High-quality immersive display technologies are becoming mainstream with the release of head-mounted displays (HMDs) such as the Oculus Rift. These devices potentially represent an affordable alternative to the more traditional, centralised CAVE-style immersive environments. One driver for the development of CAVE-style immersive environments has been collaborative sense-making. Despite this, there has been little research on the effectiveness of collaborative visualisation in CAVE-style facilities, especially with respect to abstract data visualisation tasks. Indeed, very few studies have focused on the use of these displays to explore and analyse abstract data such as networks and there have been no formal user studies investigating collaborative visualisation of abstract data in immersive environments. In this paper we present the results of the first such study. It explores the relative merits of HMD and CAVE-style immersive environments for collaborative analysis of network connectivity, a common and important task involving abstract data. We find significant differences between the two conditions in task completion time and the physical movements of the participants within the space: participants using the HMD were faster while the CAVE2 condition introduced an asymmetry in movement between collaborators. Otherwise, affordances for collaborative data analysis offered by the low-cost HMD condition were not found to be different for accuracy and communication with the CAVE2. These results are notable, given that the latest HMDs will soon be accessible (in terms of cost and potentially ubiquity) to a massive audience.

We report the findings of a study designed to evaluate the effect of stereopsis and field of regard (FOR) in two different mixed reality (MR) simulation platforms: a head-mounted display (HMD) and a CAVE. We compared the performance of participants on two levels of stereopsis (mono and stereo) and two levels of FOR (90 degrees and 270 degrees) using a variety of scientific visualization tasks. Among the findings, we observed that not all the effects were consistent between the platforms. Stereo alone or in combination with higher FOR improved completion time on both platforms. However, adding stereo solely reduced the accuracy of the participants on the CAVE and improved on the HMD. Our findings extend prior knowledge on the contribution of visual fidelity components and suggests potential limits on MR simulation between platforms.

While there have been hundreds of psychological studies using virtual reality (VR) over the past few decades, those studies have almost exclusively been conducted in laboratory settings using small samples of college students with little demographic variance. Hence, the generalizability of the results is limited, as not all findings will apply outside the college demographic. In this paper, we present our mobile VR project (Immersion at Scale) where we conduct VR experiment sessions in naturalistic settings (e.g., local events, museums, etc.). On average, we were able to collect data from 20-25 people for each 4-hour data collection session of Immersion at Scale. We discovered a number of obstacles and opportunities based on bringing VR out into the field. Thus, we do not focus on experimental stimuli and results, but methodological guidelines based on our iterative design improvements from pilot testing.

We present the results of a variable information space experiment, targeted at exploring the scalability limits of immersive highresolution, tiled-display walls under physical navigation. Our work is motivated by a lack of evidence supporting the extension of previously established benefits on substantially large, room-shaped displays. Using the Reality Deck, a gigapixel resolution immersive display, as its apparatus, our study spans four display form-factors, starting at 100 megapixels arranged planarly and up to one gi-gapixel in a horizontally immersive setting. We focus on four core tasks: visual search, attribute search, comparisons and pattern finding. We present a quantitative analysis of per-task user performance across the various display conditions. Our results demonstrate improvements in user performance as the display form-factor changes to 600 megapixels. At the 600 megapixel to 1 gigapixel transition, we observe no tangible performance improvements and the visual search task regressed substantially. Additionally, our analysis of subjective mental effort questionnaire responses indicates that subjective user effort grows as the display size increases, validating previous studies on smaller displays. Our analysis of the participants' physical navigation during the study sessions shows an increase in user movement as the display grew. Finally, by visualizing the participants' movement within the display apparatus space, we discover two main approaches (termed “overview” and “detail”) through which users chose to tackle the various data exploration tasks. The results of our study can inform the design of immersive high-resolution display systems and provide insight into how users navigate within these room-sized visualization spaces.

Volume visualization is an important technique for analyzing datasets from a variety of different scientific domains. Volume data analysis is inherently difficult because volumes are three-dimensional, dense, and unfamiliar, requiring scientists to precisely control the viewpoint and to make precise spatial judgments. Researchers have proposed that more immersive (higher fidelity) VR systems might improve task performance with volume datasets, and significant results tied to different components of display fidelity have been reported. However, more information is needed to generalize these results to different task types, domains, and rendering styles. We visualized isosurfaces extracted from synchrotron microscopic computed tomography (SR-μCT) scans of beetles, in a CAVE-like display. We ran a controlled experiment evaluating the effects of three components of system fidelity (field of regard, stereoscopy, and head tracking) on a variety of abstract task categories that are applicable to various scientific domains, and also compared our results with those from our prior experiment using 3D texture-based rendering. We report many significant findings. For example, for search and spatial judgment tasks with isosurface visualization, a stereoscopic display provides better performance, but for tasks with 3D texture-based rendering, displays with higher field of regard were more effective, independent of the levels of the other display components. We also found that systems with high field of regard and head tracking improve performance in spatial judgment tasks. Our results extend existing knowledge and produce new guidelines for designing VR systems to improve the effectiveness of volume data analysis.

In our research agenda to study the effects of immersion (level of fidelity) on various tasks in virtual reality (VR) systems, we have found that the most generalizable findings come not from direct comparisons of different technologies, but from controlled simulations of those technologies. We call this the mixed reality (MR) simulation approach. However, the validity of MR simulation, especially when different simulator platforms are used, can be questioned. In this paper, we report the results of an experiment examining the effects of field of regard (FOR) and head tracking on the analysis of volume visualized micro-CT datasets, and compare them with those from a previous study. The original study used a CAVE-like display as the MR simulator platform, while the present study used a high-end head-mounted display (HMD). Out of the 24 combinations of system characteristics and tasks tested on the two platforms, we found that the results produced by the two different MR simulators were similar in 20 cases. However, only one of the significant effects found in the original experiment for quantitative tasks was reproduced in the present study. Our observations provide evidence both for and against the validity of MR simulation, and give insight into the differences caused by different MR simulator platforms. The present experiment also examined new conditions not present in the original study, and produced new significant results, which confirm and extend previous existing knowledge on the effects of FOR and head tracking. We provide design guidelines for choosing display systems that can improve the effectiveness of volume visualization applications.

Studying what design features are necessary and effective for educational virtual environments (VEs), we focused on two design issues: level of environmental detail and method of navigation. In a controlled experiment, participants studied animal facts distributed among different locations in an immersive VE. Participants viewed the information as either an automated tour through the environment or with full navigational control. The experiment also compared two levels of environmental detail: a sparse environment with only the animal fact cards and a detailed version that also included landmark items and ground textures. The experiment tested memory and understanding of the animal information. Though neither environmental detail nor navigation type significantly affected learning outcomes, the results suggest that manual navigation may have negatively affected the learning activity. Also, learning scores were correlated with both spatial ability and video game usage, suggesting that educational VEs may not be an appropriate presentation method for some learners.

Volume visualization has been widely used for decades for analyzing datasets ranging from 3D medical images to seismic data to paleontological data. Many have proposed using immersive virtual reality (VR) systems to view volume visualizations, and there is anecdotal evidence of the benefits of VR for this purpose. However, there has been very little empirical research exploring the effects of higher levels of immersion for volume visualization, and it is not known how various components of immersion influence the effectiveness of visualization in VR. We conducted a controlled experiment in which we studied the independent and combined effects of three components of immersion (head tracking, field of regard, and stereoscopic rendering) on the effectiveness of visualization tasks with two x-ray microscopic computed tomography datasets. We report significant benefits of analyzing volume data in an environment involving those components of immersion. We find that the benefits do not necessarily require all three components simultaneously, and that the components have variable influence on different task categories. The results of our study improve our understanding of the effects of immersion on perceived and actual task performance, and provide guidance on the choice of display systems to designers seeking to maximize the effectiveness of volume visualization applications.