph drawing and visualization algorithms, such as force-directed layout and line-dot rendering, work very well on relatively small and sparse graphs. However, they often produce extremely tangled results and exhibit impractical running times for highly non-planar graphs with large edge density. And very few graph layout algorithms support dynamic time-varying graphs; applying them independently to each frame produces distracting temporally incoherent visualizations. We have developed a new visualization technique based on a novel approach to hierarchically structuring dense graphs via stratification.Using this structure, we formulate a hierarchical force-directed layout algorithm that is both efficient and produces quality graph layouts.The stratification of the graph also allows us to present views of the data that abstract away many small details of its structure. Rather than displaying all edges and nodes at once, resulting in a convoluted rendering, we present an interactive tool that filters edges and nodes using the graph hierarchy and allows users to drill down into the graph for details. Our layout algorithm also accommodates time-varying graphs in a natural way, producing a temporally coherent animation that can be used to analyze and extract trends from dynamic graph data. For example, we demonstrate the use of our method to explore financial correlation data for the U.S. stock market in the period from 1990 to 2005.The user can easily analyze the time-varying correlation graph of the market, uncovering information such as market sector trends, representative stocks for portfolio construction, and the interrelationship of stocks over time.

Quasi-trees, namely graphs with tree-like structure, appear in many application domains, including bioinformatics and computer networks.Our new SPF approach exploits the structure of these graphs with a two-level approach to drawing, where the graph ...

Quasi-trees, namely graphs with tree-like structure, appear in many application domains, including bioinformatics and computer networks.Our new SPF approach exploits the structure of these graphs with a two-level approach to drawing, where the graph is decomposed into a tree of biconnected components. The low-level biconnected components are drawn with a force-directed approach that uses a spanning tree skeleton as a starting point for the layout. The higher-level structure of the graph is a true tree with meta-nodes of variable size that contain each biconnected component. That tree is drawn with a new area-aware variant of a tree drawing algorithm that handles high-degree nodes gracefully, at the cost of allowing edge-node overlaps. SPF performs an order of magnitude faster than the best previous approaches, while producing drawings of commensurate or improved quality.

We extend the popular force-directed approach to network (or graph) layout to allow separation constraints, which enforce a minimum horizontal or vertical separation between selected pairs of nodes. This simple class of linear constraints is expressive ...

We extend the popular force-directed approach to network (or graph) layout to allow separation constraints, which enforce a minimum horizontal or vertical separation between selected pairs of nodes. This simple class of linear constraints is expressive enough to satisfy a wide variety of application-specific layout requirements, including: layout of directed graphs to better show flow; layout with non-overlapping node labels; and layout of graphs with grouped nodes (called clusters). In the stress majorization force-directed layout process, separation constraints can be treated as a quadratic programming problem. We give an incremental algorithm based on gradient projection for efficiently solving this problem. The algorithm is considerably faster than using generic constraint optimization techniques and is comparable in speed to unconstrained stress majorization. We demonstrate the utility of our technique with sample data from a number of practical applications including gene-activation networks, terrorist networks and visualization of high-dimensional data.

Existing information-visualization techniques that target small screens are usually limited to exploring a few hundred items. In this article we present a scatterplot tool for Personal Digital Assistants that allows the handling of many thousands of ...

Existing information-visualization techniques that target small screens are usually limited to exploring a few hundred items. In this article we present a scatterplot tool for Personal Digital Assistants that allows the handling of many thousands of items. The application's scalability is achieved by incorporating two alternative interaction techniques: a geometric-semantic zoom that provides smooth transition between overview and detail, and a fisheye distortion that displays the focus and context regions of the scatterplot in a single view. A user study with 24 participants was conducted to compare the usability and efficiency of both techniques when searching a book database containing 7500 items. The study was run on a pen-driven Wacom board simulating a PDA interface. While the results showed no significant difference in task-completion times, a clear majority of 20 users preferred the fisheye view over the zoom interaction. In addition, other dependent variables such as user satisfaction and subjective rating of orientation and navigation support revealed a preference for the fisheye distortion. These findings partly contradict related research and indicate that, when using a small screen, users place higher value on the ability to preserve navigational context than they do on the ease of use of a simplistic, metaphor-based interaction style.

Larger, higher resolution displays can be used to increase the scalability of information visualizations. But just how much can scalability increase using larger displays before hitting human perceptual or cognitive limits? Are the same visualization ...

Larger, higher resolution displays can be used to increase the scalability of information visualizations. But just how much can scalability increase using larger displays before hitting human perceptual or cognitive limits? Are the same visualization techniques that are good on a single monitor also the techniques that are best when they are scaled up using large, high-resolution displays? To answer these questions we performed a controlled experiment on user performance time, accuracy, and subjective workload when scaling up data quantity with different space-time-attribute visualizations using a large, tiled display. Twelve college students used small multiples, embedded bar matrices, and embedded time-series graphs either on a 2 megapixel (Mp) display or with data scaled up using a 32 Mp tiled display. Participants performed various overview and detail tasks on geospatially-referenced multidimensional time-series data. Results showed that current designs are perceptually scalable because they result in a decrease in task completion time when normalized per number of data attributes along with no decrease in accuracy. It appears that, for the visualizations selected for this study, the relative comparison between designs is generally consistent between display sizes. However, results also suggest that encoding is more important on a smaller display while spatial grouping is more important on a larger display. Some suggestions for designers are provided based on our experience designing visualizations for large displays.

Commonly known detail in context techniques for the two-dimensional Euclidean space enlarge details and shrink their context using mapping functions that introduce geometrical compression. This makes it difficult or even impossible to recognize shapes ...

Commonly known detail in context techniques for the two-dimensional Euclidean space enlarge details and shrink their context using mapping functions that introduce geometrical compression. This makes it difficult or even impossible to recognize shapes for large differences in magnification factors. In this paper we propose to use the complex logarithm and the complex root functions to show very small details even in very large contexts. These mappings are conformal, which means they only locally rotate and scale, thus keeping shapes intact and recognizable. They allow showing details that are orders of magnitude smaller than their surroundings in combination with their context in one seamless visualization. We address the utilization of this universal technique for the interaction with complex two-dimensional data considering the exploration of large graphs and other examples.

Despite a diversity of software architectures supporting information visualization, it is often difficult to identify, evaluate, and re-apply the design solutions implemented within such frameworks. One popular and effective approach for addressing such ...

Despite a diversity of software architectures supporting information visualization, it is often difficult to identify, evaluate, and re-apply the design solutions implemented within such frameworks. One popular and effective approach for addressing such difficulties is to capture successful solutions in design patterns, abstract descriptions of interacting software components that can be customized to solve design problems within a particular context. Based upon a review of existing frameworks and our own experiences building visualization software, we present a series of design patterns for the domain of information visualization. We discuss the structure, context of use, and interrelations of patterns spanning data representation, graphics, and interaction. By representing design knowledge in a reusable form, these patterns can be used to facilitate software design, implementation, and evaluation, and improve developer education and communication.

We present a novel pipeline for computer-aided detection (CAD) of colonic polyps by integrating texture and shape analysis with volume rendering and conformal colon flattening. Using our automatic method, the 3D polyp detection problem is converted into ...

We present a novel pipeline for computer-aided detection (CAD) of colonic polyps by integrating texture and shape analysis with volume rendering and conformal colon flattening. Using our automatic method, the 3D polyp detection problem is converted into a 2D pattern recognition problem. The colon surface is first segmented and extracted from the CT data set of the patient's abdomen, which is then mapped to a 2D rectangle using conformal mapping. This flattened image is rendered using a direct volume rendering technique with a translucent electronic biopsy transfer function. The polyps are detected by a 2D clustering method on the flattened image. The false positives are further reduced by analyzing the volumetric shape and texture features. Compared with shape based methods, our method is much more efficient without the need of computing curvature and other shape parameters for the whole colon surface. The final detection results are stored in the 2D image, which can be easily incorporated into a virtual colonoscopy (VC) system to highlight the polyp locations. The extracted colon surface mesh can be used to accelerate the volumetric ray casting algorithm used to generate the VC endoscopic view. The proposed automatic CAD pipeline is incorporated into an interactive VC system, with a goal of helping radiologists detect polyps faster and with higher accuracy.

This paper presents a procedure for virtual autopsies based on interactive 3D visualizations of large scale, high resolution data from CT-scans of human cadavers. The procedure is described using examples from forensic medicine and the added value and ...

This paper presents a procedure for virtual autopsies based on interactive 3D visualizations of large scale, high resolution data from CT-scans of human cadavers. The procedure is described using examples from forensic medicine and the added value and future potential of virtual autopsies is shown from a medical and forensic perspective. Based on the technical demands of the procedure state-of-the-art volume rendering techniques are applied and refined to enable real-time, full body virtual autopsies involving gigabyte sized data on standard GPUs. The techniques applied include transfer function based data reduction using level-of-detail selection and multi-resolution rendering techniques. The paper also describes a data management component for large, out-of-core data sets and an extension to the GPU-based raycaster for efficient dual TF rendering.Detailed benchmarks of the pipeline are presented using data sets from forensic cases.

We present real-time vascular visualization methods, which extend on illustrative rendering techniques to particularly accentuate spatial depth and to improve the perceptive separation of important vascular properties such as branching level and supply ...

We present real-time vascular visualization methods, which extend on illustrative rendering techniques to particularly accentuate spatial depth and to improve the perceptive separation of important vascular properties such as branching level and supply area. The resulting visualization can and has already been used for direct projection on a patientÕs organ in the operation theater where the varying absorption and reflection characteristics of the surface limit the use of color. The important contributions of our work are a GPU-based hatching algorithm for complex tubular structures that emphasizes shape and depth as well as GPU-accelerated shadow-like depth indicators, which enable reliable comparisons of depth distances in a static monoscopic 3D visualization. In addition, we verify the expressiveness of our illustration methods in a large, quantitative study with 160 subjects.

Computer-aided diagnosis (CAD) is a helpful addition to laborious visual inspection for preselection of suspected colonic polyps in virtual colonoscopy. Most of the previous work on automatic polyp detection makes use of indicators based on the scalar ...

Computer-aided diagnosis (CAD) is a helpful addition to laborious visual inspection for preselection of suspected colonic polyps in virtual colonoscopy. Most of the previous work on automatic polyp detection makes use of indicators based on the scalar curvature of the colon wall and can result in many false-positive detections. Our work tries to reduce the number of false-positive detections in the preselection of polyp candidates.Polyp surface shape can be characterized and visualized using lines of curvature. In this paper, we describe techniques for generating and rendering lines of curvature on surfaces and we show that these lines can be used as part of a polyp detection approach. We have adapted existing approaches on explicit triangular surface meshes, and developed a new algorithm on implicit surfaces embedded in 3D volume data. The visualization of shaded colonic surfaces can be enhanced by rendering the derived lines of curvature on these surfaces.Features strongly correlated with true-positive detections were calculated on lines of curvature and used for the polyp candidate selection. We studied the performance of these features on 5 data sets that included 331 pre-detected candidates, of which 50 sites were true polyps. The winding angle had a significant discriminating power for true-positive detections, which was demonstrated by a Wilcoxon rank sum test with p<0.001. The median winding angle and inter-quartile range (IQR) for true polyps were 7.817 and 6.770-9.288 compared to 2.954 and 1.995-3.749 for false-positive detections.

Focus+context visualization integrates a visually accentuated representation of selected data items in focus (more details, more opacity, etc.) with a visually deemphasized representation of the rest of the data, i.e., the context. The role of context ...

Focus+context visualization integrates a visually accentuated representation of selected data items in focus (more details, more opacity, etc.) with a visually deemphasized representation of the rest of the data, i.e., the context. The role of context visualization is to provide an overview of the data for improved user orientation and improved navigation. A good overview comprises the representation of both outliers and trends. Up to now, however, context visualization not really treated outliers sufficiently. In this paper we present a new approach to focus+context visualization in parallel coordinates which is truthful to outliers in the sense that small-scale features are detected before visualization and then treated specially during context visualization. Generally, we present a solution which enables context visualization at several levels of abstraction, both for the representation of outliers and trends. We introduce outlier detection and context generation to parallel coordinates on the basis of a binned data representation. This leads to an output-oriented visualization approach which means that only those parts of the visualization process are executed which actually affect the final rendering. Accordingly, the performance of this solution is much more dependent on the visualization size than on the data size which makes it especially interesting for large datasets. Previous approaches are outperformed, the new solution was successfully applied to datasets with up to 3 million data records and up to 50 dimensions.

We present the first scalable algorithm that supports the composition of successive rectilinear deformations.Earlier systems that provided stretch and squish navigation could only handle small datasets.More recent work featuring rubber sheet navigation ...

We present the first scalable algorithm that supports the composition of successive rectilinear deformations.Earlier systems that provided stretch and squish navigation could only handle small datasets.More recent work featuring rubber sheet navigation for large datasets has focused on rendering and on application-specific issues. However, no algorithm has yet been presented for carrying out such navigation methods; our paper addresses this problem. For maximum flexibility with large datasets, a stretch and squish navigation algorithm should allow for millions of potentially deformable regions. However, typical usage only changes the extents of a small subset k of these n regions at a time. The challenge is to avoid computations that are linear in n, because a single deformation can affect the absolute screen-space location of every deformable region. We provide an O(k log n) algorithm that supports any application that can lay out a dataset on a generic grid, and show an implementation that allows navigation of trees and gene sequences with millions of items in sub-millisecond time.

Time-varying, multi-variate, and comparative data sets are not easily visualized due to the amount of data that is presented to the user at once. By combining several volumes together with different operators into one visualized volume, the user is able ...

Time-varying, multi-variate, and comparative data sets are not easily visualized due to the amount of data that is presented to the user at once. By combining several volumes together with different operators into one visualized volume, the user is able to compare values from different data sets in space over time, run, or field without having to mentally switch between different renderings of individual data sets. In this paper, we propose using a volume shader where the user is given the ability to easily select and operate on many data volumes to create comparison relationships. The user specifies an expression with set and numerical operations and her data to see relationships between data fields. Furthermore, we render the contextual information of the volume shader by converting it to a volume tree. We visualize the different levels and nodes of the volume tree so that the user can see the results of suboperations. This gives the user a deeper understanding of the final visualization, by seeing how the parts of the whole are operationally constructed.

We present an approach to visualizingcorrelations in 3D multifield scalar data. The core of our approach is the computation of correlation fields, which are scalar fields containing the local correlations of subsets of the multiple fields.While the visualization ...

We present an approach to visualizingcorrelations in 3D multifield scalar data. The core of our approach is the computation of correlation fields, which are scalar fields containing the local correlations of subsets of the multiple fields.While the visualization of the correlation fields can be done using standard 3D volume visualization techniques, their huge number makes selection and handling a challenge. We introduce the Multifield-Graph to give an overview of which multiple fields correlate and to show the strength of their correlation. This information guides the selection of informative correlation fields for visualization. We use our approach to visually analyze a number of real andsynthetic multifield datasets.

Recent research in visual saliency has established a computational measure of perceptual importance. In this paper we present a visual-saliency-based operator to enhance selected regions of a volume. We show how we use such an operator on a user-specified ...

Recent research in visual saliency has established a computational measure of perceptual importance. In this paper we present a visual-saliency-based operator to enhance selected regions of a volume. We show how we use such an operator on a user-specified saliency field to compute an emphasis field. We further discuss how the emphasis field can be integrated into the visualization pipeline through its modifications of regional luminance and chrominance. Finally, we validate our work using an eye-tracking-based user study and show that our new saliency enhancement operator is more effective at eliciting viewer attention than the traditional Gaussian enhancement operator.

This paper introduces a concept for automatic focusing on features within a volumetric data set. The user selects a focus, i.e., object of interest, from a set of pre-defined features. Our system automatically determines the most expressive view on this ...

This paper introduces a concept for automatic focusing on features within a volumetric data set. The user selects a focus, i.e., object of interest, from a set of pre-defined features. Our system automatically determines the most expressive view on this feature. A characteristic viewpoint is estimated by a novel information-theoretic framework which is based on the mutual information measure. Viewpoints change smoothly by switching the focus from one feature to another one. This mechanism is controlled by changes in the importance distribution among features in the volume. The highest importance is assigned to the feature in focus. Apart from viewpoint selection, the focusing mechanism also steers visual emphasis by assigning a visually more prominent representation. To allow a clear view on features that are normally occluded by other parts of the volume, the focusing for example incorporates cut-away views.}

Volume rendered imagery often includes a barrage of 3D information like shape, appearance and topology of complex structures, and it thus quickly overwhelms the user. In particular, when focusing on a specific region a user cannot observe the relationship ...

Volume rendered imagery often includes a barrage of 3D information like shape, appearance and topology of complex structures, and it thus quickly overwhelms the user. In particular, when focusing on a specific region a user cannot observe the relationship between various structures unless he has a mental picture of the entire data. In this paper we present ClearView, a GPU-based, interactive framework for texture-based volume ray-casting that allows users which do not have the visualization skills for this mental exercise to quickly obtain a picture of the data in a very intuitive and user-friendly way. ClearView is designed to enable the user to focus on particular areas in the data while preserving context information without visual clutter. ClearView does not require additional feature volumes as it derives any features in the data from image information only. A simple point-and-click interface enables the user to interactively highlight structures in the data. ClearView provides an easy to use interface to complex volumetric data as it only uses transparency in combination with a few specific shaders to convey focus and context information.

Vortices are undesirable in many applications while indispensable in others. It is therefore of common interest to understand their mechanisms of creation. This paper aims at analyzing the transport of vorticity inside incompressible flow. The analysis ...

Vortices are undesirable in many applications while indispensable in others. It is therefore of common interest to understand their mechanisms of creation. This paper aims at analyzing the transport of vorticity inside incompressible flow. The analysis is based on the vorticity equation and is performed along pathlines which are typically started in upstream direction from vortex regions. Different methods for the quantitative and explorative analysis of vorticity transport are presented and applied to CFD simulations of water turbines. Simulation quality is accounted for by including the errors of meshing and convergence into analysis and visualization. The obtained results are discussed and interpretations with respect to engineering questions are given.

In order to understand complex vortical flows in large data sets, we must be able to detect and visualize vortices in an automated fashion. In this paper, we present a feature-based vortex detection and visualization technique that is appropriate for ...

In order to understand complex vortical flows in large data sets, we must be able to detect and visualize vortices in an automated fashion. In this paper, we present a feature-based vortex detection and visualization technique that is appropriate for large computational fluid dynamics data sets computed on unstructured meshes. In particular, we focus on the application of this technique to visualization of the flow over a serrated wing and the flow field around a spinning missile with dithering canards. We have developed a core line extraction technique based on the observation that vortex cores coincide with local extrema in certain scalar fields. We also have developed a novel technique to handle complex vortex topology that is based on k-means clustering. These techniques facilitate visualization of vortices in simulation data that may not be optimally resolved or sampled. Results are included that highlight the strengths and weaknesses of our approach. We conclude by describing how our approach can be improved to enhance robustness and expand its range of applicability.

This paper presents an advanced evenly-spaced streamline placement algorithm for fast, high-quality, and robust layout of flow lines. A fourth-order Runge-Kutta integrator with adaptive step size and error control is employed for rapid accurate streamline ...

This paper presents an advanced evenly-spaced streamline placement algorithm for fast, high-quality, and robust layout of flow lines. A fourth-order Runge-Kutta integrator with adaptive step size and error control is employed for rapid accurate streamline advection. Cubic Hermite polynomial interpolation with large sample-spacing is adopted to create fewer evenly-spaced samples along each streamline to reduce the amount of distance checking. We propose two methods to enhance placement quality. Double queues are used to prioritizetopological seeding and to favor long streamlines to minimize discontinuities. Adaptive distance control based on the local flow variance is explored to reduce cavities. Furthermore, we propose a universal, effective, fast, and robust loop detection strategy to address closed and spiraling streamlines. Our algorithm is an order-of-magnitude faster than Jobard and Lefer's algorithm [8] with better placement quality and over 5 times faster than Mebarki et al.'s algorithm [9] with comparable placement quality, but with a more robust solution to loop detection.

The pipeline model in visualization has evolved from a conceptual model of data processing into a widely used architecture for implementing visualization systems. In the process, a number of capabilities have been introduced, including streaming of data ...

The pipeline model in visualization has evolved from a conceptual model of data processing into a widely used architecture for implementing visualization systems. In the process, a number of capabilities have been introduced, including streaming of data in chunks, distributed pipelines, and demand-driven processing. Visualization systems have invariably built on stateful programming technologies, and these capabilities have had to be implemented explicitly within the lower layers of a complex hierarchy of services. The good news for developers is that applications built on top of this hierarchy can access these capabilities without concern for how they are implemented. The bad news is that by freezing capabilities into low-level services expressive power and flexibility is lost. In this paper we express visualization systems in a programming language that more naturally supports this kind of processing model. Lazy functional languages support fine-grained demand-driven processing, a natural form of streaming, and pipeline-like function composition for assembling applications. The technology thus appears well suited to visualization applications. Using surface extraction algorithms as illustrative examples, and the lazy functional language Haskell, we argue the benefits of clear and concise expression combined with fine-grained, demand-driven computation. Just as visualization provides insight into data, functional abstraction provides new insight into visualization.

This paper presents an interactive visualization system, named WebSearchViz, for visualizing the Web search results and facilitating users' navigation and exploration.The metaphor in our model is the solar system with its planets and asteroids revolving ...

This paper presents an interactive visualization system, named WebSearchViz, for visualizing the Web search results and facilitating users' navigation and exploration.The metaphor in our model is the solar system with its planets and asteroids revolving around the sun. Location, color, movement, and spatial distance of objects in the visual space are used to represent the semantic relationships between a query and relevant Web pages. Especially, the movement of objects and their speeds add a new dimension to the visual space, illustrating the degree of relevance among a query and Web search results in the context of users' subjects of interest. By interacting with the visual space, users are able to observe the semantic relevance between a query and a resulting Web page with respect to their subjects of interest, context information, or concern. Users' subjects of interest can be dynamically changed, redefined, added, or deleted from the visual space.

In the past decade, a lot of research work has been conductedto support collaborative visualization among remote users over thenetworks, allowing them to visualize and manipulate shared data forproblem solving. There are many applications of collaborativevisualization, ...

In the past decade, a lot of research work has been conductedto support collaborative visualization among remote users over thenetworks, allowing them to visualize and manipulate shared data forproblem solving. There are many applications of collaborativevisualization, such as oceanography, meteorology and medical science. Tofacilitate user interaction, a critical system requirement forcollaborative visualization is to ensure that remote users will perceivea synchronized view of the shared data. Failing this requirement, theuser¡¦s ability in performing the desirable collaborative tasks will beaffected. In this paper, we propose a synchronization method to supportcollaborative visualization. It considers how interaction with dynamicobjects is perceived by application participants under the existence ofnetwork latency, and remedies the motion trajectory of the dynamicobjects. It also handles the false positive and false negative collisiondetection problems. The new method is particularly well designed forhandling content changes due to unpredictable user interventions orobject collisions. We demonstrate the effectiveness of our methodthrough a number of experiments.

We describe a concurrent visualization pipeline designed for operation in a production supercomputing environment.The facility was initially developed on the NASA Ames "Columbia" supercomputer for a massively parallel forecast model (GEOS4).During the ...

We describe a concurrent visualization pipeline designed for operation in a production supercomputing environment.The facility was initially developed on the NASA Ames "Columbia" supercomputer for a massively parallel forecast model (GEOS4).During the 2005 Atlantic hurricane season, GEOS4 was run 4 times a day under tight time constraints so that its output could be included in an ensemble prediction that was made available to forecasters at the National Hurricane Center.Given this time-critical context, we designed a configurable concurrent pipeline to visualize multiple global fields without significantly affecting the runtime model performance or reliability.We use MPEG compression of the accruing images to facilitate live low-bandwidth distribution of multiple visualization streams to remote sites.We also describe the use of our concurrent visualization framework with a global ocean circulation model, which provides a 864-fold increase in the temporal resolution of practically achievable animations.In both the atmospheric and oceanic circulation models, the application scientists gained new insights into their model dynamics, due to the high temporal resolution animations attainable.

Navigating through large-scale virtual environments such as simulations of the astrophysical Universe is difficult. The huge spatial range of astronomical models and the dominance of empty space make it hard for users to travel across cosmological scales ...

Navigating through large-scale virtual environments such as simulations of the astrophysical Universe is difficult. The huge spatial range of astronomical models and the dominance of empty space make it hard for users to travel across cosmological scales effectively, and the problem of wayfinding further impedes the user's ability to acquire reliable spatial knowledge of astronomical contexts. We introduce a new form of technique called the scalable world-in-miniature (WIM) map as a unifying interface to facilitate travel and wayfinding in the virtual environment spanning gigantic spatial scales: Scale controls enable smooth, rapid transitions among widely separated regions; logarithmically mapped miniature spaces offer a global overview mode when the full context is too large; 3D landmarks represented in the WIM are enhanced by scale, positional, and directional cues to augment spatial context awareness; a series of navigation models are incorporated into the scalable WIM to improve the performance of travel tasks posed by the unique characteristics of virtual cosmic exploration. The scalable WIM user interface supports an improved physical navigation experience and assists pragmatic cognitive understanding of a visualization context that incorporates the features of large-scale astronomy.

This paper describes a set of visual cues of contact designed to improve the interactive manipulation of virtual objects inindustrial assembly/maintenance simulations. These visual cues display information of proximity, contact and effort between virtualobjects ...

This paper describes a set of visual cues of contact designed to improve the interactive manipulation of virtual objects inindustrial assembly/maintenance simulations. These visual cues display information of proximity, contact and effort between virtualobjects when the user manipulates a part inside a digital mock-up. The set of visual cues encloses the apparition of glyphs (arrow, disk, or sphere) when the manipulated object is close or in contactwith another part of the virtual environment. Light sources can also be added at the level of contact points. A filtering technique isproposed to decrease the number of glyphs displayed at the same time. Various effects -such as change in color, change in size, anddeformation of shape- can be applied to the glyphs as a function of proximity with other objects or amplitude of the contact forces. A preliminary evaluation was conducted to gather the subjective preference of a group of participants during the simulation of anautomotive assembly operation. The collected questionnaires showed that participants globally appreciated our visual cues of contact.The changes in color appeared to be preferred concerning the display of distances and proximity information. Size changes anddeformation effects appeared to be preferred in terms of perception of contact forces between the parts. Last, light sources wereselected to focus the attention of the user on the contact areas.

Many sophisticated techniques for the visualization of volumetric data such as medical data have been published. While existing techniques are mature from a technical point of view, managing the complexity of visual parameters is still difficult for ...

Many sophisticated techniques for the visualization of volumetric data such as medical data have been published. While existing techniques are mature from a technical point of view, managing the complexity of visual parameters is still difficult for nonexpert users. To this end, this paper presents new ideas to facilitate the specification of optical properties for direct volume rendering. We introduce an additional level of abstraction for parametric models of transfer functions. The proposed framework allows visualization experts to design high-level transfer function models which can intuitively be used by non-expert users. The results are user interfaces which provide semantic information for specialized visualization problems. The proposed method is based on principal component analysis as well as on concepts borrowed from computer animation.

In multiresolution volume visualization, a visual representation of level-of-detail (LOD) quality is important for us to examine, compare, and validate different LOD selection algorithms. While traditional methods rely on ultimate images for quality ...

In multiresolution volume visualization, a visual representation of level-of-detail (LOD) quality is important for us to examine, compare, and validate different LOD selection algorithms. While traditional methods rely on ultimate images for quality measurement, we introduce the LOD map - an alternative representation of LOD quality and a visual interface for navigating multiresolution data exploration. Our measure for LOD quality is based on the formulation of entropy from information theory. The measure takes into account the distortion and contribution of multiresolution data blocks. A LOD map is generated through the mapping of key LOD ingredients to a treemap representation. The ordered treemap layout is used for relative stable update of the LOD map when the view or LOD changes. This visual interface not only indicates the quality of LODs in an intuitive way, but also provides immediate suggestions for possible LOD improvement through visually-striking features. It also allows us to compare different views and perform rendering budget control. A set of interactive techniques is proposed to make the LOD adjustment a simple and easy task. We demonstrate the effectiveness and efficiency of our approach on large scientific and medical data sets.

Current practice in particle visualization renders particle position data directly onto the screen as points or glyphs. Using a camera placed at a fixed position, particle motions can be visualized by rendering trajectories or by animations. Applying ...

Current practice in particle visualization renders particle position data directly onto the screen as points or glyphs. Using a camera placed at a fixed position, particle motions can be visualized by rendering trajectories or by animations. Applying such direct techniques to large, time dependent particle data sets often results in cluttered images in which the dynamic properties of the underlying system are difficult to interpret.In this case study we take an alternative approach to the visualization of ion motions. Instead of rendering ion position data directly, we first extract meaningful motion information from the ion position data and then map this information onto geometric primitives. Our goal is to produce high-level visualizations that reflect the physicists' way of thinking about ion dynamics. Parameterized geometric icons are defined to encode motion information of clusters of related ions. In addition, a parameterized camera control mechanism is used to analyze relative instead of only absolute ion motions. We apply the techniques to simulations of Fourier transform mass spectrometry (FTMS) experiments. The data produced by such simulations can amount to $5\cdot10^4$ ions and $10^5$ timesteps. This paper discusses the requirements, design and informal evaluation of the implemented system.

A method for the semi-automatic detection and visualization of defects in models of nematic liquid crystals (NLCs) is introduced; this method is suitable for unstructured models, a previously unsolved problem. The detected defects---also known as \emph{disclinations}---are ...

A method for the semi-automatic detection and visualization of defects in models of nematic liquid crystals (NLCs) is introduced; this method is suitable for unstructured models, a previously unsolved problem. The detected defects---also known as \emph{disclinations}---are regions were the alignment of the liquid crystal rapidly changes over space; these defects play a large role in the physical behavior of the NLC substrate. Defect detection is based upon a measure of total angular change of crystal orientation (the \emph{director}) over a node neighborhood via the use of a nearest neighbor path. Visualizations based upon the detection algorithm clearly identifies complete defect regions as opposed to incomplete visual descriptions provided by cutting-plane and isosurface approaches. The introduced techniques are currently in use by scientists studying the dynamics of defect change.

When a heavy fluid is placed above a light fluid, tiny vertical perturbations in the interface create a characteristic structure of rising bubbles and falling spikes known as Rayleigh-Taylor instability. Rayleigh-Taylor instabilities have received much ...

When a heavy fluid is placed above a light fluid, tiny vertical perturbations in the interface create a characteristic structure of rising bubbles and falling spikes known as Rayleigh-Taylor instability. Rayleigh-Taylor instabilities have received much attention over the past half-century because of their importance in understanding many natural and man-made phenomena, ranging from the rate of formation of heavy elements in supernovae to the design of capsules for Inertial Confinement Fusion. We present a new approach to analyze Rayleigh-Taylor instabilities in which we extract a hierarchical segmentation of the mixing envelope surface to identify bubbles and analyze analogous segmentations of fields on the original interface plane. We compute meaningful statistical information that reveals the evolution of topological features and corroborates the observations made by scientists. We also use geometric tracking to follow the evolution of single bubbles and highlight merge/split events leading to the formation of the large and complex structures characteristic of the later stages. In particular we (i) Provide a formal definition of a bubble; (ii) Segment the envelope surface to identify bubbles; (iii) Provide a multi-scale analysis technique to produce statistical measures of bubble growth; (iv) Correlate bubble measurements with analysis of fields on the interface plane; (v) Track the evolution of individual bubbles over time. Our approach is based on the rigorous mathematical foundations of Morse theory and can be applied to a more general class of applications.

The Network for Computational Nanotechnology (NCN) has developed a science gateway at nanoHUB.org for nanotechnology education and research. Remote users can browse through online seminars and courses, and launch sophisticated nanotechnology simulation ...

The Network for Computational Nanotechnology (NCN) has developed a science gateway at nanoHUB.org for nanotechnology education and research. Remote users can browse through online seminars and courses, and launch sophisticated nanotechnology simulation tools, all within their web browser. Simulations are supported by a middleware that can route complex jobs to grid supercomputing resources.But what is truly unique about the middleware is the way that it uses hardware accelerated graphics to support both problem setup and result visualization. This paper describes the design and integration of a remote visualization framework into the nanoHUB for interactive visual analytics of nanotechnology simulations. Our services flexibly handle a variety of nanoscience simulations, render them utilizing graphics hardware acceleration in a scalable manner, and deliver them seamlessly through the middleware to the user. Rendering is done only on-demand, as needed, so each graphics hardware unit can simultaneously support many user sessions. Additionally, a novel node distribution scheme further improves our system's scalability. Our approach is not only efficient but also cost-effective. Only a half-dozen render nodes are anticipatedto support hundreds of active tool sessions on the nanoHUB. Moreover, this architecture and visual analytics environment provides capabilities that can serve many areas of scientific simulation and analysis beyond nanotechnology with its ability to interactively analyze and visualize multivariate scalar and vector fields.

In this paper we describe a GPU-based technique for creating illustrative visualization through interactive manipulation of volumetric models. It is partly inspired by medical illustrations, where it is common to depict cuts and deformation in order ...

In this paper we describe a GPU-based technique for creating illustrative visualization through interactive manipulation of volumetric models. It is partly inspired by medical illustrations, where it is common to depict cuts and deformation in order to provide a better understanding of anatomical and biological structures or surgical processes, and partly motivated by the need for a real-time solution that supports the specification and visualization of such illustrative manipulation. We propose two new feature-aligned techniques, namely surface alignment and segment alignment, and compare them with the axis-aligned techniques which was reported in previous work on volume manipulation. We also present a mechanism for defining features using texture volumes, and methods for computing correct normals for the deformed volume in respect to different alignments. We describe a GPU-based implementation to achieve real-time performance of the techniques and a collection of manipulation operators including peelers, retractors, pliers and dilators which are adaptations of the metaphors and tools used in surgical procedures and medical illustrations. Our approach is directly applicable in medical and biological illustration, and we demonstrate how it works as an interactive tool for focus+context visualization, as well as a generic technique for volume graphics.

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve ...

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve the general problem of occlusion. In many cases an object of interest is occluded by other structures. While transparency or cutaways can be used to reveal a focus object, these techniques remove parts of the context information. Exploded views, on the other hand, do not suffer from this drawback. Our approach employs a force-based model: the volume is divided into a part configuration controlled by a number of forces and constraints. The focus object exerts an explosion force causing the parts to arrange according to the given constraints. We show that this novel and flexible approach allows for a wide variety of explosion-based visualizations including view-dependent explosions. Furthermore, we present a high-quality GPU-based volume ray casting algorithm for exploded views which allows rendering and interaction at several frames per second.

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve ...

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve the general problem of occlusion. In many cases an object of interest is occluded by other structures. While transparency or cutaways can be used to reveal a focus object, these techniques remove parts of the context information. Exploded views, on the other hand, do not suffer from this drawback. Our approach employs a force-based model: the volume is divided into a part configuration controlled by a number of forces and constraints. The focus object exerts an explosion force causing the parts to arrange according to the given constraints. We show that this novel and flexible approach allows for a wide variety of explosion-based visualizations including view-dependent explosions. Furthermore, we present a high-quality GPU-based volume ray casting algorithm for exploded views which allows rendering and interaction at several frames per second.

Video visualization is a computation process that extracts meaningful information from original video data sets and conveys the extracted information to users in appropriate visual representations. This paper presents a broad treatment of the subject, ...

Video visualization is a computation process that extracts meaningful information from original video data sets and conveys the extracted information to users in appropriate visual representations. This paper presents a broad treatment of the subject, following a typical research pipeline involving concept formulation, system development, a path-finding user study, and a field trial with real application data. In particular, we have conducted a fundamental study on the visualization of motion events in videos. We have, for the first time, deployed flow visualization techniques in video visualization. We have compared the effectiveness of different abstract visual representations of videos. We have conducted a user study to examine whether users are able to learn to recognize visual signatures of motions, and to assist in the evaluation of different visualization techniques. We have applied our understanding and the developed techniques to a set of application video clips. Our study has demonstrated that video visualization is both technically feasible and cost-effective. It has provided the first set of evidence confirming that ordinary users can be accustomed to the visual features depicted in video visualizations, and can learn to recognize visual signatures of a variety of motion events.

Centralized techniques have been used until now when automatically calibrating (both geometrically and photometrically) large high-resolution displays created by tiling multiple projectors in a 2D array. A centralized server managed all the projectors ...

Centralized techniques have been used until now when automatically calibrating (both geometrically and photometrically) large high-resolution displays created by tiling multiple projectors in a 2D array. A centralized server managed all the projectors and also the camera(s) used to calibrate the display. In this paper, we propose an asynchronous distributed calibration methodology via a display unit called the plug-and-play projector (PPP). The PPP consists of a projector, camera, computation and communication unit, thus creating a self-sufficient module that enables an asynchronous distributed architecture for multi-projector displays. We present a single-program-multiple-data (SPMD) calibration algorithm that runs on each PPP and achieves a truly scalable and reconfigurable display without any input from the user. It instruments novel capabilities like adding/removing PPPs from the display dynamically, detecting faults, and reshaping the display to a reasonable rectangular shape to react to the addition/removal/faults. To the best of our knowledge, this is the first attempt to realize a completely asynchronous and distributed calibration architecture and methodology for multi-projector displays.

Animation is an effective way to show how time-varying phenomena evolve over time. A key issue of generating a good animation is to select ideal views through which the user can perceive the maximum amount of information from the time-varying dataset. ...

Animation is an effective way to show how time-varying phenomena evolve over time. A key issue of generating a good animation is to select ideal views through which the user can perceive the maximum amount of information from the time-varying dataset. In this paper, we first propose an improved view selection method for static data. The method measures the quality of a static view by analyzing the opacity, color and curvature distributions of the corresponding volume rendering images from the given view. Our view selection metric prefers an even opacity distribution with a larger projection area, a larger area of salient features' colors with an even distribution among the salient features, and more perceived curvatures. We use this static view selection method and a dynamic programming approach to select time-varying views. The time-varying view selection maximizes the information perceived from the time-varying dataset based on the constraints that the time-varying view should show smooth changes of direction and near-constant speed. We also introduce a method that allows the user to generate a smooth transition between any two views in a given time step, with the perceived information maximized as well. By combining the static and dynamic view selection methods, the users are able to generate a time-varying view that shows the maximum amount of information from a time-varying data set.

We present empirical studies that consider the effects of stereopsis and simulated aerial perspective on depth perception in translucent volumes.We consider a purely absorptive lighting model, in which light is not scattered or reflected, but is simply ...

We present empirical studies that consider the effects of stereopsis and simulated aerial perspective on depth perception in translucent volumes.We consider a purely absorptive lighting model, in which light is not scattered or reflected, but is simply absorbed as it passes through the volume.A purely absorptive lighting model is used, for example, when rendering digitally reconstructed radiographs (DRRs), which are synthetic X--ray images reconstructed from CT volumes.Surgeons make use of DRRs in planning and performing operations, so an improvement of depth perception in DRRs may help diagnosis and surgical planning.

This paper is a contribution to the literature on perceptually optimal visualizations of layered three-dimensional surfaces. Specifically, we develop guidelines for generating texture patterns, which, when tiled on two overlapped surfaces, minimize confusion ...

This paper is a contribution to the literature on perceptually optimal visualizations of layered three-dimensional surfaces. Specifically, we develop guidelines for generating texture patterns, which, when tiled on two overlapped surfaces, minimize confusion in depth-discrimination and maximize the ability to localize distinct features. We design a parameterized texture space and explore this texture space using a "human in the loop" experimental approach. Subjects are asked to rate their ability to identify Gaussian bumps on both upper and lower surfaces of noisy terrain fields. Their ratings direct a genetic algorithm, which selectively searches the texture parameter space to find fruitful areas. Data collected from these experiments are analyzed to determine what combinations of parameters work well and to develop texture generation guidelines. Data analysis methods include ANOVA, linear discriminant analysis, decision trees, and parallel coordinates. To confirm the guidelines, we conduct a post-analysis experiment, where subjects rate textures following our guidelines against textures violating the guidelines. Across all subjects, textures following the guidelines consistently produce high rated textures on an absolute scale, and are rated higher than those that did not follow the guidelines.

We present an evaluation of a parameterized set of 2D icon-based visualization methods where we quantified how perceptual interactions among visual elements affect efficient data exploration. During the experiment, subjects quantified three different ...

We present an evaluation of a parameterized set of 2D icon-based visualization methods where we quantified how perceptual interactions among visual elements affect efficient data exploration. During the experiment, subjects quantified three different design factors for each method: the spatial resolution it could represent, the number of data values it could display at each point, and the degree to which it is visually linear. The class of visualization methods includes Poisson-disk distributed icons where icon size, icon spacing, and icon brightness can be set to a constant or coupled to data values from a 2D scalar field. By only coupling one of those visual components to data, we measured filtering interference for all three design factors. Filtering interference characterizes how different levels of the constant visual elements affect the evaluation of the data-coupled element. Our novel experimental methodology allowed us to generalize this perceptual information, gathered using ad-hoc artificial datasets, onto quantitative rules for visualizing real scientific datasets. This work also provides a framework for evaluating visualizations of multi-valued data that incorporate additional visual cues, such as icon orientation or color.

This paper presents a method for occlusion-free animation of geographical landmarks, and its application to a new type of car navigation system in which driving routes of interest are always visible in mountain areas.This is achieved by animating a nonperspective ...

This paper presents a method for occlusion-free animation of geographical landmarks, and its application to a new type of car navigation system in which driving routes of interest are always visible in mountain areas.This is achieved by animating a nonperspective image where geographical landmarks such as mountain tops and roads are rendered as if they are seen from different viewpoints.The contribution of this paper lies in formulating the nonperspective navigation as an inverse problem of continuously deforming a 3D terrain surface from the 2D screen arrangement of the geographical landmarks.The present approach provides a perceptually reasonable compromise between the navigation clarity and visual realism where the corresponding nonperspective view is fully augmented by assigning appropriate textures and shading effects to the terrain surface according to its geometry.An eye tracking experiment are conducted to prove that the present approach actually exhibits visually-pleasing navigation frames where users can clearly recognize the shape of the driving route without occlusion, together with the spatial configuration of geographical landmarks in its neighborhood.

We present GyVe, an interactive visualization tool for understanding structure in sparse three-dimensional (3D) point data. The scientific goal driving the tool's development is to determine the presence of filaments and voids as defined by inferred ...

We present GyVe, an interactive visualization tool for understanding structure in sparse three-dimensional (3D) point data. The scientific goal driving the tool's development is to determine the presence of filaments and voids as defined by inferred 3D galaxy positions within the Horologium-Reticulum supercluster (HRS). GyVe provides visualization techniques tailored to examine structures defined by the intercluster galaxies. Specific techniques include: interactive user control to move between a global overview and local viewpoints, labelled axes and curved drop lines to indicate positions in the astronomical RA-DEC-cz coordinate system, torsional rocking and stereo to enhance 3D perception, and geometrically distinct glyphs to show potential correlation between intercluster galaxies and known clusters. We discuss the rationale for each design decision and review the success of the techniques in accomplishing the scientific goals. In practice, GyVe has been useful for gaining intuition about structures that were difficult to perceive with 2D projection techniques alone. For example, during their initial session with GyVe, our collaborators quickly confirmed scientific conclusions regarding the large-scale structure of the HRS previously obtained over months of study with 2D projections and statistical techniques. Further use of GyVe revealed the spherical shape of voids and showed that a presumed filament was actually two disconnected structures.

Meteorological research involves the analysis of multi-field, multi-scale, and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. Unfortunately, traditional atmospheric ...

Meteorological research involves the analysis of multi-field, multi-scale, and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. Unfortunately, traditional atmospheric visualization systems only provide tools to view a limited number of variables and small segments of the data. These tools are often restricted to two-dimensional contour or vector plots or three-dimensional isosurfaces. The meteorologist must mentally synthesize the data from multiple plots to glean the information needed to produce a coherent picture of the weather phenomenon of interest. In order to provide better tools to meteorologists and reduce system limitations, we have designed an integrated atmospheric visual analysis and exploration system for interactive analysis of weather data sets. Our system allows for the integrated visualization of 1D, 2D, and 3D atmospheric data sets in common meteorological grid structures and utilizes a variety of rendering techniques. These tools provide meteorologists with new abilities to analyze their data and answer questions on regions of interest, ranging from physics-based atmospheric rendering to illustrative rendering containing particles and glyphs.In this paper, we will discuss the use and performance of our visual analysis for two important meteorological applications. The first application is warm rain formation in small cumulus clouds. Here, our three-dimensional, interactive visualization of modeled drop trajectories within spatially correlated fields from a cloud simulation has provided researchers with new insight. Our second application is improving and validating severe storm models, specifically the Weather Research and Forecasting (WRF) model. This is done through correlative visualization of WRF model and experimental Doppler storm data.

Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization ...

Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization since they tend to be densely packed in small volumes of tissue. This makes it difficult for an observer to interpret useful patterns from the data or trace individual fibers. In this paper we describe several methods for dealing with large amounts of thread-like data, such as data sets collected using Knife-Edge Scanning Microscopy (KESM) and Serial Block-Face Scanning Electron Microscopy (SBF-SEM). These methods allow us to collect volumetric data from embedded samples of whole-brain tissue. The neuronal and microvascular data that we acquire consists of thin, branching structures extending over very large regions. Traditional visualization schemes are not sufficient to make sense of the large, dense, complex structures encountered. In this paper, we address three methods to allow a user to explore a fiber network effectively. We describe interactive techniques for rendering large sets of neurons using self-orienting surfaces implemented on the GPU.We also present techniques for rendering fiber networks in a way that provides useful information about flow and orientation. Third, a global illumination framework is used to create high-quality visualizations that emphasize the underlying fiber structure. Implementation details, performance, and advantages and disadvantages of each approach are discussed.

We present a comparative visualization of the acoustic simulation results obtained by two different approaches that were combined into a single simulation algorithm. The rst method solves the wave equation on a volume grid based on nite elements. The ...

We present a comparative visualization of the acoustic simulation results obtained by two different approaches that were combined into a single simulation algorithm. The rst method solves the wave equation on a volume grid based on nite elements. The second method, phonon tracing, is a geometric approach that we have previously developed for interactive simulation, visualization and modeling of room acoustics. Geometric approaches of this kind are more efcient than FEM in the high and medium frequency range. For low frequencies they fail to represent diffraction, which on the other hand can be simulated properly by means of FEM. When combining both methods we need to calibrate them properly and estimate in which frequency range they provide comparable results. For this purpose we use an acoustic metric called gain and display the resulting error. Furthermore we visualize interference patterns, since these depend not only on diffraction, but also exhibit phase-dependent amplication and neutralization effects.

Diffusion tensor imaging is of high value in neurosurgery, providing information about the location of white matter tracts in the human brain. For their reconstruction, streamline techniques commonly referred to as fiber tracking model the underlying ...

Diffusion tensor imaging is of high value in neurosurgery, providing information about the location of white matter tracts in the human brain. For their reconstruction, streamline techniques commonly referred to as fiber tracking model the underlying fiber structures and have therefore gained interest. To meet the requirements of surgical planning and to overcome the visual limitations of line representations, a new real-time visualization approach of high visual quality is introduced. For this purpose, textured triangle strips and point sprites are combined in a hybrid strategy employing GPU programming. The triangle strips follow the fiber streamlines and are textured to obtain a tube-like appearance. A vertex program is used to orient the triangle strips towards the camera. In order to avoid triangle flipping in case of fiber segments where the viewing and segment direction are parallel, a correct visual representation is achieved in these areas by chains of point sprites. As a result, a high quality visualization similar to tubes is provided allowing for interactive multimodal inspection. Overall, the presented approach is faster than existing techniques of similar visualization quality and at the same time allows for real-time rendering of dense bundles encompassing a high number of fibers, which is of high importance for diagnosis and surgical planning.

Topological methods are often used to describe flow structures in fluid dynamics and topological flow field analysis usually relies on the invariants of the associated tensor fields. A visual impression of the local properties of tensor fields is often ...

Topological methods are often used to describe flow structures in fluid dynamics and topological flow field analysis usually relies on the invariants of the associated tensor fields. A visual impression of the local properties of tensor fields is often complex and the search of a suitable technique for achieving this is an ongoing topic in visualization. This paper introduces and assesses a method of representing the topological properties of tensor fields and their respective flow patterns with the use of colors. First, a tensor norm is introduced, which preserves the properties of the tensor and assigns the tensor invariants to values of the RGB color space. Secondly, the RGB colors of the tensor invariants are transferred to corresponding hue values as an alternative color representation. The vectorial tensor invariants field is reduced to a scalar hue field and visualization of iso-surfaces of this hue value field allows us to identify locations with equivalent flow topology. Additionally highlighting by the maximum of the eigenvalue difference field reflects the magnitude of the structural change of the flow. The method is applied on a vortex breakdown flow structure inside a cylinder with a rotating lid.

A glyph-based method for visualizing the nematic liquid crystal alignment tensor is introduced. Unlike previous approaches, the glyph is based upon physically-linked metrics, not offsets of the eigenvalues. These metrics, combined with a set of superellipsoid ...

A glyph-based method for visualizing the nematic liquid crystal alignment tensor is introduced. Unlike previous approaches, the glyph is based upon physically-linked metrics, not offsets of the eigenvalues. These metrics, combined with a set of superellipsoid shapes, communicate both the strength of the crystal's uniaxial alignment and the amount of biaxiality. With small modifications, our approach can visualize any real symmetric traceless tensor.

Isosurfaces are ubiquitous in many fields, including visualization, graphics, and vision. They are often the main computational component of important processing pipelines (e.g. , surface reconstruction), and are heavily used in practice. The classical ...

Isosurfaces are ubiquitous in many fields, including visualization, graphics, and vision. They are often the main computational component of important processing pipelines (e.g. , surface reconstruction), and are heavily used in practice. The classical approach to compute isosurfaces is to apply the Marching Cubes algorithm, which although robust and simple to implement, generates surfaces that require additional processing steps to improve triangle quality and mesh size. An important issue is that in some cases, the surfaces generated by Marching Cubes are irreparably damaged, and important details are lost which can not be recovered by subsequent processing. The main motivation of this work is to develop a technique capable of constructing high-quality and high-fidelity isosurfaces.We propose a new advancing front technique that is capable of creating high-quality isosurfaces from regular and irregular volumetric datasets. Our work extends the guidance field framework of Schreiner et al. to implicit surfaces, and improves it in significant ways. In particular, we describe a set of sampling conditions that guarantee that surface features will be captured by the algorithm. We also describe an efficient technique to compute a minimal guidance field, which greatly improves performance. Our experimental results show that our technique can generate high-quality meshes from complex datasets.

Current computer architectures employ caching to improve the performance of a wide variety of applications.One of the main characteristics of such cache schemes is the use of block fetching whenever an uncached data element is accessed.To maximize the ...

Current computer architectures employ caching to improve the performance of a wide variety of applications.One of the main characteristics of such cache schemes is the use of block fetching whenever an uncached data element is accessed.To maximize the benefit of the block fetching mechanism, we present novel cache-aware and cache-oblivious layouts of surface and volume meshes that improve the performance of interactive visualization and geometric processing algorithms. Based on a general I/O model, we derive new cache-aware and cache-oblivious metrics that have high correlations with the number of cache misses when accessing a mesh.In addition to guiding the layout process, our metrics can be used to quantify the quality of a layout, e.g. for comparing different layouts of the same mesh and for determining whether a given layout is amenable to significant improvement. We show that layouts of unstructured meshes optimized for our metrics result in improvements over conventional layouts in the performance of visualization applications such as isosurface extraction and view-dependent rendering. Moreover, we improve upon recent cache-oblivious mesh layouts in terms of performance, applicability, and accuracy.

We propose an out-of-core method for creating semi-regular surface representations from large input surface meshes. Our approach is based on a streaming implementation of the MAPS remesher of Lee et al. Our remeshing procedure consists of two stages. ...

We propose an out-of-core method for creating semi-regular surface representations from large input surface meshes. Our approach is based on a streaming implementation of the MAPS remesher of Lee et al. Our remeshing procedure consists of two stages. First, a simplification process is used to obtain the base domain. During simplification, we maintain the mapping information between the input and the simplified meshes. The second stage of remeshing uses the mapping information to produce samples of the output semi-regular mesh. The out-of-core operation of our method is enabled by the synchronous streaming of a simplified mesh and the mapping information stored at the original vertices. The synchronicity of two streaming buffers is maintained using a specially designed write strategy for each buffer. Experimental results demonstrate the remeshing performance of the proposed method, as well as other applications that use the created mapping between the simplified and the original surface representations.

Computational simulations frequently generate solutions defined over very large tetrahedral volume meshes containing many millions of elements. Furthermore, such solutions may often be expressed using non-linear basis functions.Certain solution techniques, ...

Computational simulations frequently generate solutions defined over very large tetrahedral volume meshes containing many millions of elements. Furthermore, such solutions may often be expressed using non-linear basis functions.Certain solution techniques, such as discontinuous Galerkin methods, may even produce non-conforming meshes.Such data is difficult to visualize interactively, as it is far too large to fit in memory and many common data reduction techniques, such as mesh simplification, cannot be applied to non-conforming meshes.We introduce a point-based visualization system for interactive rendering of large, potentially non-conforming, tetrahedral meshes. We propose methods for adaptively sampling points from non-linear solution data and for decimating points at run time to fit GPU memory limits. Because these are streaming processes, memory consumption is independent of the input size. We also present an order-independent point rendering method that can efficiently render volumes on the order of 20 million tetrahedra at interactive rates.

The paper presents a set of combined techniques to enhance the real-time visualization of simple or complex molecules (up to order of $10^6$ atoms) space fill mode. The proposed approach includes an innovative technique for efficient computation and ...

The paper presents a set of combined techniques to enhance the real-time visualization of simple or complex molecules (up to order of $10^6$ atoms) space fill mode. The proposed approach includes an innovative technique for efficient computation and storage of ambient occlusion terms, a small set of GPU accelerated procedural impostors for space-fill and ball-and-stick rendering, and novel edge-cueing techniques. As a result, the user's understanding of the three-dimensional structure under inspection is strongly increased (even for still images), while the rendering still occurs in real time.

Large scale scientific simulation codes typically run on a cluster of CPUs that write/read time steps to/from a single file system. As data sets are constantly growing in size, this increasingly leads to I/O bottlenecks. When the rate at which data is ...

Large scale scientific simulation codes typically run on a cluster of CPUs that write/read time steps to/from a single file system. As data sets are constantly growing in size, this increasingly leads to I/O bottlenecks. When the rate at which data is produced exceeds the available I/O bandwidth, the simulation stalls and the CPUs are idle. Data compression can alleviate this problem by using some CPU cycles to reduce the amount of data needed to be transfered. Most compression schemes, however, are designed to operate offline and seek to maximize compression, notthroughput.Furthermore, they often require quantizing floating-point values onto a uniform integer grid, which disqualifies their use in applications where exact values must be retained. We propose a simple scheme for lossless, online compression of floating-point data that transparently integrates into the I/O ofmany applications.A plug-in scheme for data-dependent prediction makes our scheme applicable to a wide variety of data used invisualization, such as unstructured meshes, point sets, images, and voxel grids. We achieve state-of-the-art compression rates and speeds, the latter in part due to an improved entropy coder. We demonstrate that this significantly accelerates I/O throughput in real simulation runs. Unlike previous schemes, our method also adapts well to variable-precision floating-point and integer data.

In this paper we propose an approach in which interactive visualization and analysis are combined with batch tools for the processing of large data collections. Large and heterogeneous data collections are difficult to analyze and pose specific problems ...

In this paper we propose an approach in which interactive visualization and analysis are combined with batch tools for the processing of large data collections. Large and heterogeneous data collections are difficult to analyze and pose specific problems to interactive visualization. Application of the traditional interactive processing and visualization approaches as well as batch processing encounter considerable drawbacks for such large and heterogeneous data collections due to the amount and type of data. Computing resources are not sufficient for interactive exploration of the data and automated analysis has the disadvantage that the user has only limited control and feedback on the analysis process.In our approach, an analysis procedure with features and attributes of interest for the analysis is defined interactively. This procedure is used for off-line processing of large collections of data sets. The results of the batch process along with ``visual summaries'' are used for further analysis. Visualization is not only used for the presentation of the result, but also as a tool to monitor the validity and quality of the operations performed during the batch process. Operations such as feature extraction and attribute calculation of the collected data sets are validated by visual inspection. This approach is illustrated by an extensive case study, in which a collection of confocal microscopy data sets is analyzed.

In this paper, we show that histograms represent spatial function distributions with a nearest neighbour interpolation. We confirm that this results in systematic underrepresentation of transitional features of the data, and provide new insight why this ...

In this paper, we show that histograms represent spatial function distributions with a nearest neighbour interpolation. We confirm that this results in systematic underrepresentation of transitional features of the data, and provide new insight why this occurs. We further show that isosurface statistics, which use higher quality interpolation, give better representations of the function distribution. We also use our experimentally collected isosurface statistics to resolve some questions as to the formal complexity of isosurfaces.

We present an efficient point-based isosurface exploration system with high quality rendering. Our system incorporates two point-based isosurface extraction and visualization methods: edge splatting and the edge kernel method. In a volume, two neighboring ...

We present an efficient point-based isosurface exploration system with high quality rendering. Our system incorporates two point-based isosurface extraction and visualization methods: edge splatting and the edge kernel method. In a volume, two neighboring voxels define an edge. The intersection points between the active edges and the isosurface are used for exact isosurface representation. The point generation is incorporated in the GPU-based hardware-accelerated rendering, thus avoiding any overhead when changing the isovalue in the exploration. We call this method edge splatting. In order to generate high quality isosurface rendering regardless of the volume resolution and the view, we introduce an edge kernel method. The edge kernel upsamples the isosurface by subdividing every active cell of the volume data. Enough sample points are generated to preserve the exact shape of the isosurface defined by the trilinear interpolation of the volume data. By employing these two methods, we can achieve interactive isosurface exploration with high quality rendering.

We present a novel approach to out-of-core time-varying isosurface visualization. We attempt to interactively visualize time-varying datasets which are too large to fit into main memory using a technique which is dramatically different from existing ...

We present a novel approach to out-of-core time-varying isosurface visualization. We attempt to interactively visualize time-varying datasets which are too large to fit into main memory using a technique which is dramatically different from existing algorithms. Inspired by video encoding techniques, we examine the data differences between time steps to extract isosurface information. We exploit span space extraction techniques to retrieve operations necessary to update isosurface geometry from neighboring time steps. Because only the changes between time steps need to be retrieved from disk, I/O bandwidth requirements are minimized. We apply temporal compression to further reduce disk access and employ a point-based previewing technique that is refined in idle interaction cycles. Our experiments on computational simulation data indicate that this method is an extremely viable solution to large time-varying isosurface visualization. Our work advances the state-of-the-art by enabling all isosurfaces to be represented by a compact set of operations.

We propose a novel Persistent OcTree (POT) indexing structure for accelerating isosurface extraction and spatial filtering from volumetric data. This data structure efficiently handles a wide range of visualization problems such as the generation of ...

We propose a novel Persistent OcTree (POT) indexing structure for accelerating isosurface extraction and spatial filtering from volumetric data. This data structure efficiently handles a wide range of visualization problems such as the generation of view-dependent isosurfaces, ray tracing, and isocontour slicing for high dimensional data. POT can be viewed as a hybrid data structure between the interval tree and the Branch-On-Need Octree (BONO) in the sense that it achieves the asymptotic bound of the interval tree for identifying the active cells corresponding to an isosurface and is more efficient than BONO for handling spatial queries. We encode a compact octree for each isovalue. Each such octree contains only the corresponding active cells, in such a way that the combined structure has linear space. The inherent hierarchical structure associated with the active cells enables very fast filtering of the active cells based on spatial constraints. We demonstrate the effectiveness of our approach by performing view-dependent isosurfacing on a wide variety of volumetric data sets and 4D isocontour slicing on the time-varying Richtmyer-Meshkov instability dataset.

Volumetric datasets with multiple variables on each voxel over multiple time steps are often complex, especially when considering the exponentially large attribute space formed by the variables in combination with the spatial and temporal dimensions. ...

Volumetric datasets with multiple variables on each voxel over multiple time steps are often complex, especially when considering the exponentially large attribute space formed by the variables in combination with the spatial and temporal dimensions. It is intuitive, practical, and thus often desirable, to interactively select a subset of the data from within that high-dimensional value space for efficient visualization. This approach is straightforward to implement if the dataset is small enough to be stored entirely in-core. However, to handle datasets sized at hundreds of gigabytes and beyond, this simplistic approach becomes infeasible and thus, more sophisticated solutions are needed. In this work, we developed a system that supports efficient visualization of an arbitrary subset, selected by range-queries, of a large multivariate time-varying dataset. By employing specialized data structures and schemes of data distribution, our system can leverage a large number of networked computers as parallel data servers, and guarantees a near optimal load-balance. We demonstrate our system of scalable data servers using two large time-varying simulation datasets.

We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by ...

We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two Gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming.

We describe a new progressive technique that allows real-time rendering of extremely large tetrahedral meshes.Our approach uses a client-server architecture to incrementally stream portions of the mesh from a server to a client which refines the quality ...

We describe a new progressive technique that allows real-time rendering of extremely large tetrahedral meshes.Our approach uses a client-server architecture to incrementally stream portions of the mesh from a server to a client which refines the quality of the approximate rendering until it converges to a full quality rendering. The results of previous steps are re-used in each subsequent refinement, thus leading to an efficient rendering.Our novel approach keeps very little geometry on the client and works by refining a set of rendered images at each step.Our interactive representation of the dataset is efficient, light-weight, and high quality.We present a framework for the exploration of large datasets stored on a remote server with a thin client that is capable of rendering and managing full quality volume visualizations.

Accurately representing higher-order singularities of vector fields defined on piecewise linear surfaces is a non-trivial problem. In this work, we introduce a concise yet complete interpolation scheme of vector fields on arbitrary triangulated surfaces. ...

Accurately representing higher-order singularities of vector fields defined on piecewise linear surfaces is a non-trivial problem. In this work, we introduce a concise yet complete interpolation scheme of vector fields on arbitrary triangulated surfaces. The scheme enablesarbitrary singularities to be represented at vertices} The representation can be considered as a facet-based "encoding" of vector fields on piecewise linear surfaces. The vector field is described in polar coordinates over each facet, with a facet edge being chosen as the reference to define the angle. An integer called theperiod jump is associated to each edge of the triangulation to remove the ambiguity when interpolating the direction of the vector fieldbetween two facets that share an edge. To interpolate the vector field, we first linearlyinterpolate the angle of rotation of the vectors along the edges of the facet graph. Then, we use a variant ofNielson's side-vertex scheme to interpolate the vector field over the entire surface. With our representation, we remove the bound imposed on the complexity of singularities that a vertex can represent by its connectivity. This boundis a limitation generally exists in vertex-based linear schemes. Furthermore, using our data structure, the index of a vertex of a vector field can be combinatorily determined.We show the simplicity of the interpolation scheme with a GPU-accelerated algorithm for a LIC-based visualization of the so-defined vector fields, operating in image space. We demonstrate the algorithm applied to various vector fields on curved surfaces.

We present visualization tools for analyzing molecular simulations of liquid crystal (LC) behavior. The simulation data consists of terabytes of data describing the position and orientation of every molecule in the simulated system over time. Condensed ...

We present visualization tools for analyzing molecular simulations of liquid crystal (LC) behavior. The simulation data consists of terabytes of data describing the position and orientation of every molecule in the simulated system over time. Condensed matter physicists study the evolution of topological defects in these data, and our visualization tools focus on that goal. We first convert the discrete simulation data to a sampled version of a continuous second-order tensor field and then use combinations of visualization methods to simultaneously display combinations of contractions of the tensor data, providing an interactive environment for exploring these complicated data. The system, built using AVS, employs colored cutting planes, colored isosurfaces, and colored integral curves to display fields of tensor contractions including Westin's scalar cl, cp, and cs metrics and the principal eigenvector. Our approach has been in active use in the physics lab for over a year. It correctly displays structures already known; it displays the data in a spatially and temporally smoother way than earlier approaches, avoiding confusing grid effects and facilitating the study of multiple time steps; it extends the use of tools developed for visualizing diffusion tensor data, re-interpreting them in the context of molecular simulations; and it has answered long-standing questions regarding the orientation of molecules around defects and the conformational changes of the defects

A common goal of multivariate visualization is to enable data inspection at discrete points, while also illustrating the larger-scale continuous structures.In diffusion tensor visualization, glyphs are typically used to meet the first goal, and methods ...

A common goal of multivariate visualization is to enable data inspection at discrete points, while also illustrating the larger-scale continuous structures.In diffusion tensor visualization, glyphs are typically used to meet the first goal, and methods suchas texture synthesis or fiber tractography can address the second.We adapt particle systems originally developed for surface modeling and anisotropic mesh generation to enhance the utility of glyph-based tensor visualizations.By carefully distributing glyphs throughout the field (either on a slice, or in the volume) into a dense packing, using potential energy profiles shaped by the local tensor value, we remove undue visual emphasis of the regular sampling grid of the data, and the underlying continuous features become more apparent.The method is demonstrated on a DT-MRI scan of a patient with a brain tumor.

In this article we propose a box spline and its variants for reconstructing volumetric data sampled on the Cartesian lattice. In particular we present a tri-variate box spline reconstruction kernel that is superior to tensor product reconstruction schemes ...

In this article we propose a box spline and its variants for reconstructing volumetric data sampled on the Cartesian lattice. In particular we present a tri-variate box spline reconstruction kernel that is superior to tensor product reconstruction schemes in terms of recovering the proper Cartesian spectrum of the underlying function. This box spline produces a $C^2$ reconstruction that can be considered as a three dimensional extension of the well known Zwart-Powell element in 2D. While its smoothness and approximation power are equivalent to those of the tri-cubic B-spline, we illustrate the superiority of this reconstruction on functions sampled on the Cartesian lattice and contrast it to tensor product B-splines. Our construction is validated through a Fourier domain analysis of the reconstruction behavior of this box spline.Moreover, we present a stable method for evaluation of this box spline by means of a decomposition. Through a convolution, this decomposition reduces the problem to evaluation of a four directional box spline that we previously published in its explicit closed form [8].

Recent advances in algorithms and graphics hardware have opened the possibility to render tetrahedral grids at interactive rates on commodity PCs. This paper extends on this work in that it presents a direct volume rendering method for such grids which ...

Recent advances in algorithms and graphics hardware have opened the possibility to render tetrahedral grids at interactive rates on commodity PCs. This paper extends on this work in that it presents a direct volume rendering method for such grids which supports both current and upcoming graphics hardware architectures, large and deformable grids, as well as different rendering options. At the core of our method is the idea to perform the sampling of tetrahedral elements along the view rays entirely in local barycentric coordinates. Then, sampling requires minimum GPU memory and texture access operations, and it maps efficiently onto a feed-forward pipeline of multiple stages performing computation and geometry construction. We propose to spawn rendered elements from one single vertex. This makes the method amenable to upcoming Direct3D 10 graphics hardware which allows to create geometry on the GPU. By only modifying the algorithm slightly it can be used to render per-pixel iso-surfaces and to perform tetrahedral cell projection. As our method neither requires any pre-processing nor an intermediate grid representation it can efficiently deal with dynamic and large 3D meshes.

In this paper we investigate the effects of function composition in the form g(f(x)) = h(x) by means of a spectral analysis of h. We decompose the spectral description of h(x) into a scalar product of the spectral description of g(x) and a term that ...

In this paper we investigate the effects of function composition in the form g(f(x)) = h(x) by means of a spectral analysis of h. We decompose the spectral description of h(x) into a scalar product of the spectral description of g(x) and a term that solely depends on f(x) and that is independent of g(x). We then use the method of stationary phase to derive the essential maximum frequency of g(f(x)) bounding the main portion of the energy of its spectrum. This limit is the product of the maximum frequency of g(x) and the maximum derivative of f(x). This leads to a proper sampling of the composition h of the two functions g and f. We apply our theoretical results to a fundamental open problem in volume rendering---the proper sampling of the rendering integral after the application of a transfer function. In particular, we demonstrate how the sampling criterion can be incorporated in adaptive ray integration, visualization with multi-dimensional transfer functions, and pre-integrated volume rendering.

The back matter to this issue contains the cover image credits and the author index.

The back matter to this issue contains the cover image credits and the author index.