Bireswar Laha

Effects of Immersion on Visual Analysis of Volume Data

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.

Immersive Collaborative Analysis of Network Connectivity: CAVE-style or Head-Mounted Display?

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.

Effects of VR System Fidelity on Analyzing Isosurface Visualization of Volume Datasets

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.

Poster: Designing effective travel techniques with bare-hand interaction

Emerging novel 3D interaction technologies allow precise tracking of bare hands and fingers, but due to the differences between these devices and traditional trackers, it is not clear how to design effective interaction techniques using these technologies. Using the Leap Motion Controller, we designed travel techniques with bare-hand interaction. We prototyped both unimanual and bimanual techniques using various metaphors (e.g., airplane and camera-in-hand), control mappings (position- vs. rate-control), camera movements (scene vs. camera dependent) and methods for speed control. Based on our experiences with these prototypes, we discuss the challenges and design issues for bare-hand interaction techniques. We present the results of a user study comparing the usability of five representative techniques for three travel tasks: absolute travel, naïve search and path following. We found that the limited workspace of the Leap caused movements with the camera-in-hand metaphor to be faster and less accurate, making it more effective for search but less effective for path following tasks. In addition, the Leaps ability to precisely track small finger movements benefited the usability of continuous speed control techniques.

Validation of the MR Simulation Approach for Evaluating the Effects of Immersion on Visual Analysis of Volume Data

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.

Regenerating optic pathways from the eye to the brain

Humans are highly visual. Retinal ganglion cells (RGCs), the neurons that connect the eyes to the brain, fail to regenerate after damage, eventually leading to blindness. Here, we review research on regeneration and repair of the optic system. Intrinsic developmental growth programs can be reactivated in RGCs, neural activity can enhance RGC regeneration, and functional reformation of eye-to-brain connections is possible, even in the adult brain. Transplantation and gene therapy may serve to replace or resurrect dead or injured retinal neurons. Retinal prosthetics that can restore vision in animal models may too have practical power in the clinical setting. Functional restoration of sight in certain forms of blindness is likely to occur in human patients in the near future.

Volume cracker: a bimanual 3D interaction technique for analysis of raw volumetric data

Analysis of volume datasets often involves peering inside the volume to understand internal structures. Traditional approaches involve removing part of the volume through slicing, but this can result in the loss of context. Focus+context visualization techniques can distort part of the volume, or can assume prior definition of a region of interest or segmentation of layers of the volume. We propose a new bimanual 3D interaction technique, called Volume Cracker (VC), which allows the user to crack open a raw volume like a book to analyze the internal structures. VC preserves context by always displaying all the voxels, and by connecting the sub-volumes with curves joining the cracked faces. We discuss the design choices that we made, based on observations from prior user studies, input from domain scientists, and design studios. We also report the results of a user study comparing VC with a standard desktop interaction technique and a standard 3D bimanual interaction technique. The study used tasks from two categories of a generic volume analysis task taxonomy. We found VC had significant advantages over the other two techniques for search and pattern recognition tasks.

The effects of navigational control and environmental detail on learning in 3D virtual environments

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.

Immersion at scale: Researcher's guide to ecologically valid mobile experiments

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.

A classification of user tasks in visual analysis of volume data

Empirical findings from studies in one scientific domain have very limited applicability to other domains, unless we formally establish deeper insights on the generalizability of task types. We present a domain-independent classification of visual analysis tasks with volume visualizations. This taxonomy will help researchers design experiments, ensure coverage, and generate hypotheses in empirical studies with volume datasets. To develop our taxonomy, we first interviewed scientists working with spatial data in disparate domains. We then ran a survey to evaluate the design participants in which were scientists and professionals from around the world, working with volume data in various scientific domains. Respondents agreed substantially with our taxonomy design, but also suggested important refinements. We report the results in the form of a goal-based generic categorization of visual analysis tasks with volume visualizations. Our taxonomy covers tasks performed with a wide variety of volume datasets.