Navigation is a major challenge in exploring data within immersive environments, especially of large omnidirectional spherical images. We propose a method of auto-scaling to allow users to navigate using teleportation within the safe boundary of their physical environment with different levels of focus. Our method combines physical navigation with virtual teleportation. We also propose a “peek then warp” behavior when using a zoom lens and evaluate our system in conjunction with different teleportation transitions, including a proposed transition for exploration of omnidirectional and 360-degree panoramic imagery, termed Envelop, wherein the destination view expands out from the zoom lens to completely envelop the user. In this work, we focus on visualizing and navigating large omnidirectional or panoramic images with application to GIS visualization as an inside-out omnidirectional image of the earth. We conducted two user studies to evaluate our techniques over a search and comparison task. Our results illustrate the advantages of our techniques for navigation and exploration of omnidirectional images in an immersive environment.

Virtual colonoscopy (VC) is a non-invasive screening tool for colorectal polyps which employs volume visualization of a colon model reconstructed from a CT scan of the patient's abdomen. We present an immersive analytics system for VC which enhances and improves the traditional desktop VC through the use of VR technologies. Our system, using a head-mounted display (HMD), includes all of the standard VC features, such as the volume rendered endoluminal fly-through, measurement tool, bookmark modes, electronic biopsy, and slice views. The use of VR immersion, stereo, and wider field of view and field of regard has a positive effect on polyp search and analysis tasks in our immersive VC system, a volumetric-based immersive analytics application. Navigation includes enhanced automatic speed and direction controls, based on the user's head orientation, in conjunction with physical navigation for exploration of local proximity. In order to accommodate the resolution and frame rate requirements for HMDs, new rendering techniques have been developed, including mesh-assisted volume raycasting and a novel lighting paradigm. Feedback and further suggestions from expert radiologists show the promise of our system for immersive analysis for VC and encourage new avenues for exploring the use of VR in visualization systems for medical diagnosis.

For many virtual reality applications, a pre-calculated fly-through path is the de facto standard navigation method. Such a path is convenient for users and ensures coverage of critical areas throughout the scene. Traditional applications use constant camera speed, allow for fully user-controlled manual speed adjustment, or use automatic speed adjustment based on heuristics from the scene. We introduce two novel methods for constrained path navigation and exploration in virtual environments which rely on the natural orientation of the user's head during scene exploration. Utilizing head tracking to obtain the user's area of focus, we perform automatic camera speed adjustment to allow for natural off-axis scene examination. We expand this to include automatic camera navigation along the pre-computed path, abrogating the need for any navigational inputs from the user. Our techniques are applicable for any scene with a pre-computed navigation path, including medical applications such as virtual colonoscopy, coronary fly-through, or virtual angioscopy, and graph navigation. We compare the traditional methods (constant speed and manual speed adjustment) and our two methods (automatic speed adjustment and automatic speed/direction control) to determine the effect of speed adjustment on system usability, mental load, performance, and user accuracy. Through this evaluation we observe the effect of automatic speed adjustment compared to traditional methods. We observed no negative impact from automatic navigation, and the users performed as well as with the manual navigation.

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.