The 3D Interaction Group would like to acknowledge its member’s contributions to IEEE VR 2025.
Investigating the Influence of Playback Interactivity during Guided Tours for Asynchronous Collaboration in Virtual Reality
Alexander Giovannelli, Leonardo Pavanatto, Shakiba Davari, Haichao Miao, Vuthea Chheang, Brian Giera, Peer-Timo Bremer, Doug Bowman
Abstract: 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.
Spatial Bar: Exploring Window Switching Techniques for Large Virtual Displays
Leonardo Pavanatto, Jens Grubert, Doug Bowman
Abstract: Virtual displays provided through head-worn displays (HWDs) offer users large screen space for productivity, but managing this space effectively presents challenges. 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. Results show gaze coupled with teleport led to the quickest window-switching times, particularly in tasks where the original cursor position or the target window was far from the Spatial Bar.
Exploring Multiscale Navigation of Homogeneous and Dense Objects with Progressive Refinement in Virtual Reality
Leonardo Pavanatto, Alexander Giovannelli, Brian Giera, Peer-Timo Bremer, Haichao Miao, Doug Bowman
Abstract: 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.
Exploring the Effects of Level of Control in the Initialization of Shared Whiteboarding Sessions in Collaborative Augmented Reality
Logan Lane, Jerald Thomas, Alexander Giovannelli, Ibrahim Tahmid, Doug Bowman
Abstract: Augmented Reality (AR) collaboration can benefit from a shared 2D surface, such as a whiteboard. However, many features of each collaborators physical environment must be considered in order to determine the best placement and shape of the shared surface. We explored the effects of three methods for beginning a collaborative whiteboarding session with varying levels of user control: MANUAL, DISCRETE CHOICE, and AUTOMATIC by conducting a simulated AR study within Virtual Reality (VR). In the MANUAL method, users draw their own surfaces directly in the environment until they agree on the placement; in the DISCRETE CHOICE method, the system provides three options for whiteboard size and location; and in the AUTOMATIC method, the system automatically creates a whiteboard that fits within each collaborators environment. We evaluate these three conditions in a study in which two collaborators used each method to begin collaboration sessions. After establishing a session, the users worked together to complete an affinity diagramming task using the shared whiteboard. We found that the majority of participants preferred to have direct control during the initialization of a new collaboration session, despite the additional workload induced by the Manual method.
Planet Purifiers: A Collaborative Immersive Experience Proposing New Modifications to HOMER and Fishing Reel Interaction Techniques
Alexander Giovannelli, Fionn Murphy, Trey Davis, Chaerin Lee, Rehema Abulikemu, Matthew Gallagher, Sahil Sharma, Lee Lisle, Doug Bowman
Abstract: This paper presents our solution to the 2025 3DUI Contest challenge. We aimed to develop a collaborative, immersive experience that raises awareness about trash pollution in natural landscapes while enhancing traditional interaction techniques in virtual environments. To achieve these objectives, we created an engaging multiplayer game where one user collects harmful pollutants while the other user provides medication to impacted wildlife using enhancements to traditional interaction techniques: HOMER and Fishing Reel. We enhanced HOMER to use a cone volume to reduce the precise aiming required by a selection raycast to provide a more efficient means to collect pollutants at large distances, coined as FLOW-MATCH. To improve the animal feed distribution to wildlife far away from the user with Fishing Reel, we created RAWR-XD, an asymmetric bi-manual technique to more conveniently adjust the reeling speed using the non-selecting wrist rotation of the user.