Background: Virtual reality (VR) has been used successfully and effectively in psychotherapy for a variety of disorders. In the field of depression, there are only a few VR interventions and approaches. Although simple social interactions have been successfully modeled in VR for several mental disorders, there has been no transfer to the field of depression therapy. VR may be employed for psychodynamic psychotherapy to work on interpersonal conflict patterns. In this study, we developed and evaluated a VR intervention for the simulation of roleplay situations in the context of supportive-expressive therapy. Methods: We conducted a clinical user experience (UX) study at a psychotherapeutic clinic in Düsseldorf, Germany. Eight inpatients with depression and four therapists were included. Semi-structured interviews and qualitative content analysis were used to identify UX issues of the developed VR intervention. Usability questionnaires and technical usage data were also considered. The VR intervention consisted of two therapist-controlled roleplay scenarios designed to support work on the core conflictual relationship theme by allowing patients to interact in typical problematic social situations. Recorded VR roleplays allow for therapeutic debriefing with a change of perspective. Therapists were given the option of using the roleplay in multiple sessions. Results: All therapists conducted one session per patient with the VR intervention. From the patient interviews, 26 UX issues were extracted, of which one technical malfunction and two unclarities in the interaction with the VR agent were rated as major problems. From the therapist interviews, 14 UX issues were extracted, of which five were rated as major problems related to the interface in the dialog control or the complex system setup. Conclusion: The main problem was designing a dialog structure that allows both complex conversational flows and a clear control interface. In principle, VR roleplays could be integrated well and safely into therapy. The VR intervention shows promise for providing an emotional experience of interpersonal conflict patterns in the context of psychotherapy. Additionally, other roleplay situations involving various social problem areas must be created and evaluated in terms of the fit to the patients' core conflictual relationship themes.

Various factors influence the degree of cybersickness a user can suffer in an immersive virtual environment, some of which can be controlled without adapting the virtual environment itself. When using HMDs, one example is the size of the field of view. However, the degree to which factors like this can be manipulated without affecting the user negatively in other ways is limited. Another prominent characteristic of cybersickness is that it affects individuals very differently. Therefore, to account for both the possible disruptive nature of alleviating factors and the high interpersonal variance, a promising approach may be to intervene only in cases where users experience discomfort symptoms, and only as much as necessary. Thus, we conducted a first experiment, where the field of view was decreased when people feel uncomfortable, to evaluate the possible positive impact on sickness and negative influence on presence. While we found no significant evidence for any of these possible effects, interesting further results and observations were made.

In this paper we describe the xR4DRAMA system, a solution that makes use of XR capabilities to support professionals who deal with disasters, man-made crises or media productions. The key contribution of this work in progress is the increase of situation awareness, which is achieved by the innovative combination of data collection, multimedia and sensor analysis, linking data, GIS and interactive XR technologies. The proposed platform is designed to facilitate the creation of immersive environments using semantically enriched content and comprises a powerful tool that is applicable to multiple real use case scenarios.

Virtual reality applications potentially offer very life-like experiences in different contexts. Increasingly, they are also used in the medical field to optimize the utilization of resources as well as to support learning processes. In the field of psychotherapy, first anxiety treating systems are established. However, regarding depression and psychodynamic therapy, VR-based therapeutic models are yet rarely seen. This article introduces the interdisciplinary project DeepVR which aims to close this gap. The project's goal is to develop a VR system which is supposed to be used in addition to the presence therapeutical setting in the psychodynamic treatment of depression. In this paper, the theoretical core concepts and the three successfully developed modules are presented. The modules consist of a role play in which relationship conflicts are processed, a mindfulness routine, and a feedback module for the therapist to support success monitoring and early detection of relapse in patients. Finally, promising feedback of the user-centered development process is reported and further development as well as evaluation opportunities are discussed.

During free exploration of an unknown virtual scene, users often miss important parts, leading to incorrect or incomplete environment knowledge and a potential negative impact on performance in later tasks. This is addressed by wayfinding aids such as compasses, maps, or trails, and automated exploration schemes such as guided tours. However, these approaches either do not actually ensure exploration success or take away control from the user. Therefore, we present an interactive assistance interface to support exploration that guides users to interesting and unvisited parts of the scene upon request, supplementing their own, free exploration. It is based on an automated analysis of object visibility and viewpoint quality and is therefore applicable to a wide range of scenes without human supervision or manual input. In a user study, we found that the approach improves users' knowledge of the environment, leads to a more complete exploration of the scene, and is also subjectively helpful and easy to use.

Scene visibility—the information of which parts of the scene are visible from a certain location—can be used to derive various properties of a virtual environment. For example, it enables the computation of viewpoint quality to determine the informativeness of a viewpoint, helps in constructing virtual tours, and allows to keep track of the objects a user may already have seen. However, computing visibility at runtime may be too computationally expensive for many applications, while sampling the entire scene beforehand introduces a costly precomputation step and may include many samples not needed later on. Therefore, in this paper, we propose a novel approach to precompute visibility information based on navigation meshes, a polygonal representation of a scene's navigable areas. We show that with only limited precomputation, high accuracy can be achieved in these areas. Furthermore, we demonstrate the usefulness of the approach by means of several applications, including viewpoint quality computation, landmark and room detection, and exploration assistance. In addition, we present a travel interface based on common visibility that we found to result in less cybersickness in a user study.

Viewpoint quality estimation methods allow the determination of the most informative position in a scene. However, a single position usually cannot represent an entire scene, requiring instead a set of several viewpoints. Measuring the quality of such a set of views, however, is not trivial, and the computation of an optimal set of views is an NP-hard problem. Therefore, in this work, we propose three methods to estimate the quality of a set of views. Furthermore, we evaluate three approaches for computing an approximation to the optimal set (two of them new) regarding effectiveness and efficiency.

The manual adjustment of travel speed to cover medium or large distances in virtual environments may increase cognitive load, and manual travel at high speeds can lead to cybersickness due to inaccurate steering. In this work, we present an approach to quickly pass regions where the environment does not change much, using automated suggestions based on the computation of common visibility. In a user study, we show that our method can reduce cybersickness when compared with manual speed control.

We present an approach for tracking space-filling features based on a two-step algorithm utilizing two graph optimization techniques. First, one-to-one assignments between successive time steps are found by a matching on a weighted, bi-partite graph. Second, events are detected by computing an independent set on potential event explanations. The main objective of this work is investigating options for formal evaluation of complex feature tracking algorithms in the absence of ground truth data.

Computer-controlled, human-like virtual agents (VAs), are often embedded into immersive virtual environments (IVEs) in order to enliven a scene or to assist users. Certain constraints need to be fulfilled, e.g., a collision avoidance strategy allowing users to maintain their personal space. Violating this flexible protective zone causes discomfort in real-world situations and in IVEs. However, no studies on collision avoidance for small-scale IVEs have been conducted yet. Our goal is to close this gap by presenting the results of a controlled user study in a CAVE. 27 participants were immersed in a small-scale office with the task of reaching the office door. Their way was blocked either by a male or female VA, representing their co-worker. The VA showed different behavioral patterns regarding gaze and locomotion. Our results indicate that participants preferred collaborative collision avoidance: they expect the VA to step aside in order to get more space to pass while being willing to adapt their own walking paths.

When moving through a tracked immersive virtual environment, it is sometimes useful to deviate from the normal one-to-one mapping of real to virtual motion. One option is the application of rotation gain, where the virtual rotation of a user around the vertical axis is amplified or reduced by a factor. Previous research in head-mounted display environments has shown that rotation gain can go unnoticed to a certain extent, which is exploited in redirected walking techniques. Furthermore, it can be used to increase the effective field of regard in projection systems. However, rotation gain has never been studied in CAVE systems, yet. In this work, we present an experiment with 87 participants examining the effects of rotation gain in a CAVE-like virtual environment. The results show no significant effects of rotation gain on simulator sickness, presence, or user performance in a cognitive task, but indicate that there is a negative influence on spatial knowledge especially for inexperienced users. In secondary results, we could confirm results of previous work and demonstrate that they also hold for CAVE environments, showing a negative correlation between simulator sickness and presence, cognitive performance and spatial knowledge, a positive correlation between presence and spatial knowledge, a mitigating influence of experience with 3D applications and previous CAVE exposure on simulator sickness, and a higher incidence of simulator sickness in women.

To use the full potential of immersive data analysis when wearing a head-mounted display, users have to be able to navigate through the spatial data. We collected, developed and evaluated 5 different hands-free navigation methods that are usable while seated in the analyst's usual workplace. All methods meet the requirements of being easy to learn and inexpensive to integrate into existing workplaces. We conducted a user study with 23 participants which showed that a body leaning metaphor and an accelerometer pedal metaphor performed best. In the given task the participants had to determine the shortest path between various pairs of vertices in a large 3D graph.

Orientation and wayfinding in architectural Immersive Virtual Environments (IVEs) are non-trivial, accompanying tasks which generally support the users' main task. World in Miniatures (WIMs) - essentially 3D maps containing a scene replica - are an established approach to gain survey knowledge about the virtual world, as well as information about the user's relation to it. However, for large-scale, information-rich scenes, scaling and occlusion issues result in diminishing returns. Since there typically is a lack of standardized information regarding scene decompositions, presenting the inside of self-contained scene extracts is challenging. Therefore, we present an automatic WIM generation workflow for arbitrary, realistic in- and outdoor IVEs in order to support users with meaningfully selected and scaled extracts of the IVE as well as corresponding context information. Additionally, a 3D user interface is provided to manually manipulate the represented extract.

When traveling virtually through large scenes, long distances and different detail densities render fixed movement speeds impractical. However, to manually adjust the travel speed, users have to control an additional parameter, which may be uncomfortable and requires cognitive effort. Although automatic speed adjustment techniques exist, many of them can be problematic in indoor scenes. Therefore, we propose to automatically adjust travel speed based on viewpoint quality, originally a measure of the informativeness of a viewpoint. In a user study, we show that our technique is easy to use, allowing users to reach targets faster and use less cognitive resources than when choosing their speed manually.

We present a novel approach for tracking space-filling features, i.e., a set of features covering the entire domain. The assignment between successive time steps is determined by a two-step, global optimization scheme. First, a maximum-weight, maximal matching on a bi-partite graph is computed to provide one-to-one assignments between features of successive time steps. Second, events are detected in a subsequent step; here the matching step serves to restrict the exponentially large set of potential solutions. To this end, we compute an independent set on a graph representing conflicting event explanations. The method is evaluated by tracking dissipation elements, a structure definition from turbulent flow analysis.

In this work, we report on a pilot study we conducted, and on a study design, to examine the effects and applicability of rotation gain in CAVE-like virtual environments. The results of the study will give recommendations for the maximum levels of rotation gain that are reasonable in algorithms for enlarging the virtual field of regard or redirected walking.

In contrast to the wide-spread use of 6-DOF pointing devices, free-hand user interfaces in Immersive Virtual Environments (IVE) are non-intrusive. However, for gesture interfaces, the definition of trigger signals is challenging. The use of mechanical devices, dedicated trigger gestures, or speech recognition are often used options, but each comes with its own drawbacks. In this paper, we present an alternative approach, which allows to precisely trigger events with a low latency using microphone input. In contrast to speech recognition, the user only blows into the microphone. The audio signature of such blow events can be recognized quickly and precisely. The results of an user study show that the proposed method allows to successfully complete a standard selection task and performs better than expected against a standard interaction device, the Flystick.

In this work, we present an approach for tracking the feet of multiple users in CAVE-like systems with under-floor projection. It is based on low-cost consumer cameras, does not require users to wear additional equipment, and can be installed without modifying existing components. If the brightness of the floor projection does not contain too much variation, the feet of several people can be reliably tracked and assigned to individuals.