Gamers use a variety of different display sizes, though for PC gaming, monitors in the 24 to 27 inch size range have become most popular.Particularly popular among many PC gamers, first person shooter (FPS) games represent a genre where hand-eye coordination is particularly central to the player's performance in game.In a carefully designed set of experiments on FPS aiming, we compare player performance across a range of display sizes.In two experiments, we compare 12.5 inch, 17.3 inch and 24 inch monitors on a multi-target elimination task, once with stationary, and once with moving targets.We find that aiming improves as display sizes increase.Next, we highlight the differences between 24.5 inch and 27 inch displays in a third experiment using very small targets.We find a small, but statistically significant improvement in aiming when using the larger monitor.Overall, our results indicate that in typical desktop gaming settings with freely varying head position and field of view, FPS aiming improves as display size grows, though improvements begin to decline as size approaches 30 inches.

Which display size helps gamers win? Recommendations from the research and PC gaming communities are contradictory. We find that as display size grows, targeting performance improves. When size increases from 13′′ to 26′′, targeting time drops by over 3%. Further size increases from 26′′ through 39′′, 52′′ and 65′′, bring more modest improvements, with targeting time dropping a further 1%. While such improvements may not be meaningful for novice gamers, they are extremely important to skilled and competitive players. To produce these results, 30 gamers participated in a targeting task as we varied display size by placing a display at varying distances. We held field of view constant by varying viewport size, and resolution constant by rendering to a fixed-size off-screen buffer. This paper offers further experimental detail, and examines likely explanations for the effects of display size.

Email has lost much of its original function: connecting people. Today, people use it as a task list, a database, and even legal documentation. For these and other reasons, email has become a source of stress; pushing us apart rather than bringing us together. In this paper, we describe POEM (People-Oriented EMail), a prototype email client designed to restore and strengthen email’s socially connective role. Because much of human communication is non-verbal, POEM features a visualization that summarizes user’s inbox by correspondent, using their profile pictures. To highlight human relationships, POEM offers access to detailed correspondent messages only by clicking on their pictures. Encouraging deeper relationships, POEM organizes correspondents by social importance measures including communication effort, balance, and delay before response. We conclude by sketching our plans to evaluate POEM.

Users often do not use keyboard shortcuts in applications as recalling and choosing the correct shortcut is a higher-order cognitive task. Mouse driven menus, toolbars, and icons are easier for a user to learn because they present hints and make visible what operations are possible, drawing on the power of recognition rather than recall. How can we better support the usage of shortcuts with such menus? Two existing methods are text in the icons, and popups with mouse hover. While the first is space inefficient; the second limits exposure and imposes an interaction cost. We propose a third method, ShoCons, that is spatially more efficient and neither limits user exposure nor imposes an interaction cost. To achieve this, ShoCons use a succinct iconic display of meta keys, limiting textual display to one character. We examine these alternatives in a controlled study, and find that when used with a high-level task, ShoCons enable faster task performance and an immediate increase in the accuracy of shortcut use.

Although mobile devices are generating a rapidly increasing proportion of search queries, search interfaces have not changed significantly to accommodate mobile constraints. In particular, imprecise search exists in the no-man's land between specific fact-finding and general browsing, and can be especially challenging on mobile devices, when user input is difficult and environmental distractions make remembering related information difficult. We examined the prevalence of these mobile search use cases in a two-week diary study, finding that imprecise and general search accounted for the large majority of difficulty with search. Hypothesizing that the ability to view a link neighborhood around the search result could be quite helpful in these cases, we designed GraphTiles, a visual interface for mobile search that exploits the structured entity relationships present in a significant portion of online datasets (e.g. IMDb [5] and LinkedIn [6]). In an experimental evaluation, users performed imprecise searches more quickly with GraphTiles than with a standard mobile site.

In his book Multimedia Learning [7], Richard Mayer asserts that viewers learn best from imagery that provides them with cues to help them organize new information into the correct knowledge structures. Designers have long been exploiting the Gestalt laws of visual grouping to deliver viewers those cues using visual hierarchy, often communicating structures much more complex than the simple organizations studied in psychological research. Unfortunately, designers are largely practical in their work, and have not paused to build a complex theory of structural communication. If we are to build a tool to help novices create effective and well structured visuals, we need a better understanding of how to create them. Our work takes a first step toward addressing this lack, studying how five of the many grouping cues (proximity, color similarity, common region, connectivity, and alignment) can be effectively combined to communicate structured text and imagery from real world examples. To measure the effectiveness of this structural communication, we applied a digital version of card sorting, a method widely used in anthropology and cognitive science to extract cognitive structures. We then used tree edit distance to measure the difference between perceived and communicated structures. Our most significant findings are: 1) with careful design, complex structure can be communicated clearly; 2) communicating complex structure is best done with multiple reinforcing grouping cues; 3) common region (use of containers such as boxes) is particularly effective at communicating structure; and 4) alignment is a weak structural communicator.

The popularity of mobile interfaces and application development is increasing along with the rapid expansion of the mobile electronics market and its migration from text-based applications to various multimedia applications. Real-time graphics and web applications are becoming one of the most attractive applications in mobile terminals due to their benefits for enterprise, gaming, and social media. This hands-on course will cover a comprehensive set of topics for developing mobile visual interfaces, including an overview of the mobile market, a comparison of mobile and desktop applications, and a survey of mobile development environments. We will also undertake a detailed discussion of UI development for mobiles, and graphics development for mobiles. During the course, various smartphones will be loaned to attendees for trying out several in-class exercises.

Traditional layered graph depictions such as flow charts are in wide use. Yet as graphs grow more complex, these depictions can become difficult to understand. Quilts are matrix-based depictions for layered graphs designed to address this problem. In this research, we first improve Quilts by developing three design alternatives, and then compare the best of these alternatives to better-known node-link and matrix depictions. A primary weakness in Quilts is their depiction of skip links, links that do not simply connect to a succeeding layer. Therefore in our first study, we compare Quilts using color-only, text-only, and mixed (color and text) skip link depictions, finding that path finding with the color-only depiction is significantly slower and less accurate, and that in certain cases, the mixed depiction offers an advantage over the text-only depiction. In our second study, we compare Quilts using the mixed depiction to node-link diagrams and centered matrices. Overall results show that users can find paths through graphs significantly faster with Quilts (46.6 secs) than with node-link (58.3 secs) or matrix (71.2 secs) diagrams. This speed advantage is still greater in large graphs (e.g. in 200 node graphs, 55.4 secs vs. 71.1 secs for node-link and 84.2 secs for matrix depictions).

Abstract Urban spaces consist of a complex collection of buildings, parcels, blocks and neighbourhoods interconnected by streets. Accurately modelling both the appearance and the behaviour of dense urban spaces is a significant challenge. The recent surge in urban data and its availability via the Internet has fomented a significant amount of research in computer graphics and in a number of applications in urban planning, emergency management and visualization. In this paper, we seek to provide an overview of methods spanning computer graphics and related fields involved in this goal. Our paper reports the most prominent methods in urban modelling and rendering, urban visualization and urban simulation models. A reader will be well versed in the key problems and current solution methods.

GeneaQuilts is a new visualization technique for representing large genealogies of up to several thousand individuals. The visualization takes the form of a diagonally-filled matrix, where rows are individuals and columns are nuclear families. After identifying the major tasks performed in genealogical research and the limits of current software, we present an interactive genealogy exploration system based on GeneaQuilts. The system includes an overview, a timeline, search and filtering components, and a new interaction technique called Bring & Slide that allows fluid navigation in very large genealogies. We report on preliminary feedback from domain experts and show how our system supports a number of their tasks.

We propose an adaptive form of frameless rendering with the potential to dramatically increase rendering speed over conventional interactive rendering approaches. Without the rigid sampling patterns of framed renderers, sampling and reconstruction can adapt with very fine granularity to spatio-temporal color change. A sampler uses closed-loop feedback to guide sampling toward edges or motion in the image. Temporally deep buffers store all the samples created over a short time interval for use in reconstruction and as sampler feedback. GPU-based reconstruction responds both to sampling density and space-time color gradients. Where the displayed scene is static, spatial color change dominates and older samples are given significant weight in reconstruction, resulting in sharper and eventually antialiased images. Where the scene is dynamic, more recent samples are emphasized, resulting in less sharp but more up-to-date images. We also use sample reprojection to improve reconstruction and guide sampling toward occlusion edges, undersampled regions, and specular highlights. In simulation our frameless renderer requires an order of magnitude fewer samples than traditional rendering of similar visual quality (as measured by RMS error), while introducing overhead amounting to 15% of computation time.

Traffic anomalies and attacks are commonplace in today's networks and identifying them rapidly and accurately is critical for large network operators. For a statistical intrusion detection system (IDS), it is crucial to detect at the flow-level for accurate detection and mitigation. However, existing IDS systems offer only limited support for: 1) interactively examining detected intrusions and anomalies; 2) analyzing worm propagation patterns; 3) and discovering correlated attacks. These problems are becoming even more acute as the traffic on today's high-speed routers continues to grow. IDGraphs is an interactive visualization system for intrusion detection that addresses these challenges. The central visualization in the system is a flow-level trace plotted with time on the horizontal axis and aggregated number of unsuccessful connections on the vertical axis. We then summarize a stack of tens or hundreds of thousands of these traces using the histographs (Pin Ren and Watson, 2005) technique, which maps data frequency at each pixel to brightness. Users may then interactively query the summary view, performing analysis by highlighting subsets of the traces. For example, brushing a linked correlation matrix view highlights traces with similar patterns, revealing distributed attacks that are difficult to detect using standard statistical analysis. We apply IDGraphs system to a real network router data-set with 179M flow-level records representing a total traffic of 1.16TB. The system successfully detects and analyzes a variety of attacks and anomalies, including port scanning, worm outbreaks, stealthy TCP SYN floodings, and some distributed attacks.

Guest Editorial: Special Issue on Haptics, Virtual, and Augmented Reality

Level of detail (LOD) is widely used to control visual feedback in interactive applications. LOD control is typically based on perception at threshold -- the conditions in which a stimulus first becomes perceivable. Yet most LOD manipulations are quite perceivable and occur well above threshold. Moreover, research shows that supra-threshold perception differs drastically from perception at threshold. In that case, should supra-threshold LOD control also differ from LOD control at threshold?In two experiments, we examine supra-threshold LOD control in the visual periphery and find that indeed, it should differ drastically from LOD control at threshold. Specifically, we find that LOD must support a task-dependent level of reliable perceptibility. Above that level, perceptibility of LOD control manipulations should be minimized, and detail contrast is a better predictor of perceptibility than detail size. Below that level, perceptibility must be maximized, and LOD should be improved as eccentricity rises or contrast drops. This directly contradicts prevailing threshold-based LOD control schemes, and strongly suggests a reexamination of LOD control for foveal display.

Interruptible rendering is a novel approach to the fidelity-versus-performance tradeoff ubiquitous in real-time rendering. Interruptible rendering unifies spatial error caused by rendering coarse approximations for speed and temporal error caused by the delay imposed by rendering into a single image-space error measure. The heart of this approach is a progressive rendering framework that renders a coarse image into the back buffer and continuously refines it while monitoring temporal error. When temporal error exceeds the spatial error caused by coarse rendering, further refinement is pointless, and the image is displayed. We discuss how to adapt different rendering algorithms for interruptible use and present implementations based on polygonal rendering and ray casting. Interruptible rendering provides a low-latency, self-tuning approach to interactive rendering. To evaluate our results we introduce a "gold standard" approach that measures dynamic visual error against a hypothetical perfect rendering and show that interruptible rendering is more accurate than standard fidelity-versus-performance schemes. This improved accuracy enables better interactive rendering, both for complex models and complex rendering modalities such as ray casting.

This paper describes an experimental investigation into the relationship of delay to user performance in 3D object placement. In the first experiment, 10 participants performed a placement task as delay and placement difficulty varied. Results were analyzed with statistical analyses of variance. Placement errors and times rose as delay and difficulty increased. An interaction indicated that controlling delay is particularly important when placement is already difficult. In vehicle control tasks, previewing forecasts required input, and is a useful way of compensating for delay. The second experiment examined the relationship of previewing to delay and difficulty in placement. With regard to delay and difficulty, the 15 participants replicated the first experiment's results. Previewing reduced placement times directly, and mitigated the effects of delay and difficulty. A three-way interaction indicated that when previewing is used, more delay can be tolerated even in difficult placement tasks.

Assessments of spatial, constructional ability are used widely in cognitive research and in clinical diagnosis of disease or injury. Some believe that three-dimensional (3D) forms of these assessments would be particularly sensitive, but difficulties with consistency in administration and scoring have limited their use. We describe Cognitive Cubes, a novel computerized tool for 3D constructional assessment that increases consistency and promises improvements in flexibility, reliability, sensitivity and control. Cognitive Cubes makes use of ActiveCube, a novel tangible user interface for describing 3D shape. In testing, Cognitive Cubes was sensitive to differences in cognitive ability and task, and correlated well to a standard paper-and-pencil 3D spatial assessment

We present semisimp, a tool for semiautomatic simplification of three dimensional polygonal models. Existing automatic simplification technology is quite mature, but is not sensitive to the heightened importance of distinct semantic model regions such as faces and limbs, nor to simplification constraints imposed by model usage such as animation. semisimp allows users to preserve such regions by intervening in the simplification process. Users can manipulate the order in which basic simplifications are applied to redistribute model detail, improve the simplified models themselves by repositioning vertices with propagation to neighboring levels of detail, and adjust the hierarchical partitioning of the model surface to segment simplification and improve control of reordering and position propagation. ACM Category and Subject Descriptor: I.3.5 [Computer Graphics] Computational Geometry and Object Modeling - hierarchy and geometric transformations Additional Keywords: model simplificatio...

This paper is a study of techniques for measuring and predicting visual fidelity. As visual stimuli we use polygonal models, and vary their fidelity with two different model simplification algorithms. We also group the stimuli into two object types: animals and man made artifacts. We examine three different experimental techniques for measuring these fidelity changes: naming times, ratings, and preferences. All the measures were sensitive to the type of simplification and level of simplification. However, the measures differed from one another in their response to object type. We also examine several automatic techniques for predicting these experimental measures, including techniques based on images and on the models themselves. Automatic measures of fidelity were successful at predicting experimental ratings, less successful at predicting preferences, and largely failures at predicting naming times. We conclude with suggestions for use and improvement of the experimental and automatic measures of visual fidelity.

Model simplification researchers require quality heuristics to guide simplification, and quality predictors to allow comparison of different simplification algorithms. However, there has been little evaluation of these heuristics or predictors. We present an evaluation of quality predictors. Our standard of comparison is naming time, a well established measure of recognition from cognitive psychology. Thirty participants named models of familiar objects at three levels of simplification. Results confirm that naming time is sensitive to model simplification. Correlations indicate that view-dependent image quality predictors are most effective for drastic simplifications, while view-independent three-dimensional predictors are better for more moderate simplifications.

As modeling and visualization applications proliferate, there arises a need to simplify large polygonal models at interactive rates. We present a simplification algorithm suitable for interactive applications. The algorithm is fast and can guarantee displayable results within a given time limit. Results also have good quality. Inspired by splitting algorithms from the vector quantization literature, we simplify models in reverse, from coarse to fine.

CAVE/sup TM/ displays offer many advantages over other virtual reality (VR) displays, including a large, unencumbered viewing space. Unfortunately, the typical tracking subsystems used with CAVE/sup TM/ displays tether the user and lessen this advantage. We have designed a simple, low-cost foot tracker that is wireless, leaving the user free to move. The tracker can be assembled for less than $200 US, and achieves an accuracy of /spl plusmn/10 cm at a 20-Hz sampling rate. We have tested the prototype with two applications: a visualization supporting close visual inspection, and a walkthrough of the campus. Although the tracking was convincing, it was clear that the tracker's limitations make it less than ideal for applications requiring precise visual inspection. However the freedom of motion allowed by the tracker was a compelling supplement to our campus walkthrough, allowing users to stroll and look around corners.

Previous work has demonstrated the utility of reductions in the level of detail (LOD) in the periphery of head-tracked, large field of view displays. This paper provides a psychophysically based model, centered around an eye/head movement tradeoff, that explains the effectiveness of peripheral degradation and suggests how peripherally degraded displays should be designed. An experiment evaluating the effect on search performance of the shape and area of the high detail central area (inset) in peripherally degraded displays was performed, results indicated that inset shape is not a significant factor in performance. Inset area, however, was significant: performance with displays subtending at least 30 degrees of horizontal and vertical angle was not significantly different from performance with an undegraded display. These results agreed with the proposed model.

Two user studies were performed to evaluate the effect of level-of-detail (LOD) degradation in the periphery of head-mounted displays on visual search performance. In the first study, spatial detail was degraded by reducing resolution. In the second study, detail was degraded in the color domain by using grayscale in the periphery. In each study, 10 subjects were given a complex search task that required users to indicate whether or not a target object was present among distracters. Subjects used several different displays varying in the amount of detail presented. Frame rate, object location, subject input method, and order of display use were all controlled. The primary dependent measures were search time on correctly performed trials and the percentage of all trials correctly performed. Results indicated that peripheral LOD degradation can be used to reduce color or spatial visual complexity by almost half in some search tasks with out significantly reducing performance.