Publications

Effective navigation and interaction within immersive virtual environments rely on thorough scene exploration. Therefore, wayfinding is essential, assisting users in comprehending their surroundings, planning routes, and making informed decisions. Based on real-life observations, wayfinding is, thereby, not only a cognitive process but also a social activity profoundly influenced by the presence and behaviors of others. In virtual environments, these 'others' are virtual agents (VAs), defined as anthropomorphic computer-controlled characters, who enliven the environment and can serve as background characters or direct interaction partners. However, little research has been done to explore how to efficiently use VAs as social wayfinding support. In this paper, we aim to assess and contrast user experience, user comfort, and the acquisition of scene knowledge through a between-subjects study involving n = 60 participants across three distinct wayfinding conditions in one slightly populated urban environment: (i) unsupported wayfinding, (ii) strong social wayfinding using a virtual supporter who incorporates guiding and accompanying elements while directly impacting the participants' wayfinding decisions, and (iii) weak social wayfinding using flows of VAs that subtly influence the participants' wayfinding decisions by their locomotion behavior. Our work is the first to compare the impact of VAs' behavior in virtual reality on users' scene exploration, including spatial awareness, scene comprehension, and comfort. The results show the general utility of social wayfinding support, while underscoring the superiority of the strong type. Nevertheless, further exploration of weak social wayfinding as a promising technique is needed. Thus, our work contributes to the enhancement of VAs as advanced user interfaces, increasing user acceptance and usability.

Immersive authoring enables content creation for virtual environments without a break of immersion. To enable immersive authoring of reactive behavior for a broad audience, we present modulation mapping, a simplified visual programming technique. To evaluate the applicability of our technique, we investigate the role of reference frames in which the programming elements are positioned, as this can affect the user experience. Thus, we developed two interface layouts: "surround-referenced" and "object-referenced". The former positions the programming elements relative to the physical tracking space, and the latter relative to the virtual scene objects. We compared the layouts in an empirical user study (n = 34) and found the surround-referenced layout faster, lower in task load, less cluttered, easier to learn and use, and preferred by users. Qualitative feedback, however, revealed the object-referenced layout as more intuitive, engaging, and valuable for visual debugging. Based on the results, we propose initial design implications for immersive authoring of reactive behavior by visual programming. Overall, modulation mapping was found to be an effective means for creating reactive behavior by the participants.

Honorable Mention for Best Paper!

In-situ, in-transit, and hybrid approaches have become well-established visualization methods over the last decades. Especially for large simulations, these paradigms enable visualization and additionally allow for early insights. While there has been a lot of research on combining these approaches with classical visualization software, only a few worked on combining in-situ/in-transit approaches with modern game engines. In this paper, we present and demonstrate InsitUE, a Catalyst2 compatible hybrid workflow that enables interactive real-time visualization of simulation results using Unreal Engine.

Visualization, from simple line plots to complex high-dimensional visual analysis systems, has established itself throughout numerous domains to explore, analyze, and evaluate data. Applying such visualizations in the context of simulation science where High-Performance Computing (HPC) produces ever-growing amounts of data that is more complex, potentially multidimensional, and multimodal, takes up resources and a high level of technological experience often not available to domain experts. In this work, we present DaVE -- a curated database of visualization examples, which aims to provide state-of-the-art and advanced visualization methods that arise in the context of HPC applications. Based on domain- or data-specific descriptors entered by the user, DaVE provides a list of appropriate visualization techniques, each accompanied by descriptions, examples, references, and resources. Sample code, adaptable container templates, and recipes for easy integration in HPC applications can be downloaded for easy access to high-fidelity visualizations. While the database is currently filled with a limited number of entries based on a broad evaluation of needs and challenges of current HPC users, DaVE is designed to be easily extended by experts from both the visualization and HPC communities.

Ensembles of simulations are generated to capture uncertainties in the simulation model and its initialization. When simulating 3D spatial phenomena, the value distributions may vary from region to region. Therefore, visualization methods need to adapt to different types and shapes of statistical distributions across regions. In the case of normal distribution, a region is well represented and visualized by the means and standard deviations. In the case of multi-modal distributions, the ensemble can be subdivided to investigate whether sub-ensembles exhibit uni-modal distributions in that region. We, therefore, propose an interactive visual analysis approach for region-based visualization within a hierarchy of sub-ensembles. The hierarchy of sub-ensembles is created using hierarchical clustering, while regions can be defined using parallel coordinates of statistical properties. The identified regions are rendered in a hierarchy of interactive volume renderers. We apply our approach to two real-world simulation ensembles to show its usability.

second-order tensors are fundamental in various scientific and engineering domains, as they can represent properties such as material stresses or diffusion processes in brain tissue. In recent years, several approaches have been introduced and improved to analyze these fields using topological features, such as degenerate tensor locations, i.e., the tensor has repeated eigenvalues, or normal surfaces. Traditionally, the identification of such features has been limited to single tensor fields. However, it has become common to create ensembles to account for uncertainties and variability in simulations and measurements. In this work, we explore novel methods for describing and visualizing degenerate tensor locations in 3D symmetric second-order tensor field ensembles. We base our considerations on the tensor mode and analyze its practicality in characterizing the uncertainty of degenerate tensor locations before proposing a variety of visualization strategies to effectively communicate degenerate tensor information. We demonstrate our techniques for synthetic and simulation data sets. The results indicate that the interplay of different descriptions for uncertainty can effectively convey information on degenerate tensor locations.

We present a data acquisition and visualization pipeline that allows experts to monitor additive manufacturing processes, in particular laser metal deposition with wire (LMD-w) processes, in immersive virtual reality. Our virtual environment consists of a digital shadow of the LMD-w production site enriched with additional measurement data shown on both static as well as handheld virtual displays. Users can explore the production site by enhanced teleportation capabilities that enable them to change their scale as well as their elevation above the ground plane. In an exploratory user study with 22 participants, we demonstrate that our system is generally suitable for the supervision of LMD-w processes while generating low task load and cybersickness. Therefore, it serves as a first promising step towards the successful application of virtual reality technology in the comparatively young field of additive manufacturing.

Immersive knowledge spaces like museums or cultural sites are often explored by traversing pre-defined paths that are curated to unfold a specific educational narrative. To support this type of guided exploration in VR, we present a semi-automated, handsfree path traversal technique based on teleportation that features a slow-paced interaction workflow targeted at fostering knowledge acquisition and maintaining spatial awareness. In an empirical user study with 34 participants, we evaluated two variations of our technique, differing in the presence or absence of intermediate teleportation points between the main points of interest along the route. While visiting additional intermediate points was objectively less efficient, our results indicate significant benefits of this approach regarding the user’s spatial awareness and perception of interface dependability. However, the user’s perception of flow, presence, attractiveness, perspicuity, and stimulation did not differ significantly. The overall positive reception of our approach encourages further research into semi-automated locomotion based on teleportation and provides initial insights into the design space of successful techniques in this domain.

Many lecturers develop voice problems, such as hoarseness. Nevertheless, research on how voice quality influences listeners’ perception, comprehension, and retention of spoken language is limited to a small number of audio-only experiments. We aimed to address this gap by using audio-visual virtual reality (VR) to investigate the impact of a lecturer’s hoarseness on university students’ heard text recall, listening effort, and listening impression. Fifty participants were immersed in a virtual seminar room, where they engaged in a Dual-Task Paradigm. They listened to narratives presented by a virtual female professor, who spoke in either a typical or hoarse voice. Simultaneously, participants performed a secondary task. Results revealed significantly prolonged secondary-task response times with the hoarse voice compared to the typical voice, indicating increased listening effort. Subjectively, participants rated the hoarse voice as more annoying, effortful to listen to, and impeding for their cognitive performance. No effect of voice quality was found on heard text recall, suggesting that, while hoarseness may compromise certain aspects of spoken language processing, this might not necessarily result in reduced information retention. In summary, our findings underscore the importance of promoting vocal health among lecturers, which may contribute to enhanced listening conditions in learning spaces.

Object selection in virtual environments is one of the most common and recurring interaction tasks. Therefore, the used technique can critically influence a system’s overall efficiency and usability. IntenSelect is a scoring-based selection-by-volume technique that was shown to offer improved selection performance over conventional raycasting in virtual reality. This initial method, however, is most pronounced for small spherical objects that converge to a point-like appearance only, is challenging to parameterize, and has inherent limitations in terms of flexibility. We present an enhanced version of IntenSelect called IntenSelect+ designed to overcome multiple shortcomings of the original IntenSelect approach. In an empirical within-subjects user study with 42 participants, we compared IntenSelect+ to IntenSelect and conventional raycasting on various complex object configurations motivated by prior work. In addition to replicating the previously shown benefits of IntenSelect over raycasting, our results demonstrate significant advantages of IntenSelect+ over IntenSelect regarding selection performance, task load, and user experience. We, therefore, conclude that IntenSelect+ is a promising enhancement of the original approach that enables faster, more precise, and more comfortable object selection in immersive virtual environments.

Authentication poses a significant challenge in VR applications, as conventional methods, such as text input for usernames and passwords, prove cumbersome and unnatural in immersive virtual environments. Alternatives such as password managers or two-factor authentication may necessitate users to disengage from the virtual experience by removing their headsets. Consequently, we present an innovative system that utilizes virtual agents (VAs) as interaction partners, enabling users to authenticate naturally through a set of ten gestures, such as high fives, fist bumps, or waving. By combining these gestures, users can create personalized authentications akin to PINs, potentially enhancing security without compromising the immersive experience. To gain first insights into the suitability of this authentication process, we conducted a formal expert review with five participants and compared our system to a virtual keypad authentication approach. While our results show that the effectiveness of a VA-mediated gesture-based authentication system is still limited, they motivate further research in this area.

Virtual Reality has become an important medium in the automotive industry, providing engineers with a simulated platform to actively engage with and evaluate realistic driving scenarios for testing and validating automated vehicles. However, engineers are often restricted to using 2D desktop-based tools for designing driving scenarios, which can result in inefficiencies in the development and testing cycles. To this end, we present VRScenarioBuilder, an immersive authoring tool that enables engineers to create and modify dynamic driving scenarios directly in VR using free-hand interactions. Our tool features a natural user interface that enables users to create scenarios by using drag-and-drop building blocks. To evaluate the interface components and interactions, we conducted a user study with VR experts. Our findings highlight the effectiveness and potential improvements of our tool. We have further identified future research directions, such as exploring the spatial arrangement of the interface components and managing lengthy blocks.

One core aspect of immersive visualization labs is to develop and provide powerful tools and applications that allow for efficient analysis and exploration of scientific data. As the requirements for such applications are often diverse and complex, the same applies to the development process. This has led to a myriad of different tools, frameworks, and approaches that grew and developed over time. The steady advance of commercial off-the-shelf game engines such as Unreal Engine has made them a valuable option for development in immersive visualization labs. In this work, we share our experience of migrating to Unreal Engine as a primary developing environment for immersive visualization applications. We share our considerations on requirements, present use cases developed in our lab to communicate advantages and challenges experienced, discuss implications on our research and development environments, and aim to provide guidance for others within our community facing similar challenges.

As virtual reality overlays the user’s view, challenges arise when interaction with their physical surroundings is still needed. In a seated workspace environment interaction with the physical surroundings can be essential to enable productive working. Interaction with e.g. physical mouse and keyboard can be difficult when no visual reference is given to where they are placed. This demo shows a combination of computer vision-based marker detection with machine-learning-based hand detection to bring users’ hands and arbitrary objects into VR.

Collaborative work in social virtual reality often requires an interplay of loosely coupled collaboration from different virtual locations and tightly coupled face-to-face collaboration. Without appropriate system mediation, however, transitioning between these phases requires high navigation and coordination efforts. In this paper, we present an interaction system that allows collaborators in virtual reality to seamlessly switch between different collaboration models known from related work. To this end, we present collaborators with functionalities that let them work on individual sub-tasks in different virtual locations, consult each other using asymmetric interaction patterns while keeping their current location, and temporarily or permanently join each other for face-to-face interaction. We evaluated our methods in a user study with 32 participants working in teams of two. Our quantitative results indicate that delegating the target selection process for a long-distance teleport significantly improves placement accuracy and decreases task load within the team. Our qualitative user feedback shows that our system can be applied to support flexible collaboration. In addition, the proposed interaction sequence received positive evaluations from teams with varying VR experiences.

Virtual travel in Virtual Reality experiences is common, offering users the ability to explore expansive virtual spaces. Various interfaces exist for virtual travel, with speed playing a crucial role in user experience and spatial awareness. Teleportation-based interfaces provide instantaneous transitions, whereas continuous and semi-continuous methods vary in speed and control. Prior research by Bowman et al. highlighted the impact of travel speed on spatial awareness demonstrating that instantaneous travel can lead to user disorientation. However, additional cues, such as visual target selection, can aid in reorientation. This study replicates and extends Bowman’s experiment, investigating the influence of travel speed and visual target cues on spatial orientation.

Several group navigation techniques enable a single navigator to control travel for all group members simultaneously in social virtual reality. A key aspect of this process is the ability to rearrange the group into a new formation to facilitate the joint observation of the scene or to avoid obstacles on the way. However, the question of how users should be distributed within the new formation to create an intuitive transition that minimizes disruptions of ongoing social activities is currently not explored. In this paper, we begin to close this gap by introducing four user placement strategies based on mathematical considerations, discussing their benefits and drawbacks, and sketching further novel ideas to approach this topic from different angles in future work. Our work, therefore, contributes to the overarching goal of making group interactions in social virtual reality more intuitive and comfortable for the involved users.

The ability of a user to adjust their own scale while traveling through virtual environments enables them to inspect tiny features being ant-sized and to gain an overview of the surroundings as a giant. While prior work has almost exclusively focused on steering-based interfaces for multi-scale travel, we present three novel teleportation-based techniques that avoid continuous motion flow to reduce the risk of cybersickness. Our approaches build on the extension of known teleportation workflows and suggest specifying scale adjustments either simultaneously with, as a connected second step after, or separately from the user’s new horizontal position. The results of a two-part user study with 30 participants indicate that the simultaneous and connected specification paradigms are both suitable candidates for effective and comfortable multi-scale teleportation with nuanced individual benefits. Scale specification as a separate mode, on the other hand, was considered less beneficial. We compare our findings to prior research and publish the executable of our user study to facilitate replication and further analyses.

Setting up and conducting user studies is fundamental to virtual reality research. Yet, often these studies are developed from scratch, which is time-consuming and especially hard and error-prone for novice developers. In this paper, we introduce the StudyFramework, a framework specifically designed to streamline the setup and execution of factorial-design VR-based user studies within the Unreal Engine, significantly enhancing the overall process. We elucidate core concepts such as setup, randomization, the experimenter view, and logging. After utilizing our framework to set up and conduct their respective studies, 11 study developers provided valuable feedback through a structured questionnaire. This feedback, which was generally positive, highlighting its simplicity and usability, is discussed in detail.

Exploring the synergy between visual and acoustic cues in virtual reality (VR) is crucial for elevating user engagement and perceived (social) presence. We present a study exploring the necessity and design impact of background sound source visualizations to guide the design of future soundscapes. To this end, we immersed n = 27 participants using a head-mounted display (HMD) within a virtual seminar room with six virtual peers and a virtual female professor. Participants engaged in a dual-task paradigm involving simultaneously listening to the professor and performing a secondary vibrotactile task, followed by recalling the heard speech content. We compared three types of background sound source visualizations in a within-subject design: no visualization, static visualization, and animated visualization. Participants’ subjective ratings indicate the importance of animated background sound source visualization for an optimal coherent audiovisual representation, particularly when embedding peer-emitted sounds. However, despite this subjective preference, audiovisual coherence did not affect participants’ performance in the dual-task paradigm measuring their listening effort.

Enabling the widespread utilization of the Artificial-Social-Agent (ASA)Questionnaire, a research instrument to comprehensively assess diverse ASA qualities while ensuring comparability, necessitates translations beyond the original English source language questionnaire. We thus present Dutch and German translations of the long and short versions of the ASA Questionnaire and describe the translation challenges we encountered. Summative assessments with 240 English-Dutch and 240 English-German bilingual participants show, on average, excellent correlations (Dutch ICC M = 0.82,SD = 0.07, range [0.58, 0.93]; German ICC M = 0.81, SD = 0.09, range [0.58,0.94]) with the original long version on the construct and dimension level. Results for the short version show, on average, good correlations (Dutch ICC M = 0.65, SD = 0.12, range [0.39, 0.82]; German ICC M = 0.67, SD = 0.14, range [0.30,0.91]). We hope these validated translations allow the Dutch and German-speaking populations to evaluate ASAs in their own language.

VR-CrowdCraft is a newly formed interdisciplinary initiative, dedicated to the convergence and advancement of two distinct yet interconnected research fields: pedestrian dynamics (PD) and social virtual reality (VR). The initiative aims to establish foundational workflows for a systematic integration of PD data obtained from real-life experiments, encompassing scenarios ranging from smaller clusters of approximately ten individuals to larger groups comprising several hundred pedestrians, into immersive virtual environments (IVEs), addressing the following two crucial goals: (1) Advancing pedestrian dynamic analysis and (2) Advancing virtual pedestrian behavior: authentic populated IVEs and new PD experiments. The LBR presentation will focus on goal 1.