Prior research has developed a number of manipulation techniques that can achieve precise object placement in virtual reality, but studies of these techniques typically use simple objects. We conducted a study comparing two existing techniques, (AMP-IT and WISDOM), during alignment of objects with complex geometry to evaluate the potential influence of geometric complexity on performance, usability, workload and preference. Our findings indicate that participants had faster completion times and higher trial completion rates with AMP-IT on high-precision alignment tasks, contrary to earlier findings that used simple objects. Yet WISDOM is still preferred and considered more usable, despite increased workload and poorer performance, exposing participants' willingness to trade objective performance for comfort during use.

Collaborative virtual environments allow workers to contribute to team projects across space and time. While much research has closely examined the problem of working in different spaces at the same time, few have investigated the best practices for collaborating in those spaces at different times aside from textual and auditory annotations. We designed a system that allows experts to record a tour inside a virtual inspection space, preserving knowledge and providing later observers with insights through a 3D playback of the expert’s inspection. We also created several interactions to ensure that observers are tracking the tour and remaining engaged. We conducted a user study to evaluate the influence of these interactions on an observing user’s information recall and user experience. Findings indicate that independent viewpoint control during a tour enhances the user experience compared to fully passive playback and that additional interactivity can improve auditory and spatial recall of key information conveyed during the tour.

Virtual displays provided through head-worn displays (HWDs) offer users large screen space for productivity, but managing this space effectively presents challenges. Existing research shows that while increased screen space improves performance, it can also introduce significant window management overhead. This paper explores how to enhance window-switching strategies for virtual displays by leveraging eye tracking provided by HWDs and underutilized spaces around the main display area. We investigate the efficiency and usability of different cursor behaviors and selection modes in a Spatial Bar interface for window-switching tasks in augmented reality environments. Our study involved two primary selection modes: Gaze and Cursor, each tested with two cursor behaviors: Teleport and Stay. We measured objective performance metrics, including task completion time and error rates, and subjective evaluations using the NASA TLX and custom questionnaires. Results show that Cursor Stay, while familiar and comfortable for participants, was laborious and led to longer task completion times, particularly over large distances. Gaze Teleport led to the quickest window switching times, particularly in tasks where the original cursor position or the target window were far from the Spatial Bar.

Locating small features in a large, dense object in virtual reality (VR) poses a significant interaction challenge. While existing multiscale techniques support transitions between various levels of scale, they are not focused on handling dense, homogeneous objects with hidden features. We propose a novel approach that applies the concept of progressive refinement to VR navigation, enabling focused inspections. We conducted a user study where we varied two independent variables in our design, navigation style (STRUCTURED vs. UNSTRUCTURED) and display mode (SELECTION vs. EVERYTHING), to better understand their effects on efficiency and awareness during multiscale navigation. Our results showed that unstructured navigation can be faster than structured and that displaying only the selection can be faster than displaying the entire object. However, using an everything display mode can support better location awareness and object understanding.

Future augmented reality (AR) glasses empower users to view personal applications and services anytime and anywhere without being restricted by physical locations and the availability of physical screens. In typical everyday activities, people move around to carry out different tasks and need a variety of information on the go. Existing interfaces in AR do not support these use cases well, especially when the number of applications increases. We explore the usability of three world-referenced approaches that move AR applications with users as they transition among different locations, featuring different levels of AR app availability: (1) always using a menu to manually open an app when needed; (2) automatically suggesting a relevant subset of all apps; and (3) carrying all apps with the users to the new location. Through a controlled study and a relatively more ecologically-valid study in AR, we reached better understandings on the performance trade-offs and observed the impact of various everyday contextual factors on these interfaces in more realistic AR settings. Our results shed light on how to better support the mobile information needs of users in everyday life in future AR interfaces.

Although access to sufficient screen space is crucial to knowledge work, workers often find themselves with limited access to display infrastructure in remote or public settings. While virtual displays can be used to extend the available screen space through extended reality (XR) head-worn displays (HWD), we must better understand the implications of working with them in public settings from both users' and bystanders' viewpoints. To this end, we conducted two user studies. We first explored the usage of a hybrid AR display across real-world settings and tasks. We focused on how users take advantage of virtual displays and what social and environmental factors impact their usage of the system. A second study investigated the differences between working with a laptop, an AR system, or a VR system in public. We focused on a single location and participants performed a predefined task to enable direct comparisons between the conditions while also gathering data from bystanders. The combined results suggest a positive acceptance of XR technology in public settings and show that virtual displays can be used to accompany existing devices. We highlighted some environmental and social factors. We saw that previous XR experience and personality can influence how people perceive the use of XR in public. In addition, we confirmed that using XR in public still makes users stand out and that bystanders are curious about the devices, yet have no clear understanding of how they can be used.

Virtual displays enabled through head-worn augmented reality have unique characteristics that can yield extensive amounts of screen space. Existing research has shown that increasing the space on a computer screen can enhance usability. Since virtual displays offer the unique ability to present content without rigid physical space constraints, they provide various new design possibilities. Therefore, we must understand the trade-offs of layout choices when structuring that space. We propose a single Canvas approach that eliminates boundaries from traditional multi-monitor approaches and instead places windows in one large, unified space. Our user study compared this approach against a multi-monitor setup, and we considered both purely virtual systems and hybrid systems that included a physical monitor. We looked into usability factors such as performance, accuracy, and overall window management. Results show that Canvas displays can cause users to compact window layouts more than multiple monitors with snapping behavior, even though such optimizations may not lead to longer window management times. We did not find conclusive evidence of either setup providing a better user experience. Multi-Monitor displays offer quick window management with snapping and a structured layout through subdivisions. However, Canvas displays allow for more control in placement and size, lowering the amount of space used and, thus, head rotation. Multi-Monitor benefits were more prominent in the hybrid configuration, while the Canvas display was more beneficial in the purely virtual configuration.

Analysts need to process large amounts of data in order to extract concepts, themes, and plans of action based upon their findings. Different display technologies offer varying levels of space and interaction methods that change the way users can process data using them. In a comparative study, we investigated how the use of single traditional monitor, a large, high-resolution two-dimensional monitor, and immersive three-dimensional space using the Immersive Space to Think approach impact the sensemaking process. We found that user satisfaction grows and frustration decreases as available space increases. We observed specific strategies users employ in the various conditions to assist with the processing of datasets. We also found an increased usage of spatial memory as space increased, which increases performance in artifact position recall tasks. In future systems supporting sensemaking, we recommend using display technologies that provide users with large amounts of space to organize information and analysis artifacts.

Precise 3D manipulation in virtual reality (VR) is essential for effectively aligning virtual objects. However, state-of-the-art VR manipulation techniques have limitations when high levels of precision are required, including the unnaturalness caused by scaled rotations and the increase in time due to degree-of-freedom (DoF) separation in complex tasks. We designed two novel techniques to address these issues: AMP-IT, which offers direct manipulation with an adaptive scaled mapping for implicit DoF separation, and WISDOM, which offers a combination of Simple Virtual Hand and scaled indirect manipulation with explicit DoF separation. We compared these two techniques against baseline and state-of-the-art manipulation techniques in a controlled experiment. Results indicate that WISDOM and AMP-IT have significant advantages over best-practice techniques regarding task performance, usability, and user preference.

Physical monitors require space, lack flexibility, and can become expensive and less portable in large setups. Virtual monitors, on the other hand, can minimize those problems, but may be subject to technological limitations such as lower resolution and field of view. We investigate the impacts of using virtual monitors displayed on a current state-of-the-art augmented reality headset for conducting productivity work. We conducted a user study that compared physical monitors, virtual monitors, and a hybrid combination of both in terms of performance, accuracy, comfort, focus, preference, and confidence. Results show that virtual monitors are a feasible approach for performing serious productivity work, albeit currently constrained by technical limitations that lead to inferior usability and performance compared to physical monitors. We also discovered that, with current technology, the hybrid condition was a better tradeoff between the familiarity and trustworthiness of physical monitors and the extra space provided by virtual monitors. We conclude by expressing the opportunity for designing strategies for mixing virtual and physical monitors into novel hybrid interfaces.

Measuring involuntary eye movement under specific stimuli is an important way to identify diseases such as balance disorders. Exams based on video-oculography (VOG) equipment are able to detect horizontal and vertical displacements of the pupil. However, detecting torsional movements is still a challenge. Although conventional methods have good accuracy, their results can be influenced by artifacts, such as a torsion center displacement, interference by illumination, reflections, and changes in the pupil dilation. We propose a novel method which improves the robustness of this measurement by applying the Lucas-Kanade Pyrm (LKP) optical flow technique to the captured image, directly over the iris, rather than making a polar transformation. Retaining this additional information allows multiple features over the iris to be analyzed individually and as a group, providing correction of the torsion center displacements, filtering features with reflections and adapting to different pupil dilations before the torsion angle is calculated. The accuracy and performance of this method were evaluated by comparing it against a conventional method when detecting torsional movements on videos with a known ground truth. Moreover, a simplified version of the proposed method is also evaluated, in order to analyze the impacts of a torsion center displacement. Results show that the proposed method has higher accuracy and equivalent performance to the conventional method.

The analysis of Confocal Laser Endomicroscopy (CLE) is one of the techniques used for diagnosing gastroenterological diseases. However, the manual analysis of such images requires training and experience and will often lead to wrong diagnostics. This work explores the use of attributes taken from classic texture description techniques, gray level co-occurrence matrices (GLCM) and local binary patterns (LBP), as inputs for classifiers to separate images from 3 common gastroenterological diseases, with 262 images. A baseline classifier was trained for the 10 smaller groups and two others were trained using GLCM and LBP attributes. Overall, the benefits of using texture analysis techniques and attributes can be observed as an increase in accuracy and consistency of the results.