PUBLICATIONS
Papers

Full-text PDF is available for most of the papers listed below. HTML is also available for some of the papers. Technical reports are also included at the end of the paper list. I'm happy to mail copies of any of the others, please send me e-mail containing your regular mailing address and the papers you're interested in.

Visualizing Static Ensembles for Effective Shape and Data Comparison

The challenges of cyber situation awareness call for ways to provide assistance to analysts and decision-makers. In many fields, analyses of complex systems and activities benefit from visualization of data and analytical products. Analysts use images in order to engage their visual perception in identifying features in the data, and to apply the analysts' domain knowledge. One would expect the same to be true in the practice of cyber analysts as they try to form situational awareness of complex networks. This chapter takes a close look at visualization for Cyber Situation Awareness. We begin with a basic overview of scientific and information visualization, and of recent visualization systems for cyber situation awareness. Then, we outline a set of requirements, derived largely from discussions with expert cyber analysts, for a candidate visualization system.

Hao, L., Healey, C. G., Bass. S. A., and Yu, H.-Y. "Visualizing Static Ensembles for Effective Shape and Data Comparison." Visualization and Data Analytics 2016, (San Francisco, California, 2016), to appear.

Effective Visualization of Temporal Ensembles

An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details. Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore. We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: (1) segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and (2) time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps. Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions.

Hao, L., Healey, C. G., and Bass, S. A. "Effective Visualization of Temporal Ensembles." IEEE Transactions on Visualization and Computer Graphics 22, 1, (2015), 787–796.

Ensemble Visualization for Cyber Situation Awareness of Network Security Data

Network security analysis and ensemble data visualization are two active research areas. Although they are treated as separate domains, they share many common challenges and characteristics. Both focus on scalability, time-dependent data analytics, and exploration of patterns and unusual behaviors in large datasets. These overlaps provide an opportunity to apply ensemble visualization research to improve network security analysis. To study this goal, we propose methods to interpret network security alerts and flow traffic as ensemble members. We can then apply ensemble visualization techniques in a network analysis environment to produce a network ensemble visualization system. Including ensemble representations provide new, in-depth insights into relationships between alerts and flow traffic. Analysts can cluster traffic with similar behavior and identify traffic with unusual patterns, something that is difficult to achieve with high-level overviews of large network datasets. Furthermore, our ensemble approach facilitates analysis of relationships between alerts and flow traffic, improves scalability, maintains accessibility and configurability, and is designed to fit our analysts' working environment, mental models, and problem solving strategies.

Hao, L., Healey, C. G., and Hutchinson, S. E. "Ensemble Visualization for Cyber Situation Awareness of Network Security Data." In Proceedings Visualization for Cyber Security 2015 (Chicago, Illinois, 2015), pp. 25–32.

Visualizations and Analysts

The challenges of cyber situation awareness call for ways to provide assistance to analysts and decision-makers. In many fields, analyses of complex systems and activities benefit from visualization of data and analytical products. Analysts use images in order to engage their visual perception in identifying features in the data, and to apply the analysts' domain knowledge. One would expect the same to be true in the practice of cyber analysts as they try to form situational awareness of complex networks. This chapter takes a close look at visualization for Cyber Situation Awareness. We begin with a basic overview of scientific and information visualization, and of recent visualization systems for cyber situation awareness. Then, we outline a set of requirements, derived largely from discussions with expert cyber analysts, for a candidate visualization system.

Healey, C. G., Hao, L., and Hutchinson, S. E. "Visualizations and Analysts," in Cyber Defense and Situation Awareness, A. Kott, C. Wang and R. Erbacher, Eds. New York, New York: Springer Publishing Company, pp. 145–165.

Visualizing Likelihood Density Functions via Optimal Region Projection

Effective visualization of high-likelihood regions of parameter space is severely hampered by the large number of parameter dimensions that many models have. We present a novel technique, Optimal Percentile Region Projection, to visualize a high-dimensional likelihood density function that enables the viewer to understand the shape of the high-likelihood region. Optimal Percentile Region Projection has three novel components: first, we select the region of high likelihood in the high-dimensional space before projecting its shadow into a lower-dimensional projected space. Second, we analyze features on the surface of the region in the projected space to select the projection direction that shows the most interesting parameter dependencies. Finally, we use a three-dimensional projection space to show features that are not salient in only two dimensions. The viewer can also choose sets of axes to project along to explore subsets of the parameter space, using either the original parameter axes or principal-component axes. The technique was evaluated by our domain-science collaborators, who found it to be superior to their existing workflow both when there were interesting dependencies between parameters and when there were not.

Canary, H., Taylor II, R. M., Quammen, C., Pratt, S., Gomez, F., O'Shea, B., and Healey, C. G. "Visualizing Likelihood Density Functions via Optimal Region Projection." Computers & Graphics 41, (2014), 62–71.

Flexible Web Visualization for Alert-Based Network Security Analytics

This paper describes a web-based visualization system designed for network security analysts at the U.S. Army Research Laboratory (ARL). Our goal is to provide visual support to the analysts as they investigate security alerts for malicious activity within their systems. Our ARL collaborators identified a number of important requirements for any candidate visualization system. These relate to the analyst's mental models and working environment, and to the visualization tool's configurability, accessibility, scalability, and "fit" with existing analysis strategies. To meet these requirements, we designed and implement a web-based tool that uses different types of charts as its core representation framework. A JavaScript charting library (RGraph) was extended to provide the interface extensibility and correlation capabilities needed to support analysts as they explore different hypotheses about a potential attack. We describe key elements of our design, explain how an analyst's intent is used to generate different visualizations, and show how the system's interface allows an analyst to rapidly produce a sequence of visualizations to explore specific details about a potential attack as they arise. We conclude with a discussion of plans to further improve the system, and to collect feedback from our ARL colleagues on its strengths and limitations in real-world analysis scenarios.

Hao, L., Healey, C. G., and Hutchinson, S. E. "Flexible Web Visualization for Alert-Based Network Security Analytics." In Proceedings Visualization for Cyber Security 2013 (Atlanta, Georgia, 2013), pp. 33–40.

On the Limits of Resolution and Visual Angle in Visualization

This article describes a perceptual level-of-detail approach for visualizing data. Properties of a dataset that cannot be resolved in the current display environment need not be shown, for example, when too few pixels are used to render a data element, or when the element's subtended visual angle falls below the acuity limits of our visual system. To identify these situations, we asked: (1) What type of information can a human user perceive in a particular display environment? (2) Can we design visualizations that control what they represent relative to these limits? and (3) Is it possible to dynamically update a visualization as the display environment changes, to continue to effectively utilize our perceptual abilities? To answer these questions, we conducted controlled experiments that identified the pixel resolution and subtended visual angle needed to distinguish different values of luminance, hue, size, and orientation. This information is summarized in a perceptual display hierarchy, a formalization describing how many pixels—resolution—and how much physical area on a viewer's retina—visual angle—is required for an element's visual properties to be readily seen. We demonstrate our theoretical results by visualizing historical climatology data from the International Panel for Climate Change.

Healey, C. G. and Sawant, A. P. "On the Limits of Resolution and Visual Angle in Visualization." ACM Transactions on Applied Perception 9, 4, (2012), article 20.

Interest Driven Navigation in Visualization

This paper describes a new method to explore and discover within a large dataset. We apply techniques from preference elicitation to automatically identify data elements that are of potential interest to the viewer. These "elements of interest" are bundled into spatially local clusters, and connected together to form a graph. The graph is used to build camera paths that allow viewers to "tour" areas of interest within their data. It is also visualized to provide wayfinding cues. Our preference model uses Bayesian classification to tag elements in a dataset as interesting or not interesting to the viewer. The model responds in real-time, updating the elements of interest based on a viewer's actions. This allows us to track a viewer's interests as they change during exploration and analysis. Viewers can also interact directly with interest rules the preference model defines. We demonstrate our theoretical results by visualizing historical climatology data collected at locations throughout the world.

Healey, C. G. and Dennis, B. M. "Interest Driven Navigation in Visualization." IEEE Transactions on Visualization and Computer Graphics 18, 10, (2012), 1744–1756.

Attention and Visual Memory in Visualization and Computer Graphics


A change blindness example, it is often difficult to immediately see the difference between the left and the right images. Once found, it is clear the difference is not subtle. Limits on visual memory make it difficult to compare the images.

A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we “see” details in an image can directly impact a viewer’s efficiency and effectiveness. This article surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics.

Healey, C. G. and Enns, J. T. "Attention and Visual Memory in Visualization and Computer Graphics." IEEE Transactions on Visualization and Computer Graphics 18, 7, (2012), 1170–1188.

Exploring Ensemble Visualization

An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation. To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics. Results show that both techniques are capable of supporting meaningful comparisons of ensemble data.

Phadke, M. N., Pinto, L., Alabi, O., Harter, J., Taylor II, R. M., Wu, X., Petersen, H., Bass, S. A., and Healey, C. G. "Exploring Ensemble Visualization." Visualization and Data Analytics 2012, (San Francisco, California, 2012), vol. 8294, paper 0B, pp. 1–12.

Comparative Visualization of Ensembles Using Ensemble Surface Slicing

By definition, an ensemble is a set of surfaces or volumes derived from a series of simulations or experiments. Sometimes the series is run with different initial conditions for one parameter to determine parameter sensitivity. The understanding and identification of visual similarities and differences among the shapes of members of an ensemble is an acute and growing challenge for researchers across the physical sciences. More specifically, the task of gaining spatial understanding and identifying similarities and differences between multiple complex geometric data sets simultaneously has proved challenging. This paper proposes a comparison and visualization technique to support the visual study of parameter sensitivity. We present a novel single-image view and sampling technique which we call Ensemble Surface Slicing (ESS). ESS produces a single image that is useful for determining differences and similarities between surfaces simultaneously from several data sets. We demonstrate the usefulness of ESS on two real-world data sets from our collaborators.

Alabi, O., Wu, X., Harter, J., Phadke, M. N., Pinto, L., Petersen, H., Bass, S. A., Keifer, M., Zhong, S., Healey, C. G., and Taylor II, R. M. "Comparative Visualization of Ensembles Using Ensemble Surface Slicing." Visualization and Data Analytics 2012, (San Francisco, California, 2012), vol. 8294, paper 0U, pp. 1–12.

Visualizing Combinatorial Auctions

Visualizing three stages in a combinatorial auction: concentric rings represent different bundles of goods, segment color and blur shows bid price and interest in a bundle, and white rectangles identify a "winning" bidder for a bundle; winning bids connected with dashed lines identify a competitive allocation of all goods in the auction

We propose a novel scheme to visualize combinatorial auctions; auctions that involve the simultaneous sale of multiple items. Buyers bid on complementary sets of items, or bundles, where the utility of securing all the items in the bundle is more than the sum of the utility of the individual items. Our visualizations use concentric rings divided into arcs to visualize the bundles in an auction. The arcs’ positions and overlaps allow viewers to identify and follow bidding strategies. Properties of color, texture, and motion are used to represent different attributes of the auction, including active bundles, prices bid for each bundle, winning bids, and bidders’ interests. Keyframe animations are used to show changes in an auction over time. We demonstrate our visualization technique on a standard testbed dataset generated by researchers to evaluate combinatorial auction bid strategies, and on recent Federal Communications Commission (FCC) auctions designed to allocate wireless spectrum licenses to cell phone service providers.

Hsiao, J. P.-L. and Healey, C. G. "Visualizing Combinatorial Auctions." The Visual Computer 27, 6–8, (2011), 633–643.

Interactive Visual Summarization of Multidimensional Data

Visualization has become integral to the knowledge discovery process across various domains. However, challenges remain in the effective use of visualization techniques, especially when displaying, exploring and analyzing large, multidimensional datasets, such as weather and meteorological data. Direct visualizations of such datasets tend to produce images that are cluttered with excess detail and are ineffective at communicating information at higher levels of abstraction. To address this problem we provide a visual summarization framework to intuitively reduce the data to its important and relevant characteristics. Summarization is performed in three broad steps. First, high-relevance data elements and clusters of similar data attributes are identified to reduce a dataset’s size and dimensionality. Next, patterns, relationships and outliers are extracted from the reduced data. Finally, the extracted summary characteristics are visualized to the user. Such visualizations reduce excess visual detail and are more suited to the rapid comprehension of complex data. Users can interactively guide the summarization process gaining insight into both how and why the summary results are produced. Our framework improves the benefits of mathematical analysis and interactive visualization by combining the strengths of the computer and the user to generate high-quality summaries. Initial results from applying our framework to large weather datasets have been positive, suggesting that our approach could be beneficial for a wide range of domains and applications.

Kocherlakota, S. and Healey, C. G. "Interactive Visual Summarization of Multidimensional Data." In IEEE International Conference on Man, Systems, and Cybernetics 2009 (San Antonio, Texas, 2009), pp. 362–369.

Visual Perception and Mixed-Initiative Interaction For Assisted Visualization Design

This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called ViA, a system that collaborates with its users to identify perceptually salient visualizations for large, multidimensional datasets. ViA applies knowledge of low-level human vision to: (1) evaluate the effectiveness of a particular visualization for a given dataset and analysis tasks; and (2) rapidly direct its search towards new visualizations that are most likely to offer improvements over those seen to date. Context, domain expertise, and a high-level understanding of a dataset are critical to identifying effective visualizations. We apply a mixed-initiative strategy that allows ViA and its users to share their different strengths and continually improve ViA's understanding of a user's preferences. We visualize historical weather conditions to compare ViA's search strategy to exhaustive analysis, simulated annealing, and reactive tabu search, and to measure the improvement provided by mixed-initiative interaction. We also visualize intelligent agents competing in a simulated online auction to evaluate ViA's perceptual guidelines. Results from each study are positive, suggesting that ViA can construct high-quality visualizations for a range of real-world datasets.

Healey, C. G., Kocherlakota, S., Rao, V., Mehta, R., and St. Amant, R. "Visual Perception and Mixed-Initiative Interaction for Assisted Visualization Design." Transactions on Visualization and Computer Graphics 14, 2, (2008), 396–411.

Visualizing Multidimensional Query Results Using Animation

Effective representation of large, complex collections of information (datasets) presents a difficult challenge. Visualization is a solution that uses a visual interface to support efficient analysis and discovery within the data. Our primary goal in this paper is a technique that allows viewers to compare multiple query results representing user-selected subsets of a multidimensional dataset. We present an algorithm that visualizes multidimensional information along a space-filling spiral. Graphical glyphs that vary their position, color, and texture appearance are used to represent attribute values for the data elements in each query result. Guidelines from human perception allow us to construct glyphs that are specifically designed to support exploration, facilitate the discovery of trends and relationships both within and between data elements, and highlight exceptions. A clustering algorithm applied to a user-chosen ranking attribute bundles together similar data elements. This encapsulation is used to show relationships across different queries via animations that morph between query results. We apply our techniques to the MovieLens recommender system, to demonstrate their applicability in a real-world environment, and then conclude with a simple validation experiment to identify the strengths and limitations of our design, compared to a traditional side-by-side visualization.

Sawant, A. P. and Healey, C. G. "Visualizing Multidimensional Query Results Using Animation." In Proceedings Visualization and Data Analysis 2008 (San Jose, California, 2008), vol. 6809, paper 04, pp. 1–12.

ChipViz: Visualizing Memory Chip Test Data

This paper presents a technique that allows test engineers to visually analyze and explore within memory chip test data. We represent the test results from a generation of chips along a traditional grid and a spiral. We also show correspondences in the test results across multiple generations of memory chips. We use simple geometric "glyphs" that vary their spatial placement, color, and texture properties to represent the critical attribute values of a test. When shown together, the glyphs form visual patterns that support exploration, facilitate discovery of data characteristics, relationships, and highlight trends and exceptions in the test data that are often difficult to identify with existing statistical tools.

Sawant, A. P., Raina, R., and Healey, C. G. "ChipViz: Visualizing Memory Chip Test Data." In Proceedings Third International Symposium on Visual Computing 2007 (Lake Tahoe, Nevada, 2007), pp. 711–720.

Weaving Versus Blending: A Quantitative Assessment of the Information Carrying Capacities of Two Alternative Methods for Conveying Multivariate Data With Color

In many applications, it's important to understand the individual values of, and relationships between, multiple related scalar variables defined across a common domain. Several approaches have been proposed for representing data in these situations. In this paper we focus on strategies for the visualization of multivariate data that rely on color mixing. In particular, through a series of controlled observer experiments, we seek to establish a fundamental understanding of the information-carrying capacities of two alternative methods for encoding multivariate information using color: color blending and color weaving. We begin with a baseline experiment in which we assess participants' abilities to accurately read numerical data encoded in six different basic color scales defined in the L*a*b* color space. We then assess participants' abilities to read combinations of 2, 3, 4 and 6 different data values represented in a common region of the domain, encoded using either color blending or color weaving. In color blending a single mixed color is formed via linear combination of the individual values in L*a*b* space, and in color weaving the original individual colors are displayed side-by-side in a high frequency texture that fills the region. A third experiment was conducted to clarify some of the trends regarding the color contrast and its effect on the magnitude of the error that was observed in the second experiment. The results indicate that when the component colors are represented side-by-side in a high frequency texture, most participants' abilities to infer the values of individual components are significantly improved, relative to when the colors are blended. Participants' performance was significantly better with color weaving particularly when more than 2 colors were used, and even when the individual colors subtended only 3 minutes of visual angle in the texture. However, the information-carrying capacity of the color weaving approach has its limits. We found that participants' abilities to accurately interpret each of the individual components in a high frequency color texture typically falls off as the number of components increases from 4 to 6. We found no significant advantages, in either color blending or color weaving, to using color scales based on component hues that are more widely separated in the L*a*b* color space. Furthermore, we found some indications that extra difficulties may arise when opponent hues are employed.

Hagh-Shenas, H., Kim, S., Interrante, V., and Healey, C. G. "Weaving Versus Blending: A Quantitative Assessment of the Information Carrying Capacities of Two Alternative Methods for Conveying Multivariate Data With Color." IEEE Transactions on Visualization and Computer Graphics 13, 6, (2007), 1270–1277.

Engaging Viewers Through Nonphotorealistic Visualizations

A nonphotorealistic visualization of flow through a simulated supernova collapse, showing flow direction with stroke orientation, flow velocity with colour, and flow pressure with stroke size

Research in human visual cognition suggests that beautiful images can engage the visual system, encouraging it to linger in certain locations in an image and absorb subtle details. By developing aesthetically pleasing visualizations of data, we aim to engage viewers and promote prolonged inspection, which can lead to new discoveries within the data. We present three new visualization techniques that apply painterly rendering styles to vary interpretational complexity (IC), indication and detail (ID), and visual complexity (VC), image properties that are important to aesthetics. Knowledge of human visual perception and psychophysical models of aesthetics provide the theoretical basis for our designs. Computational geometry and nonphotorealistic algorithms are used to preprocess the data and render the visualizations. We demonstrate the techniques with visualizations of real weather and supernova data.

Tateosian, L. G., Healey, C. G., and Enns, J. T. "Engaging Viewers Through Nonphotorealistic Visualizations." In Proceedings Fifth International Symposium on Non-Photorealistic Animation and Rendering 2007 (San Diego, California, 2007), pp. 93–102.

PerfViz: A Visualization Tool for Analyzing, Exploring, and Comparing Storage Controller Performance Data

This paper presents a technique that allows viewers to visually analyze, explore, and compare a storage controller's performance. We present an algorithm that visualizes storage controller's performance metrics along a traditional 2D grid or a linear space-filling spiral. We use graphical "glyphs" (simple geometric objects) that vary in color, spatial placement and texture properties to represent the attribute values contained in a data element. When shown together, the glyphs form visual patterns that support exploration, facilitate discovery of data characteristics, relationships, and highlight trends and exceptions.

Sawant, A.P., Vanninen, M., and Healey, C. G. "PerfViz: A Visualization Tool for Analyzing, Exploring, and Comparing Storage Controller Performance Data." In Proceedings Visualization and Data Analysis 2007 (San Jose, California, 2007), vol. 6495, paper 07, pp. 1-11.

Stevens Dot Patterns for 2D Flow Visualization

This paper describes a new technique to visualize 2D flow fields with a sparse collection of dots. A cognitive model proposed by Ken Stevens describes how spatially local configurations of dots are processed in parallel by the low-level visual system to perceive orientations throughout the image. We integrate this model into a visualization algorithm that converts a sparse grid of dots into patterns that capture flow orientations in an underlying flow field. Because our visualizations are based on experimental results from human vision, the patterns are perceptually salient. We describe how our algorithm supports large flow fields that exceed the capabilities of a display device, and demonstrate how to include properties like direction and velocity in our visualizations. We conclude by applying our technique to 2D slices from a simulated supernova collapse.

Tateosian, L. G., Dennis, B. M., and Healey, C. G. "Stevens Dot Patterns for 2D Flow Visualization." In Proceedings Third International Symposium on Applied Perception in Graphics and Visualization 2006 (Boston, Massachusetts, 2006), pp. 93-100.

A Comparison of Immersive HMD, Fish Tank VR and Fish Tank with Haptics Displays for Volume Visualization

Although a wide range of virtual reality (VR) systems are in use, there are few guidelines to help system and application developers select the components most appropriate for the domain problem they are investigating. Using the results of an empirical study, we developed such guidelines for the choice of display environment for four specific, but common, volume visualization problems: identification and judgment of the size, shape, density, and connectivity of objects present in the volume. These tasks are derived from questions being asked by collaborators studying Cystic Fibrosis. We compared user performance in three different stereo VR systems: (1) head-mounted display (HMD); (2) fish tank VR (fish tank); and (3) fish tank VR augmented with a haptic device (haptic). HMD participants were placed "inside" the volume and walked within it to explore its structure. Fish tank and haptic participants saw the entire volume on-screen and rotated it to view it from different perspectives. Response time and accuracy were used to measure performance. Results showed that the fish tank and haptic groups were significantly more accurate at judging the shape, density, and connectivity of objects and completed the tasks significantly faster than the HMD group. Although the fish tank group was itself significantly faster than the haptic group, there were no statistical differences in accuracy between the two. Participants classified the HMD system as an "inside-out" display (looking outwards from inside the volume), and the fish tank and haptic systems as "outside-in" displays (looking inwards from outside the volume). Including haptics added an inside-out capability to the fish tank system through the use of touch. We recommend an outside-in system, since it offers both overview and context, two visual properties that are important for the volume visualization tasks we studied. In addition, based on the haptic group's opinion (80% positive) that haptic feedback aided comprehension, we recommend supplementing the outside-in visual display with inside-out haptics when possible.

Qi, W., Taylor, R. M., Healey, C. G., and Martens, J-B. "A Comparison of Immersive HMD, Fish Tank VR and Fish Tank with Haptics Displays for Volume Visualization." In Proceedings Third International Symposium on Applied Perception in Graphics and Visualization 2006 (Boston, Massachusetts, 2006), pp. 51-58.

VisTRE: A Visualization Tool to Evaluate Errors in Terrain Representations
( PDF | Poster )

New data sources and sensors bring new possibilities for terrain representations, and new types of characteristic errors. We develop a system to visualize and compare terrain representations and the errors they produce.

Healey, C. G. and Snoeyink, J. "VisTRE: A Visualization Tool to Evaluate Errors in Terrain Representations." In Proceedings Third International Symposium on 3D Data Processing, Visualization, and Transmission 2006 (Chapel Hill, North Carolina, 2006).

Visualizing Data with Motion

This paper describes an experimental study of three perceptual properties of motion: flicker, direction, and velocity. Our goal is to understand how to apply these properties to represent data in a visualization environment. Results from our experiments show that all three properties can encode multiple data values, but that minimum visual differences are needed to ensure rapid and accurate target detection: flicker must be coherent and must have a cycle length of 120 milliseconds or greater, direction must differ by at least 20°, and velocity must differ by at least 0.43° of subtended visual angle. We conclude with an overview of how we are applying our results to real-world data, then discuss future work we plan to pursue.

Huber, D. E. and Healey, C. G. "Visualizing Data with Motion." In Proceedings IEEE Visualization 2005 (Minneapolis, Minnesota, 2005), pp. 527-534.

Designing a Visualization Framework for Multidimensional Data

This article describes our initial end-to-end system that starts with data management and continues through assisted visualization design, display, navigation, and user interaction. The purposes of this discussion are to: (1) promote a more comprehensive visualization framework; (2) describe how expertise from human psychophysics, databases, rational logic, and artificial intelligence can be applied to visualization; and (3) illustrate the benefits of a more complete framework using examples from our own experiences.

Dennis, B. M., Kocherlakota, S. M., Sawant, A. P., Tateosian, L. G., and Healey, C. G. "Designing a Visualization Framework for Multidimensional Data." IEEE Computer Graphics & Applications (Visualization Viewpoints) 25, 6, (2005), 10-15.

Building Attack Scenarios Through Integrating Complementary Alert Correlation Methods

Several alert correlation methods were proposed in the past several years to construct high-level attack scenarios from low-level intrusion alerts reported by intrusion detection systems (IDSs). These correlation methods have different strengths and limitations; none of them clearly dominate the others. However, all of these methods depend heavily on the underlying IDSs, and perform poorly when the IDSs miss critical attacks. In order to improve the performance of intrusion alert correlation and reduce the impact of missed attacks, this paper presents a series of techniques to integrate two complementary types of alert correlation methods: (1) those based on the similarity between alert attributes, and (2) those based on prerequisites and consequences of attacks. In particular, this paper presents techniques to hypothesize and reason about attacks possibly missed by IDSs based on the indirect causal relationship between intrusion alerts and the constraints they must satisfy. This paper also discusses additional techniques to validate the hypothesized attacks through raw audit data and to consolidate the hypothesized attacks to generate concise attack scenarios. The experimental results in this paper demonstrate the potential of these techniques in building high-level attack scenarios and reasoning about possibly missed attacks.

Ning, P., Xu, D, Healey, C. G., and St. Amant, R. "Attack Scenarios Through Integrating Complementary Alert Correlation Methods." In Proceedings Tenth Annual Network and Distributed System Security Symposium 2004 (San Diego, California, 2004), pp. 97–111.

Perceptually-Based Brush Strokes for Nonphotorealistic Visualization

An important problem in the area of computer graphics is the visualization of large, complex information spaces. Datasets of this type have grown rapidly in recent years, both in number and in size. Images of the data stored in these collections must support rapid and accurate exploration and analysis. This paper presents a method for constructing visualizations that are both effective and aesthetic. Our approach uses techniques from master paintings and human perception to visualize a multidimensional dataset. Individual data elements are drawn with one or more brush strokes that vary their appearance to represent the element's attribute values. The result is a nonphotorealistic visualization of information stored in the dataset. Our research extends existing glyph-based and nonphotorealistic techniques by applying perceptual guidelines to build an effective representation of the underlying data. The nonphotorealistic properties the strokes employ are selected from studies of the history and theory of Impressionist art. We show that these properties are similar to visual features that are detected by the low-level human visual system. This correspondence allows us to manage the strokes to produce perceptually salient visualizations. Psychophysical experiments confirm a strong relationship between the expressive power of our nonphotorealistic properties and previous findings on the use of perceptual color and texture patterns for data display. Results from these studies are used to produce effective nonphotorealistic visualizations. We conclude by applying our techniques to a large, multidimensional weather dataset to demonstrate their viability in a practical, real-world setting.

Healey, C. G., Enns, J. T., Tateosian, L. G., and Remple, M. "Perceptually-Based Brush Strokes for Nonphotorealistic Visualization." ACM Transactions on Graphics 23, 1, (2004), 64-96.

Thoughts on User Studies: Why, How, and When

Visualization as currently practiced is mostly a craft. Methods are often designed and evaluated by presenting results informally to potential users. No matter how efficient a visualization technique may be, or how well motivated from theory, if it does not convey information effectively, it is of little use. User studies offer a scientifically sound method to measure a visualization's performance. Although their use has become more widespread, we believe they have the potential for a much broader impact. This article describes our experiences with user studies.

Kosara, R.., Healey, C. G., Interrante, V., Laidlaw, D. H., and Ware, C. "Thoughts on User Studies: Why, How, and When." IEEE Computer Graphics & Applications (Visualization Viewpoints) 23, 4, (2003), 20-25.

Target Detection and Localization in Visual Search: A Dual Systems Perspective

The dual visual systems framework was used to explore target detection and localization in visual search. Observers searched for a small patch of tilted bars against a dense background of upright bars. Target detection was performed along with two different localization tasks: direct pointing, designed to engage the dorsal stream, and indirect pointing, designed to engage the ventral stream. Results indicated that: (1) target detection was influenced more by orientation differences in three-dimensional space than by two-dimensional pictorial differences, (2) target localization was more accurate for direct than for indirect pointing, and (3) there were performance costs for indirect localization when it followed target detection, but none for direct localization. This is consistent with direct localization having a greater dependence on the dorsal visual system than either target detection or indirect localization.

Liu, G., Healey, C. G., and Enns, J. T. "Target Detection and Localization in Visual Search: A Dual Systems Perspective." Perception & Psychophysics 65, 5, (2003), 678-694.

Assisted Navigation for Large Information Spaces

This paper presents a new technique for visualizing large, complex collections of data. The size and dimensionality of these datasets make them challenging to display in an effective manner. The images must show the global structure of spatial relationships within the dataset, yet at the same time accurately represent the local detail of each data element being visualized. We propose combining ideas from information and scientific visualization together with a navigation assistant, a software system designed to help users identify and explore areas of interest within their data. The assistant locates data elements of potential importance to the user, clusters them into spatial regions, and builds underlying graph structures to connect the regions and the elements they contain. Graph traversal algorithms, constraint-based viewpoint construction, and intelligent camera planning techniques can then be used to design animated tours of these regions. In this way, the navigation assistant can help users to explore any of the areas of interest within their data. We conclude by demonstrating how our assistant is being used to visualize a multidimensional weather dataset.

Dennis, B. M. and Healey, C. G. "Assisted Navigation for Large Information Spaces." In Proceedings IEEE Visualization 2002 (Boston, Massachusetts, 2002), pp. 419-426.

Perception and Painting: A Search For Effective, Engaging Visualizations

Scientific visualization represents information as images that allow us to explore, discover, analyze, and validate large collections of data. Much of the research in this area is dedicated to the design of effective visualizations that support specific analysis needs. Recently, we have become interested in a new idea: Is a visualization beautiful? Can a visualization be considered a work of art? One might expect answers to these questions to vary widely depending on the individual and their interpretation of what it means to be artistic. We believe that the issues of effectiveness and aesthetics may not be as independent as they might seem at first glance, however. Much can be learned from a study of two related disciplines: human psychophysics, and art theory and history. Perception teaches us how we "see" the world around us. Art history shows us how artistic masters captured our attention by designing works that evoke an emotional response. The common interest in visual attention provides an important bridge between these domains. We are using this bridge to produce visualizations that are both effective and engaging. This article describes our research, and discusses some of the lessons we have learned along the way.

Healey, C. G and Enns, J. T. "Perception and Painting: A Search for Effective, Engaging Visualizations." IEEE Computer Graphics & Applications (Visualization Viewpoints) 22, 2, (2002), 10-15.

A Visual Interface to a Music Database

This paper describes a system for exploring and selecting entries from a music database through a visualization interface. The system is designed for deployment in situations in which the user's attention is a tightly limited resource. The system combines research topics in intelligent user interfaces, visualization techniques, and cognitive modeling. Informal evaluation of the system has given us useful insights into the design tradeoffs that developers may face when building visual interfaces for off-the-desktop applications.

St. Amant, R., Blair, J. E., Barry, P., Bentor, Y., and Healey, C. G. "A Visual Interface to a Music Database." In Proceedings Advanced Visual Interfaces 2002 (Trento, Italy, 2002), pp. 85-88.

Attribute Preserving Dataset Simplification

This paper describes a novel application of feature preserving mesh simplification to the problem of managing large, multidimensional datasets during scientific visualization. To allow this, we view a scientific dataset as a triangulated mesh of data elements, where the attributes embedded in each element form a set of properties arrayed across the surface of the mesh. Existing simplification techniques were not designed to address the high dimensionality that exists in these types of datasets. As well, vertex operations that relocate, insert, or remove data elements may need to be modified or restricted. Principal component analysis provides an algorithm-independent method for compressing a dataset's dimensionality during simplification. Vertex locking forces certain data elements to maintain their spatial locations; this technique is also used to guarantee a minimum density in the simplified dataset. The result is a visualization that significantly reduces the number of data elements to display, while at the same time ensuring that high-variance regions of potential interest remain intact. We apply our techniques to a number of well-known feature preserving algorithms, and demonstrate their applicability in a real-world context by simplifying a multidimensional weather dataset. Our results show a significant improvement in execution time with only a small reduction in accuracy; even when the dataset was simplified to 10% of its original size, average per attribute error was less than 1%.

Walter, J. D. and Healey, C. G. "Attribute Preserving Dataset Simplification." In Proceedings IEEE Visualization 2001 (San Diego, California, 2001), pp. 113-120.

Formalizing Artistic Techniques and Scientific Visualization for Painted Renditions of Complex Information Spaces

This paper describes a new method for visualizing complex information spaces as painted images. Scientific visualization converts data into pictures that allow viewers to "see" trends, relationships, and patterns. We introduce a formal definition of the correspondence between traditional visualization techniques and painterly styles from the Impressionist art movement. This correspondence allows us to apply perceptual guidelines from visualization to control the presentation of information in a computer-generated painting. The result is an image that is visually engaging, but that also allows viewers to rapidly and accurately explore and analyze the underlying data values. We conclude by applying our technique to a collection of environmental and weather readings, to demonstrate its viability in a practical, real-world visualization environment.

Healey, C. G. "Formalizing Artistic Techniques and Scientific Visualization for Painted Renditions of Complex Information Spaces." In Proceedings International Joint Conference on Artificial Intelligence 2001 (Seattle, Washington, 2001), pp. 371-376.

Useability Guidelines for Interactive Search in Direct Manipulation Systems

As AI systems make their way into the mainstream of interactive applications, usability becomes an increasingly important factor in their success. A wide range of user interface design guidelines have been developed for the direct manipulation and graphical user interface conventions of modern software. Unfortunately, it is not always clear how these should be applied to AI systems. This paper discusses a visualization assistant, an e-commerce simulation domain we have applied it to, and the guidelines we found relevant in the construction of its user interface. The goal of this paper is to explain how an interactive system can incorporates search-based intelligent behavior while still respecting well-established rules for effective user interaction.

St. Amant, R. and Healey, C. G. "Useability Guidelines for Interactive Search in Direct Manipulation Systems." In Proceedings International Joint Conference on Artificial Intelligence 2001 (Seattle, Washington, 2001), pp. 1179-1184.

Combining Perception and Impressionist Techniques for Nonphotorealistic Visualization of Multidimensional Data
( PDF | PowerPoint Slides | Quicktime Movie )

The goal of this course is to introduce participants to the wealth of visualization inspiration available from art and art history. How people perceive an image can have a profound effect on the meaning they attach to that image. A compelling example is the artist's use of painterly techniques that harness our perception to evoke a specific emotional response. This course surveys a number of important issues in nonphotorealistic rendering and visual perception, then discusses their direct relevance to computer graphics and scientific visualization through a series of descriptions, examples, and practical applications. Topics address questions like: Which artistic techniques can we apply during image generation? How can these techniques be used to enhance the expressive power of traditional methods like volume visualization or line integral convolution? How does the correspondence between artistic properties and human perception allow us to produce painterly renditions of complex information spaces? Answers to these questions are important to graphics researchers and practitioners who want to construct nonphotorealistic images the convey an intended meaning or perceptual effect when viewed by their audience.

Healey, C. G. "Combining Perception and Impressionist Techniques for Nonphotorealistic Visualization of Multidimensional Data." In SIGGRAPH 2001 Course 32: Nonphotorealistic Rendering in Scientific Visualization (Los Angeles, California, 2001), pp. 20-52.

Assisted Visualization of E-Commerce Auction Agents
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This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search technique. The result is a visualization assistant, a system that identifies perceptually salient visualizations for large, multidimensional collections of data. Understanding how the low-level human visual system "sees" visual information in an image allows us to: (1) evaluate a particular visualization, and (2) direct the search algorithm towards new visualizations that may be better than those seen to date. In this way we can limit search to locations that have the highest potential to contain effective visualizations. One testbed application for this work is the visualization of intelligent e-commerce auction agents participating in a simulated online auction environment. We describe how the visualization assistant was used to choose methods to effectively visualize this data.

Healey, C. G., St. Amant, R., and Chang, J. "Assisted Visualization of E-Commerce Auction Agents." In Proceedings Graphics Interface 2001 (Ottawa, Canada, 2001), pp. 201-208.

Intelligent Visualization in a Planning System

This paper describes visualization techniques for interactive planning in a physical force simulation called AFS. We have developed a 3D environment in which textures are overlaid on a simulated landscape to convey information about environmental properties, agent actions, and possible strategies. Scenes are presented, via automated camera planning, such that in some cases agent goals can be induced visually with little effort. These two areas of visualization functionality in AFS exploit properties of human low-level and intermediate-level vision, respectively. This paper presents AFS, its visualization environment, and an experiment we have run to explore the relationship between AFS visualizations and the high-level planning process.

St. Amant, R., Healey, C. G., Riedl, M., Kocherlakota, S., Pegram, D. A., and Torhola, M. "Intelligent Visualization in a Planning System." In Proceedings Intelligent User Interfaces 2001 (Santa Fe, New Mexico, 2001), pp. 153-160.

Sensitivity to 3D Orientation in Textured Surfaces

Liu, G., Enns, J. T., and Healey, C. G. "Sensitivity to 3D Orientation in Textured Surfaces." In Psychonomics 2000 Poster Session #599 (New Orleans, Louisiana, 2000).

Oriented Texture Slivers: A Technique for Local Value Estimation of Multiple Scalar Fields
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Visualizing results from a scanning electron microscope with texture slivers whose orientations represent material type: Ca (15°), Cu (30°), Fe (60°), Mg (75°), O (90°), Mn (105°), S (150°), and Si (180°); and luminances represent the material's concentration; emergent textures identify regions with strong combinations of materials, for example, the "plus sign" textures to the left and right showing high concentrations of silicon-oxide

This paper describes a texture generation technique that combines orientation and luminance to support the simultaneous display of multiple overlapping scalar fields. Our orientations and luminances are selected based on psychophysical experiments that studied how the low-level human visual system perceives these visual features. The result is an image that allows viewers to identify data values in an individual field, while at the same time highlighting interactions between different fields. Our technique supports datasets with both smooth and sharp boundaries. It is stable in the presence of noise and missing values. Images are generated in real-time, allowing interactive exploration of the underlying data. Our technique can be combined with existing methods that use perceptual colours or perceptual texture dimensions, and can therefore be seen as an extension of these methods to further assist in the exploration and analysis of large, complex, multidimensional datasets.

Weigle, C., Emigh, W. G., Liu, G., Taylor, R. M., Enns, J. T., and Healey, C. G. "Oriented Texture Slivers: A Technique for Local Value Estimation of Multiple Scalar Fields." In Proceedings Graphics Interface 2000 (Montreal, Canada, 2000), pp. 163-170.

Building a Perceptual Visualisation Architecture

Scientific datasets are often difficult to analyse or visualise, due to their large size and high dimensionality. We propose a multistep approach to address this problem. We begin by using data management techniques to identify areas of interest within the dataset. This allows us to reduce a dataset's size and dimensionality, and to estimate missing values or correct erroneous entries. We display the results using visualisation techniques based on perceptual rules. Our visualisation tools are designed to exploit the power of the low-level human visual system. The result is a set of displays that allow users to perform rapid and accurate exploratory data analysis.

Healey, C. G. "Building a Perceptual Visualisation Architecture." Behaviour and Information Technology 19, 5, (2000), 349-366.

ViA: A Perceptual Visualization Assistant

This paper describes an automated visualization assistant called ViA. ViA is designed to help users construct perceptually optimal visualizations to represent, explore, and analyze large, complex, multidimensional datasets. We have approached this problem by studying what is known about the control of human visual attention. By harnessing the low-level human visual system, we can support our dual goals of rapid and accurate visualization. Perceptual guidelines that we have built using psychophysical experiments form the basis for ViA. ViA uses modified mixed-initiative planning algorithms from artificial intelligence to search for perceptually optimal data attribute to visual feature (data-feature) mappings. Our perceptual guidelines are integrated into evaluation engines that provide evaluation weights for a given data-feature mapping, and hints on how that mapping might be improved. ViA begins by asking users a set of simple questions about their dataset and the analysis tasks they want to perform. Answers to these questions are used in combination with the evaluation engines to identify and intelligently pursue promising data-feature mappings. The result is an automatically-generated set of mappings that are perceptually salient, but that also respect the context of the dataset and users' preferences about how they want to visualize their data.

Healey, C. G., St. Amant, R., and Elhaddad, M. "ViA: A Perceptual Visualization Assistant." In Proceedings 28th Applied Imagery Pattern Recognition Workshop, (Washington, D.C., 1999), pp. 1-11.

Fundamental Issues of Visual Perception for Effective Image Generation

How people perceive an image can have a profound effect on the meaning they attach to that image. This course surveys a number of fundamental issues in visual perception, then discusses their direct relevance to computer graphics and image generation through a series of descriptions, examples, and practical applications. Topics address questions like: How does the visual system "see" color, and how does that affect the RGB color model we often use to choose our colors? How can texture patterns be used to convey multiple independent channels of information to a viewer? How can motion be used to enhance an image? Answers to these questions are important to graphics researchers and practitioners who want to ensure their images convey the intended meaning or perceptual effect when viewed by their audience.

Healey, C. G. "Fundamental Issues of Visual Perception for Effective Image Generation." In SIGGRAPH 99 Course 6: Fundamental Issues of Visual Perception for Effective Image Generation (Los Angeles, California, 1999), pp. 1-42.

Large Datasets at a Glance: Combining Textures and Colors in Scientific Visualization

This paper presents a new method for using texture and color to visualize multivariate data elements arranged on an underlying height field. We combined simple texture patterns with perceptually uniform colors to increase the number of attribute values we can display simultaneously. Our technique builds multicolored perceptual texture elements (or pexels) to represent each data element. Attribute values encoded in an element are used to vary the appearance of its pexel. Texture and color patterns that form when the pexels are displayed can be used to rapidly and accurately explore the dataset. Our pexels are built by varying three separate texture dimensions: height, density, and regularity. Results from computer graphics, computer vision, and human visual psychophysics have identified these dimensions as important for the formation of perceptual texture patterns. The pexels are colored using a selection technique that controls color distance, linear separation, and color category. Proper use of these criteria guarantees colors that are equally distinguishable from one another. We describe a set of controlled experiments that demonstrate the effectiveness of our texture dimensions and color selection criteria. We then discuss new work that studies how texture and color can be used simultaneously in a single display. Our results show that variations of height and density have no effect on color segmentation, but that random color patterns can interfere with texture segmentation. As the difficult of the visual detection task increases, so too does the amount of color on texture interference. Wee conclude by demonstrating the applicability of our approach to a real-world problem, the tracking of typhoon conditions in Southeast Asia.

Healey, C. G. and Enns, J. T. "Large Datasets at a Glance: Combining Textures and Colors in Scientific Visualization." IEEE Transactions on Visualization and Computer Graphics 5, 2, (1999), 145-167.

Building Perceptual Textures to Visualize Multidimensional Datasets
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This paper presents a new method for using texture to visualize multidimensional data elements arranged on an underlying three-dimensional surface. We use simple texture patterns in combination with other visual features like hue and intensity to increase the number of attribute values we can display simultaneously. Our technique builds perceptual texture elements (or pexels) to represent each data element. Attribute values encoded in the data element are used to vary the appearance of a corresponding pexel. Texture patterns that form when the pexels are displayed can be used to rapidly and accurately explore the dataset. Our pexels are built by controlling three separate texture dimensions: height, density, and regularity. Results from computer graphics, computer vision, and cognitive psychology have identified these dimensions as important for the formation of perceptual texture patterns. We conducted a set of controlled experiments to measure the effectiveness of these dimensions, and to identify any visual interference that may occur when all three are displayed simultaneously at the same spatial location. Results from our experiments show that these dimensions can be used in specific combinations to form perceptual textures for visualizing multidimensional datasets. We demonstrate the effectiveness of our technique by applying it to the problem of visualizing ocean and atmospheric conditions on a topographical map of eastern Asia during the summer typhoon season.

Healey, C. G. and Enns, J. T. "Building Perceptual Textures to Visualize Multidimensional Datasets." In Proceedings IEEE Visualization '98 (Research Triangle Park, North Carolina, 1998), pp. 111-118.

Applications of Visual Perception in Computer Graphics

This paper describes our investigation of methods for choosing color, texture, orientation, shape, and other features to visualize certain types of large, multidimensional datasets. These datasets are becoming more and more common; examples include scientific simulation results, geographic information systems, satellite images, and biomedical scans. The overwhelming amount of information contained in these datasets makes them difficult to analyze using traditional mathematical or statistical techniques. It also makes them difficult to visualize in an efficient or useful manner.

Healey, C. G. "Applications of Visual Perception in Computer Graphics." In SIGGRAPH 98 Course 32: Applications of Visual Perception in Computer Graphics (Orlando, Florida, 1998), pp. 205-242.

On the Use of Perceptual Cues and Data Mining for Effective Visualization of Scientific Datasets
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Visualizing historical and estimated plankton densities with hue, current strengths with height, and sea surface temperatures with packing density in the northern Pacific Ocean, this data is used as input to models of Sockeye salmon migration

Scientific datasets are often difficult to analyse or visualize, due to their large size and high dimensionality. We propose a two-step approach to address this problem. We begin by using data mining algorithms to identify areas of interest within the dataset. This allows us to reduce a dataset's size and dimensionality, and to estimate missing values or correct erroneous entries. We display the results of the data mining step using visualization techniques based on perceptual cues. Our visualization tools are designed to exploit the power of the low-level human visual system. In order to demonstrate our techniques, we visualized an environmental dataset being used to model salmon growth and migration patterns. Data mining was used to identify significant attributes and to provide accurate estimates of plankton density. We used colour and texture to visualize the significant attributes and estimated plankton densities for each month for the years 1956 to 1964. The result is a visualization tool that allows users to quickly locate specific plankton densities and the boundaries they form. Users can compare plankton densities to other environmental conditions like sea surface temperature and current strength. Finally, users can track changes in any of the dataset's attributes on a monthly or yearly basis.

Healey, C. G. "On the Use of Perceptual Cues and Data Mining for Effective Visualization of Scientific Datasets." In Proceedings Graphics Interface '98 (Vancouver, Canada, 1998), pp. 177-184.

Volume Rendering of Abdominal Aortic Aneurysms
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Volume visualization of medical images must address two important issues. First, it is difficult to segment medical scans into individual materials based only on intensity values. This can result in volumes which contain large amounts of unimportant or unnecessary material. Second, although greyscale images are the normal method for displaying medical volumes, these types of images are not necessarily appropriate for highlighting regions of interest within the volume. We addressed both problems during the visualization of CT scans of abdominal aortic aneurysms. We have developed a classification method which empirically segments regions of interest in each of the 2D slices. We use a perceptual colour selection technique to identify each region of interest in both the 2D slices and the 3D reconstructed volumes. The result is a colourized volume which the radiologists are using to rapidly and accurately identify the locations and spatial interactions of different materials from their scans. Our technique has already been used in a post-operative environment to help to evaluate the results of surgery designed to prevent the rupture of the aneurysm.

Tam, R. C., Healey, C. G., Flak, B., and Cahoon, P. "Volume Rendering of Abdominal Aortic Aneurysms." In Proceedings IEEE Visualization '97 (Phoenix, Arizona, 1997), pp. 43-50.

High-Speed Visual Estimation Using Preattentive Processing

A new method is presented for performing rapid and accurate numerical estimation. It is derived from principles arising in an area of cognitive psychology called preattentive processing. Preattentive processing refers to an initial organization of the human visual system based on operations believed to be rapid, automatic, and spatially parallel. Examples of visual features that can be detected in this way include hue, intensity, orientation, size, and motion. We believe that studies from preattentive vision should be used to assist in the design of visualization tools, especially those for which high speed target, boundary, and region detection are important. In our present study, we investigated two known preattentive features (hue and orientation) in the context of a new task (numerical estimation) in order to see whether preattentive estimation was possible. Our experiments tested displays that were designed to visualize data from simulations being run in the Department of Oceanography. The results showed that rapid and accurate estimation is indeed possible using either hue or orientation. Furthermore, random variation of one of these features resulted in no interference when subjects estimated the numerosity of the other. To determine the robustness of our results, we varied two important display parameters, display duration and feature difference, and found boundary conditions for each. Implications of our results for application to real-word data and tasks are discussed.

Healey, C. G., Booth, K. S., and Enns, J. T. "High-Speed Visual Estimation Using Preattentive Processing." ACM Transactions on Human Computer Interaction 3, 2, (1996), 107-135.

Choosing Effective Colours for Data Visualization

In this paper we describe a technique for choosing multiple colours for use during data visualization. Our goal is a systematic method for maximizing the total number of colours available for use, while still allowing an observer to rapidly and accurately search a display for any one of the given colours. Previous research suggests that we need to consider three separate effects during colour selection: colour distance, linear separation, and colour category. We describe a simple method for measuring and controlling all of these effects. Our method was tested by performing a set of target identification studies; we analysed the ability of thirty-eight observers to find a colour target in displays that contained differently coloured background elements. Results showed that our method can be used to select a group of colours that will provide good differentiation between data elements during visualization.

Healey, C. G. "Choosing Effective Colours for Data Visualization." In Proceedings IEEE Visualization '96 (San Francisco, California, 1996), pp. 263-270.

Effective Visualization of Large, Multidimensional Datasets

A new method for assisting with the visualization of large multidimensional datasets is proposed. Our data visualization techniques are based in large part on a field of cognitive psychology called preattentive processing. Preattentive processing is the study of visual features that are detected rapidly and with little effort by the human visual system. Examples include hue, orientation, form, intensity, and motion. We studied ways of extending and applying research results from preattentive processing to address our visualization requirements. We used our investigations to build visualization tools that allow a user to very rapidly and accurately perform exploratory analysis tasks. These tasks include searching for target elements, identifying boundaries between groups of common elements, and estimating the number of elements that have a specific visual feature. Our experimental results were positive, suggesting that dynamic sequences of frames can be used to explore large amounts of data in a relatively short period of time.

Recent work in both scientific visualization and database systems has started to address the problems inherent in managing large scientific datasets. One promising technique is knowledge discovery, "the nontrivial extraction of implicit, previously unknown, and potentially useful information from data". We hypothesise that knowledge discovery can be used as a filter to reduce the amount of data sent to the visualization tool. Data elements that do not belong to a user-chosen group of interest can be discarded, the dimensionality of individual data elements can be compressed, and previously unknown trends and relationships can be discovered and explored.

Healey, C. G. "Effective Visualization of Large, Multidimensional Datasets." PhD Thesis (1996), Department of Computer Science, University of British Columbia.

Visualizing Real-Time Multivariate Data Using Preattentive Processing

A new method is presented for visualizing data as they are generated from real-time applications. Previous work has shown that results from research in preattentive processing can be used to build visualization tools which allow rapid and accurate analysis of individual, static data frames. We extend these techniques to a dynamic real-time environment. This allows users to perform similar tasks on dynamic sequences of frames, exactly like those generated by real-time systems such as visual interactive simulation. We studied two known preattentive features, hue and curvature. The primary question investigated was whether rapid and accurate target and boundary detection in dynamic sequences is possible using these features. Behavioral experiments were run that simulated displays from our preattentive visualization tools. Analysis of the results of the experiments showed that rapid and accurate target and boundary detection is possible with both hue and curvature. A second question, whether interactions occur between the two features in a real-time environment, was answered positively. This suggests that these and perhaps other visual features can be used to create visualization tools that allow high-speed multidimensional data analysis for use in real-time applications. It also shows that care must be taken in the assignment of data elements to preattentive features to avoid creating certain visual interference effects.

Healey, C. G., Booth, K. S., and Enns, J. T. "Visualizing Real-Time Multivariate Data Using Preattentive Processing." ACM Transactions on Modeling and Computer Simulation 5, 3, (1995), 190-221.

Computer Simulations of the Influence of Ocean Currents on Fraser River Sockeye Salmon (Oncorhynchus Nerka) Return Times

We hypothesized that the internannual variability of the northeast Pacific Ocean circulation affects the return times of Fraser River sockeye salmon (Oncorhynchus nerka). Homeward migrations were simulated for 1982 (with a relatively weak Alaska Gyre circulation) and 1983 (with a relatively strong circulation) in the context of three sequential return migration phases: a nondirected oceanic phase, a directed oceanic phase, and a directed coastal phase. Passive drifters were simulated to examine the influence of ocean currents during the nondirected oceanic phase: model fish south of 48 degrees N were advected closer to Vancouver Island in 1983 compared with 1982; those north of 48 degrees N were advected closer to Vancouver Island in 1982 than in 1983. Fish were simulated during the directed oceanic phase using a variety of behaviour scenarios: model fish starting south of 50 degrees N had earlier return times in 1983 than in 1982; those starting north of 50 degrees N had return times in 1983 that were generally the same as or later than in 1982. We inferred that ocean currents would modulate the environmental influences on return times during the directed coastal migration phase, by deflecting sockeye salmon into different oceanographic domains along the British Columbia coast.

Thompson, K. A., Ingraham, W. J., Healey, M. C., LeBlond, P., Groot, C., and Healey, C. G. "Computer Simulations of the Influence of Ocean Currents on Fraser River Sockeye Salmon (Oncorhynchus Nerka) Return Times." Canadian Journal of Fisheries and Aquatic Sciences 51, 2, (1994), 441-449.

Harnessing Preattentive Processes for Multivariate Data Visualization

A new method for designing multivariate data visualization tools is presented. These tools allow users to perform simple tasks such as estimation, target detection, and detection of data boundaries rapidly and accurately. Our design technique is based on principles arising from an area of cognitive psychology called preattentive processing. Preattentive processing involves visual features that can be detected by the human visual system without focusing attention on particular regions in an image. Examples of preattentive features include colour, orientation, intensity, size, shape, curvature, and line length. Detection is performed very rapidly by the visual system, almost certainly using a large degree of parallelism. We studied two known preattentive features, hue and orientation. The particular question investigated is whether rapid and accurate estimation is possible using these preattentive features. Experiments that simulated displays using our preattentive visualization tool were run. Analysis of the results of the experiments showed that rapid and accurate estimation is possible with both hue and orientation. A second question, whether interaction occurs between the two features, was answered negatively. This suggests that these and perhaps other preattentive features can be used to create visualization tools which allow high-speed multivariate data analysis.

Healey, C. G., Booth, K. S., and Enns, J. T. "Harnessing Preattentive Processes for Multivariate Data Visualization." In Proceedings Graphics Interface '93 (Toronto, Canada, 1993), pp. 107-117.

Visualization of Multivariate Data Using Preattentive Processing

A new method is presented for visualizing data as they are generated from real-time applications. These techniques allow viewers to perform simple data analysis tasks such as detection of data groups and boundaries, target detection, and estimation. The goal is to do this rapidly and accurately on a dynamic sequence of data frames. Our techniques take advantage of an ability of the human visual system called preattentive processing. Preattentive processing refers to an initial organization of the visual system based on operations believed to be rapid, automatic, and spatially parallel. Examples of visual features that can be detected in this way include hue, orientation, intensity, size, curvature, and line length. We believe that studies from preattentive processing should be used to assist in the design of visualization tools, especially those for which high speed target, boundary, and region detection are important.

Previous work has shown that results from research in preattentive processing can be used to build visualization tools which allow rapid and accurate analysis of individual, static data frames. We extend these techniques to a dynamic real-time environment. This allows users to perform similar tasks on dynamic sequences of frames, exactly like those generated by real-time systems such as visual interactive simulation. We studied two known preattentive features, hue and curvature. The primary question investigated was whether rapid and accurate target and boundary detection in dynamic sequences is possible using these features. Behavioral experiments were run that simulated displays from our preattentive visualization tools. Analysis of the results of the experiments showed that rapid and accurate target and boundary detection is possible with both hue and curvature. A second question, whether interactions occur between the two features in a real-time environment, was answered positively. This suggests that these and perhaps other visual features can be used to create visualization tools that allow high-speed multidimensional data analysis for use in real-time applications. It also shows that care must be taken in the assignment of data elements to preattentive features to avoid creating certain visual interference effects.

Healey, C. G. "Visualization of Multivariate Data Using Preattentive Processing." Masters Thesis (1993), Department of Computer Science, University of British Columbia.

The Influence of Ocean Currents on the Latitude of Landfall and Migration Speed of Sockeye Salmon Returning to the Fraser River

We hypothesize that the interannual variability of the Northeast Pacific Ocean circulation affects the latitude of landfall and migration speed of adult sockeye salmon (Oncorhynchus nerka) returning to the Fraser River. The Ocean Surface Current Simulations (OSCURS) model was used to simulate the return migration paths of compass-oriented sockeye for two years: 1982, which had a weak Alaska Gyre circulation and low Northern Diversion Rate (defined as the percentage of sockeye returning around the north end of Vancouver Island instead of the south end); and 1983, with a strong circulation and high northern diversion rate. The majority of model sockeye made landfall further north in 1983 than in 1982. The difference in landfall between 1983 and 1982 depended on the migration start position, swim speed, direction of orientation, and migration start date. The currents assisted the shoreward migration of sockeye starting from south of 55 degrees N and impeded the migration of sockeye starting from further north. The simulation results were consistent with our hypothesis and suggest that the effects of the Northeast Pacific currents must be included in sockeye migration models. We propose a conceptual model for the prediction of the Northern Diversion Rate that includes Blackbourn's (1987) temperature-displacement model, enhanced to include the effects of currents during the ocean phase of migration, and the use of two predictive formulas for the coastal phase of migration: the formula of Xie and Hsieh (1989) for sockeye approaching Vancouver Island directly from the ocean, and a yet to be developed formula for sockeye approaching from within the Coastal Downwelling Domain directly to the north of Vancouver Island.

Thompson, K. A., Ingraham, W. J., Healey, M. C., LeBlond, P., Groot, C., and Healey, C. G. "The Influence of Ocean Currents on the Latitude of Landfall and Migration Speed of Sockeye Salmon Returning to the Fraser River." Fisheries Oceanography 2, 1, (1992), 163-179.

Technical Reports

Summarization Techniques for Visualization of Large Multidimensional Datasets

One of the main issues confronting visualization, is how to effectively display large, high dimensional datasets within a limited display area, without overwhelming the user. In this report, we discuss a data summarization approach to tackle this problem. Summarization is the process by which data is reduced in a meaningful and intelligent fashion, to its important and relevant features. We survey several different techniques from within computer science, which can be used to extract various characteristics from raw data. Using summarization techniques intelligently within visualization systems, could potentially reduce the size and dimensionality of large, high dimensional data, highlight relevant and important features, and enhance comprehension.

Kocherlakota, S. M. and Healey, C. G. "Summarization Techniques for Visualization of Large Multidimensional Datasets." Technical Report TR-2005-35 (2005), Department of Computer Science, North Carolina State University.

A Survey of Display Device Properties and Visual Acuity for Visualization

The advent of computers with high processing power has led to the generation of huge datasets containing large numbers of elements, where each element is often characterized by multiple attributes. This has led to a critical need for ways to explore and analyze large, multidimensional information spaces. Visualization lends itself well to this challenge by enabling users to visually explore, analyze, and discover patterns within their data. Most visualization techniques are based on the assumption that the display device has sufficient resolution, and that our visual acuity is adequate to complete the analysis tasks. This may not be true however, particularly for specialized display devices (e.g., PDAs, or large-format projection walls). This paper discusses which properties of a display device need to be considered when visualizing large, multidimensional datasets. We also investigate the strengths and limitations of our visual system, in particular to understand how basic visual properties like color, texture, and motion are distinguished. These findings will form the basis for new research on how to best match a visualization design to a display's physical characteristics and a viewer's visual abilities.

Sawant, A. P. and Healey, C. G. "A Survey of Display Device Properties and Visual Acuity for Visualization." Technical Report TR-2005-32 (2005), Department of Computer Science, North Carolina State University.

NPR: Art Enhancing Computer Graphics

Nonphotorealistic rendering is a field in computer science in which scientists apply artistic techniques to enhance computer graphics. This paper addresses the interrogatives what, how, and why, about NPR. The discussion expands on what NPR is and what kinds of projects are being done in NPR, specifically it focuses on three issues: two large problems in NPR, simulating pen-and-ink illustration and simulating painting, and last the application of NPR to visualization. Exploring these topics thoroughly provides some specific answers to how these effects are accomplished. Throughout the paper various motivations for using NPR are revealed, including the application of NPR to visualization (as evidence of why). Our lab is interested in applying NPR techniques to visualization, so the paper concludes with some conjecture on how to verify the efficacy of this goal.

Tateosian, L. G. and Healey, C. G. "NPR: Art Enhancing Computer Graphics." Technical Report TR-2004-17 (2004), Department of Computer Science, North Carolina State University.

A Perceptual Colour Segmentation Algorithm

This paper presents a simple method for segmenting colour regions into categories like red, green, blue, and yellow. We are interested in studying how colour categories influence colour selection during scientific visualization. The ability to name individual colours is also important in other problem domains like real-time displays, user-interface design, and medical imaging systems. Our algorithm uses the Munsell and CIE LUV colour models to automatically segment a colour space like RGB or CIE XYZ into ten colour categories. Users are then asked to name a small number of representative colours from each category. This provides three important results: a measure of the perceptual overlap between neighbouring categories, a measure of a category's strength, and a user-chosen name for each strong category.

Healey, C. G. "A Perceptual Colour Segmentation Algorithm." Technical Report TR-96-09 (1996), Department of Computer Science, University of British Columbia.