Sebastian Freitag, M. Sc.|
Phone: +49 241 80 24378
Fax: +49 241 80 22134
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.
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.
Honorable Mention for Best Technote!
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.
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.
To use the full potential of immersive data analysis when wearing a head-mounted display, the user has 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 within the given task.
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 largescale, 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.
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.
Honorable Mention Award!
The knowledge of which places in a virtual environment are interesting or informative can be used to improve user interfaces and to create virtual tours. Viewpoint Quality Estimation algorithms approximate this information by calculating quality scores for viewpoints. However, even though several such algorithms exist and have also been used, e.g., in virtual tour generation, they have never been comparatively evaluated on virtual scenes. In this work, we introduce three new Viewpoint Quality Estimation algorithms, and compare them against each other and six existing metrics, by applying them to two different virtual scenes. Furthermore, we conducted a user study to obtain a quantitative evaluation of viewpoint quality. The results reveal strengths and limitations of the metrics on actual scenes, and provide recommendations on which algorithms to use for real applications.
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 successfully and precisely tracked and assigned to individuals. The tracking data can be used to enable or enhance user interfaces like Walking-in-Place or torso-directed steering, provide audio feedback for footsteps, and improve the immersive experience for multiple users.
In contrast to the wide-spread use of 6-DOF pointing devices, freehand 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 a 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 mul- tiple 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.
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.
Real walking is the most natural method of navigation in virtual environments. However, physical space limitations often prevent or complicate its continuous use. Thus, many real walking interfaces, among them redirected walking techniques, depend on a reorientation technique that redirects the user away from physical boundaries when they are reached. However, existing reorientation techniques typically actively interrupt the user, or depend on the application of rotation gain that can lead to simulator sickness. In our approach, the user is reoriented using portals. While one portal is placed automatically to guide the user to a safe position, she controls the target selection and physically walks through the portal herself to perform the reorientation. In a formal user study we show that the method does not cause additional simulator sickness, and participants walk more than with point-and-fly navigation or teleportation, at the expense of longer completion times.
Simulations of geothermal reservoirs inherently contain uncertainty due to the fact that the underlying physical models are created from sparse data. Moreover, this uncertainty often cannot be completely expressed by simple key measures (e.g., mean and standard deviation), as the distribution of possible values is often not unimodal. Nevertheless, existing visualizations of these simulation data often completely neglect displaying the uncertainty, or are limited to a mean/variance representation. We present an approach to visualize geothermal simulation data that deals with both cases: scalar uncertainties as well as general ensembles of data sets. Users can interactively define two-dimensional transfer functions to visualize data and uncertainty values directly, or browse a 2D scatter plot representation to explore different possibilities in an ensemble.
The visual discrimination of different structures in one or multiple combined volume data sets is generally done with individual transfer functions that can usually be adapted interactively. Immersive virtual environments support the depth perception and thus the spatial orientation in these volume visualizations. However, complex 2D menus for elaborate transfer function design cannot be easily integrated. We therefore present an approach for changing the color mapping during volume exploration with direct volume interaction and an additional 3D widget. In this way we incorporate the modification of a color mapping for a large number of discretely labeled brain areas in an intuitive way into the virtual environment. We use our approach for the analysis of a patient’s data with a brain tissue degenerating disease to allow for an interactive analysis of affected regions.
When dealing with free convection in a geothermal reservoir, it is preferable to detect regions of up flow, which locally increase the geothermal gradient. Free convection cells are likely to be found in a large reservoir layer (Yarragadee Aquifer), which is encountered in the entire Perth Basin, including the Perth Metropolitan Area (PMA). While the knowledge about the structure of the Perth Basin has been improved recently, the heterogeneity and spatial complexity of permeability was up till now mainly neglected. We set up a refined structural model of about 5000 km² comprising the region around the city of Perth up to a depth of 4.5 km, using an implicit modelling approach (3D GeoModeller by Intrepid Geophysics ). Based on the structural model we create a discretized numerical model for simulating fluid flow and heat transport in the Yarragadee Aquifer considering spatial heterogeneity of porosity and permeability. This heterogeneity is assessed by designing three different test cases: 1) constant porosity and permeability for the entire aquifer; 2) porosity and permeability decreasing with depth; 3) a conditional random permeability field within prescribed limits and for given correlation length. We calibrate a poro-perm relationship based on a fractal approach to the Yarragadee Aquifer, using over 100 measurement pairs of porosity and permeability from three boreholes. This data was also used for calibrating porosity decrease with depth, following Athy’s law. For the model with constant porosity and permeability, convection cells vary in size between 4 km and 6 km. Simulations with depth dependent decrease in porosity and permeability yielded a transition from conductive to convective heat transport in the Yarragadee Aquifer at a threshold permeability of around 1.7 × 10-15 m². There convection cells are much smaller, at the scale of 2.4 km to 3 km. Stochastic distributions of porosity and permeability in the Yarragadee cause the formation of convection cells to adjust to the permeability field, yielding a less distinct convection pattern. Where the Yarragadee Aquifer is in contact with overlying aquifers, stable regions of down flow develop. These in turn have a strong impact on the regional flow field and therefore on the temperature distribution. Temperatures drop to about 40 °C in 2 km depth. In order to improve the reliability of the model, as well as identification and comparison of convection cells in different simulations, we are developing a specialized visualization tool tailored to this purpose. By using tools like particle tracing and direct volume rendering, the recognition of the spatial distribution of convection cells and their change in the different cases facilitated.
In this contribution, we present an immersive visualization of room acoustical simulation data. In contrast to the commonly employed external viewpoint, our approach places the user inside the visualized data. The main problem with this technique is the occlusion of some data points by others. We present different solutions for this problem that allow an interactive analysis of the simulation data.