Statistical graphs are becoming common in many fields. Modern authoring tools offer easy ways to create complex graphs. Despite multiple sources of advice, graph designers have little objective evidence on which to base design decisions to alleviate complexity. We aimed to fill a gap in the evidence of the difficulty created by two design features: adding one data series to a simple graph or adding dependent axes to a graph. We found main effects of adding a data series, of a greater number of data points, and an additional dependent axis, but primarily on the time readers studied the graph. Via deeper analysis, we explained the difficulty graph readers experienced when answering questions. That explanation focuses on the selection of points from a source graph to be part of the query. Based on our results, we recommend avenues for research on graph complexity and graph comprehension measurement.

In theory, visual saliency in a graph should be used to draw attention to its most important component(s). Thus salience is commonly viewed both as a basis for predicting where graph readers are likely to look, and as a core design technique for emphasizing what a reader is intended to see among competing elements in a given chart or plot. We briefly review models, metrics, and applicable theories as they pertain to graphs. We then introduce new saliency models based on perceptual and cognitive theories that, to our knowledge, have not been previously applied to models for viewing statistical graphics. The resulting frameworks can be broadly classified as bottom-up perceptual models or top-down cognitive models. We report the results of evaluating these new theory-informed approaches on gaze data collected for statistical graphs and for more general information visualizations. Interestingly, the new models fare no better than previous ones. We review the experience, noting why we expected these hypotheses to be effective, and discuss how and why their performance did not match our aspirations. We suggest directions for future research that may help to clarify some of the issues raised.

An experiment was conducted to investigate the utility of a number of iconographic styles in relaying ordinal depth information at vista space distances of more than 1900m. The experiment consisted of two tasks: distance judgments with respect to discrete zones, and ordinal depth determination in the presence of icon overlap. The virtual object representations were chosen based on their effectiveness, as demonstrated in previous studies. The first task is an adaptation of a previous study investigating distance judgments of occluded objects at medium field distances. We found that only one of the icon styles fared better than guessing. The second is a novel task important to situation awareness and tested two specific cases: ordinal depth of icons with 50% and 100% overlap. We found that the case of full overlap made the task effectively impossible with all icon styles, whereas in the case of partial overlap, the Ground Plane had a clear advantage.

The Microsoft Kinect for Xbox 360 (“Kinect”) provides a convenient and inexpensive depth sensor and, with the Microsoft software development kit, a skeleton tracker (Figure 2). These have great potential to be useful as virtual environment (VE) control interfaces for avatars or for viewpoint control. In order to determine its suitability for our applications, we devised and conducted tests to measure standard performance specifications for tracking systems. We evaluated the noise, accuracy, resolution, and latency of the skeleton tracking software. We also measured the range in which the person being tracked must be in order to achieve these values.

Multivariate visualization techniques have attracted great interest as the dimensionality of data sets grows. One premise of such techniques is that simultaneous visual representation of multiple variables will enable the data analyst to detect patterns amongst multiple variables. Such insights could lead to development of new techniques for rigorous (numerical) analysis of complex relationships hidden within the data. Two natural questions arise from this premise: Which multivariate visualization techniques are the most effective for high-dimensional data sets? How does the analysis task change this utility ranking? We present a user study with a new task to answer the first question. We provide some insights to the second question based on the results of our study and results available in the literature. Our task led to significant differences in error, response time, and subjective workload ratings amongst four visualization techniques. We implemented three integrated techniques (Data-driven Spots, Oriented Slivers, and Attribute Blocks), as well as a baseline case of separate grayscale images. The baseline case fared poorly on all three measures, whereas Datadriven Spots yielded the best accuracy and was among the best in response time. These results differ from comparisons of similar techniques with other tasks, and we review all the techniques, tasks, and results (from our work and previous work) to understand the reasons for this discrepancy.

Multi-valued data sets are increasingly common, with the number of dimensions growing. A number of multi-variate visualization techniques have been presented to display such data. However, evaluating the utility of such techniques for general data sets remains difficult. Thus most techniques are studied on only one data set. Another criticism that could be levied against previous evaluations of multi-variate visualizations is that the task doesn't require the presence of multiple variables. At the same time, the taxonomy of tasks that users may perform visually is extensive. We designed a task, trend localization, that required comparison of multiple data values in a multi-variate visualization. We then conducted a user study with this task, evaluating five multivariate visualization techniques from the literature (Brush Strokes, Data-Driven Spots, Oriented Slivers, Color Blending, Dimensional Stacking) and juxtaposed grayscale maps. We report the results and discuss the implications for both the techniques and the task.

The three papers in this special section are extended versions of papers presented at the International Symposium on Mixed and Augmented Reality (ISMAR).

In collaborative augmented reality (AR) missions, much georegistered information is collected and sent to a command and control center. This paper describes the concept and prototypical implementation of a mixed reality (MR) based system that integrates georegistered information from AR systems and other sources on a virtual globe. The application can be used for a command and control center to monitor the field operation where multiple AR users are engaging in a collaborative mission. Google Earth is used to demonstrate the system, which integrates georegistered icons, live video streams from field operators or surveillance cameras, 3D models, and satellite or aerial photos into one MR environment.

Properly perceived stereo display is often assumed to be vital in augmented reality (AR) displays used for close distances, echoing the general understanding from the perception literature. However, the accuracy of the perception of stereo in head-worn AR displays has not been studied greatly. We conducted a user study to elicit the precision of stereo perception in AR and its dependency on the size and contrast of the stimulus. We found a strong effect of contrast on the disparity users desired to make a virtual target verge at the distance of a real reference object. We also found that whether the target began behind or in front of the reference in a method of adjustments protocol made a significant difference. The mean disparity in the rendering that users preferred had a strong linear relationship with their IPD. We present our results and infer stereoacuity thresholds.

How do users of virtual environments perceive virtual space? Many experiments have explored this question, but most of these have used head-mounted immersive displays. This paper reports an experiment that studied large-screen immersive displays at medium-field distances of 2 to 15 meters. The experiment measured ego-centric depth judgments in a CAVE, a tiled display wall, and a real-world outdoor field as a control condition. We carefully modeled the outdoor field to make the three environments as similar as possible. Measuring egocentric depth judgments in large-screen immersive displays requires adapting new measurement protocols; the experiment used timed imagined walking, verbal estimation, and triangulated blind walking. We found that depth judgments from timed imagined walking and verbal estimation were very similar in all three environments. However, triangulated blind walking was accurate only in the out-door field; in the large-screen immersive displays it showed under-estimation effects that were likely caused by insufficient physical space to perform the technique. These results suggest using timed imagined walking as a primary protocol for assessing depth perception in large-screen immersive displays. We also found that depth judgments in the CAVE were more accurate than in the tiled display wall, which suggests that the peripheral scenery offered by the CAVE is helpful when perceiving virtual space.

We tested users' depth perception of virtual objects in our mobile augmented reality (AR) system in both indoor and outdoor environments using a depth matching task. The indoor environment is characterized by strong linear perspective cues; we attempted to re-create these cues in the outdoor environment. In the indoor environment, we found an overall pattern of underestimation of depth that is typical for virtual environments and AR systems. However, in the outdoor environment, we found that subjects overestimated depth. In addition, our synthetic linear perspective cues met with a measure of success, leading users to reduce their estimate of the depth of distant objects. We describe the experimental procedure, analyze the data, present the results of the study, and discuss the implications for mobile, outdoor AR systems.

Augmented reality (AR) displays often reduce the visual capabilities of the user. This reduction can be measured both objectively and through user studies. We acquired objective measurements with a color meter and conducted two user studies for each of two key measurements. First was the combined effect of resolution and display contrast, which equate to the visual acuity and apparent brightness. The combined effect may be captured by the contrast sensitivity function and measured through analogs of optometric exams. We expanded the number of commercial devices tested in previous studies, including higher resolution and video-overlay AR displays. We found patterns of reduced contrast sensitivity similar to previous work; however, we saw that all displays enabled users to achieve the maximum possible acuity with at least moderate levels of contrast. The second measurement was the perception of color. Objective measurements showed a distortion of color, notably in the blue region of color space. We devised a color matching task to quantify the distortion of color perception, finding that the displays themselves were poor at showing colors in the blue region of color space and that the perceptual distortion of such colors was even greater than the objective distortion. We noted significantly different distortions and variability between displays.

The two papers in this special section are extended versions of papers originally presented at the International Symposium on Mixed and Augmented Reality (ISMAR) 2007. These two papers won awards at the symposium.

We conducted a user study of the effect of registration error on performance of tracking distant objects in augmented reality. Categorizing error by types that are often used as specifications, we hoped to derive some insight into the ability of users to tolerate noise, latency, and orientation error. We used measurements from actual systems to derive the parameter settings. We expected all three errors to influence userspsila ability to perform the task correctly and the precision with which they performed the task. We found that high latency had a negative impact on both performance and response time. While noise consistently interacted with the other variables, and orientation error increased user error, the differences between ldquohighrdquo and ldquolowrdquo amounts were smaller than we expected. Results of userspsila subjective rankings of these three categories of error were surprisingly mixed. Users believed noise was the most detrimental, though statistical analysis of performance refuted this belief. We interpret the results and draw insights for system design.

Abstract-A fundamental problem in optical, see-through augmented reality (AR) is characterizing how it affects the perception of spatial layout and depth. This problem is important because AR system developers need to both place graphics in arbitrary spatial relationships with real-world objects, and to know that users will perceive them in the same relationships. Furthermore, AR makes possible enhanced perceptual techniques that have no real-world equivalent, such as x-ray vision, where AR users are supposed to perceive graphics as being located behind opaque surfaces. This paper reviews and discusses protocols for measuring egocentric depth judgments in both virtual and augmented environments, and discusses the well-known problem of depth underestimation in virtual environments. It then describes two experiments that measured egocentric depth judgments in AR. Experiment I used a perceptual matching protocol to measure AR depth judgments at medium and far-field distances of 5 to 45 meters. The experiment studied the effects of upper versus lower visual field location, the x-ray vision condition, and practice on the task. The experimental findings include evidence for a switch in bias, from underestimating to overestimating the distance of AR-presented graphics, at approximately 23 meters, as well as a quantification of how much more difficult the x-ray vision condition makes the task. Experiment II used blind walking and verbal report protocols to measure AR depth judgments at distances of 3 to 7 meters. The experiment examined real-world objects, real-world objects seen through the AR display, virtual objects, and combined real and virtual objects. The results give evidence that the egocentric depth of AR objects is underestimated at these distances, but to a lesser degree than has previously been found for most virtual reality environments. The results are consistent with previous studies that have implicated a restricted field-of-view, combined with an inability for observers to scan the ground plane in a near-to-far direction, as explanations for the observed depth underestimation.

In order to be able to perceive and recognize objects or surface properties of objects, one must be able to resolve the features. These perceptual tasks can be difficult for both graphical representations and real objects in augmented reality (AR) displays. This paper presents the results of objective measurements and two user studies. The first evaluation explores visual acuity and contrast sensitivity; the second explores color perception. Both experiments test users' capabilities with their natural vision against their capabilities using commercially-available AR displays. The limited graphical resolution, reduced brightness, and uncontrollable visual context of the merged environment demonstrably reduce users' visual capabilities. The paper concludes by discussing the implications for display design and AR applications, as well as outlining possible extensions to the current studies.

Virtual reality (VR) and augmented reality (AR) systems are reaching sufficient maturity that some systems are being used on a regular basis by users and others are close to implementation. There are limitations, however, that have prevented many systems from being truly useful for users. An important limitation is the lack of understanding of human factors issues, such as human perceptual and cognitive limitations, that affect the potential utility of VR or AR systems.

Stereo and bi-ocular head-mounted displays (HMDs) require the user to fuse two images into a coherent picture of the threedimensional world. The human visual system performs this task constantly, but when the input images contain both real and graphical depictions, the problem becomes more difficult. A vertical disparity in the graphics causes diplopia for users trying to fuse the real and virtual objects simultaneously. We implement three methods to measure and correct this disparity and assess them with a collection of a single model of optical see-through HMD.

Continued advances in display hardware, computing power, networking, and rendering algorithms have all converged to dramatically improve large high-resolution display capabilities. We present a survey on prior research with large high-resolution displays. In the hardware configurations section we examine systems including multi-monitor workstations, reconfigurable projector arrays, and others. Rendering and the data pipeline are addressed with an overview of current technologies. We discuss many applications for large high-resolution displays such as automotive design, scientific visualization, control centers, and others. Quantifying the effects of large high-resolution displays on human performance and other aspects is important as we look toward future advances in display technology and how it is applied in different situations. Interacting with these displays brings a different set of challenges for HCI professionals, so an overview of some of this work is provided. Finally, we present our view of the top ten greatest challenges in large highresolution displays.

In the late 90’s the emergence of high performance 3D commodity graphics cards opened the way to use PC clusters for high performance Virtual Reality (VR) applications. Today PC clusters are broadly used to drive multi projector immersive environments. In this paper, we survey the different approaches that have been developed to use PC clusters for VR applications. We review the most common software tools that enable to take advantage of the power of clusters. We also discuss some new trends.

A fundamental problem in optical, see-through augmented reality (AR) is characterizing how it affects the perception of spatial layout and depth. This problem is important because AR system developers need to both place graphics in arbitrary spatial relationships with real-world objects, and to know that users will perceive them in the same relationships. Furthermore, AR makes possible enhanced perceptual techniques that have no real-world equivalent, such as x-ray vision, where AR users are supposed to perceive graphics as being located behind opaque surfaces. This paper reviews and discusses techniques for measuring egocentric depth judgments in both virtual and augmented environments. It then describes a perceptual matching task and experimental design for measuring egocentric AR depth judgments at medium- and far-field distances of 5 to 45 meters. The experiment studied the effect of field of view, the x-ray vision condition, multiple distances, and practice on the task. The paper relates some of the findings to the well-known problem of depth underestimation in virtual environments, and further reports evidence for a switch in bias, from underestimating to overestimating the distance of AR-presented graphics, at 23 meters. It also gives a quantification of how much more difficult the x-ray vision condition makes the task, and then concludes with ideas for improving the experimental methodology.

Embedded sensors are envisioned to provide information about a variety of environments. One use of sensors is for military intelligence gathering in the field. Typically, these sensors are manually placed in an environment. In order to know whether the appropriate domain is covered by the sensor arrangement, we build an interface that provides visualizations of the sensor domains and coverage. To assist with planning the sensor layout, our new interface allows the user to interactively specify new locations and see the effect on the domain. To verify that line-of-sight communications requirements are met, the visualizations also show the user these relationships. These simple visualizations improve the understanding of the sensor domain. The interactive 3D display gives the user a tool for planning how to best use the available resources to get information

Augmented reality (AR) systems present a mixture of virtual and real objects. The challenge for AR system evaluators is how to tell whether the virtual world is effective at conveying the sense of reality. It may never be possible or even necessary to determine whether the user is truly fooled in all situations or is merely suspending disbelief, but one can objectively measure the effectiveness of an AR environment with a task-based approach. We present the results of our first such experiment, involving low-level perceptual tasks of recognition and depth matching.

To achieve accurate registration, the transformations which locate the tracking system components with respect to the environment must be known. These transformations relate the base of the tracking system to the virtual world and the tracking system's sensor to the graphics display. In this paper we present a unified, general calibration method for calculating these transformations. A user is asked to align the display with objects in the real world. Using this method, the sensor to display and tracker base to world transformations can be determined with as few as three measurements.

A useful function of augmented reality (AR) systems is their ability to visualize occluded infrastructure directly in a user's view of the environment. This is especially important for our application context, which utilizes mobile AR for navigation and other operations in an urban environment. A key problem in the AR field is how to best depict occluded objects in such a way that the viewer can correctly infer the depth relationships between different physical and virtual objects. Showing a single occluded object with no depth context presents an ambiguous picture to the user. But showing all occluded objects in the environments leads to the "Superman's X-ray vision" problem, in which the user sees too much information to make sense of the depth relationships of objects. Our efforts differ qualitatively from previous work in AR occlusion, because our application domain involves far-field occluded objects, which are tens of meters distant from the user. Previous work has focused on near-field occluded objects, which are within or just beyond arm's reach, and which use different perceptual cues. We designed and evaluated a number of sets of display attributes. We then conducted a user study to determine which representations best express occlusion relationships among far-field objects. We identify a drawing style and opacity settings that enable the user to accurately interpret three layers of occluded objects, even in the absence of perspective constraints.

We describe two engineering experiments designed to evaluate the effectiveness of Measurand's ShapeTape for wearable, mobile interaction. Our initial results suggest that the ShapeTape is not appropriate for interactions which require a high degree of accuracy. However, ShapeTape is capable of reproducing the qualitative motion the user is performing and thus could be used to support 3D gesture-based interaction.

The full power of mobile augmented and virtual reality systems is realized when these systems are connected to one another to immersive virtual environments, and to remote information servers. Connections are usually made through wireless networks. However, wireless networks cannot guarantee connectivity and their bandwidth can be highly constrained. The authors present a robust event-based data distribution mechanism for mobile augmented reality and virtual environments. It is based on replicated databases, pluggable networking protocols, and communication channels. We demonstrate the mechanism in the Battlefield Augmented Reality System (BARS) situation awareness system, which is composed of several mobile augmented reality systems, immersive and desktop-based virtual reality systems, a 2D map-based multi-modal system, handheld PCs, and other sources of information.

No abstract available.

Presents a new approach for establishing correspondence between two homeomorphic 3D polyhedral models. The user can specify corresponding feature pairs on the polyhedra with a simple and intuitive interface. Based on these features, our algorithm decomposes the boundary of each polyhedron into the same number of morphing patches. A 2D mapping for each morphing patch is computed in order to merge the topologies of the polyhedra one patch at a time. We create a morph by defining morphing trajectories between the feature pairs and by interpolating them across the merged polyhedron. The user interface provides high-level control as well as local refinement to improve the morph. The implementation has been applied to several complex polyhedra composed of thousands of polygons. The system can also handle non-simple polyhedra that have holes.

SystemsRegistration (or alignment) of the synthetic imagery with the real world is crucial in augmented reality (AR) systems.The data from user-input devices, tracking devices, and imaging devices need to be registered spatially and temporally with the user's view of the surroundings.Each device haa an associated delay between its observations of the world and the moment when the AR display presented to the user appe-to be afkted by a change in the data.We call the differences in delay the relative Iatencies.Relative latency is a source of misregistration and should be reduced.We give general methods for handling multiple data streams with different latency values associated with them in a working AR system.We measure the latency differences (part of the system dependent set of calibrations), time-stamp on-host, adjust the moment of sampling, and interpolate or extrapolate data streams.By using these schemes, a more accurate and consistent view is computed and presented to the user.

We define a rotation field by extending the notion of a vector field to rotations. A vector field has a vector as a value at each point of its domain; a rotation field has a rotation as a value at each point of its domain. Rotation fields result from mapping the orientation error of tracking systems. We build upon previous methods for the visualization of vector fields, tensor fields and rotations at a point, to visualize a rotation field resulting from calibration of a commonly-used magnetic tracking system.

Accurate registration between real and virtual objects is crucial for augmented reality applications.Existing tracking methods are individually inadequate: magnetic trackers are inaccurate, mechanical trackers are cumbersome, and vision-based trackers are computationally problematic.We present a hybrid tracking method that combines the accuracy of vision-based tracking with the robustness of magnetic tracking without compromising real-time performance or usability.We demonstrate excellent registration in three sample applications.

We present a real-time stereoscopic video-see-through augmented reality (AR) system applied to the medical procedure known as ultrasound-guided needle biopsy of the breast.The AR system was used by a physician during procedures on breast models and during non-invasive examinations of human subjects.The system merges rendered live ultrasound data and geometric elements with stereo images of the patient acquired through head-mounted video cameras and presents these merged images to the physician in a head-mounted display.The physician sees a volume visualization of the ultrasound data directly under the ultrasound probe, properly registered within the patient and with the biopsy needle.Using this system, a physician successfully guided a needle into an artificial tumor within a training phantom of a human breast.We discuss the construction of the AR system and the issues and decisions which led to the system architecture and the design of the video see-through head-mounted display.We designed methods to properly resolve occlusion of the real and synthetic image elements.We developed techniques for realtime volume visualization of time-and position-varying ultrasound data.We devised a hybrid tracking system which achieves improved registration of synthetic and real imagery and we improved on previous techniques for calibration of a magnetic tracker.