Publications

Common approaches for the haptic rendering of complex scenarios employ multi-rate simulation schemes. Here, the collision queries or the simulation of a complex deformable object are often performed asynchronously at a lower frequency, while some kind of intermediate contact representation is used to simulate interactions at the haptic rate. However, this can produce artifacts in the haptic rendering when the contact situation quickly changes and the intermediate representation is not able to reflect the changes due to the lower update rate.

We address this problem utilizing a novel contact model. It facilitates the creation of contact representations that are accurate for a large range of motions and multiple simulation time-steps. We handle problematic geometrically convex contact regions using a local convex decomposition and special constraints for convex areas. We combine our accurate contact model with an implicit temporal integration scheme to create an intermediate mechanical contact representation, which reflects the dynamic behavior of the simulated objects. To maintain a haptic real time simulation, the size of the region modeled by the contact representation is automatically adapted to the complexity of the geometry in contact. Moreover, we propose a new iterative solving scheme for the involved constrained dynamics problems. We increase the robustness of our method using techniques from trust region-based optimization. Our approach can be combined with standard methods for the modeling of deformable objects or constraint-based approaches for the modeling of, for instance, friction or joints. We demonstrate its benefits with respect to the simulation accuracy and the quality of the rendered haptic forces in several scenarios with one or more haptic proxies.

Interactive analysis of 3D relational data is challenging. A common way of representing such data are node-link diagrams as they support analysts in achieving a mental model of the data. However, naïve 3D depictions of complex graphs tend to be visually cluttered, even more than in a 2D layout. This makes graph exploration and data analysis less efficient. This problem can be addressed by edge bundling. We introduce a 3D cluster-based edge bundling algorithm that is inspired by the force-directed edge bundling (FDEB) algorithm [Holten2009] and fulfills the requirements to be embedded in an interactive framework for spatial data analysis. It is parallelized and scales with the size of the graph regarding the runtime. Furthermore, it maintains the edge’s model and thus supports rendering the graph in different structural styles. We demonstrate this with a graph originating from a simulation of the function of a macaque brain.

To avoid simulator sickness and improve presence in immersive virtual environments (IVEs), high frame rates and low latency are required. In contrast, volume rendering applications typically strive for high visual quality that induces high computational load and, thus, leads to low frame rates. To evaluate this trade-off in IVEs, we conducted a controlled user study with 53 participants. Search and count tasks were performed in a CAVE with varying volume rendering conditions which are applied according to viewer position updates corresponding to head tracking. The results of our study indicate that participants preferred the rendering condition with continuous adjustment of the visual quality over an instantaneous adjustment which guaranteed for low latency and over no adjustment providing constant high visual quality but rather low frame rates. Within the continuous condition, the participants showed best task performance and felt less disturbed by effects of the visualization during movements. Our findings provide a good basis for further evaluations of how to accelerate volume rendering in IVEs according to user’s preferences.

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.

Data annotation finds increasing use in Virtual Reality applications with the goal to support the data analysis process, such as architectural reviews. In this context, a variety of different annotation systems for application to immersive virtual environments have been presented. While many interesting interaction designs for the data annotation workflow have emerged from them, important details and evaluations are often omitted. In particular, we observe that the process of handling metadata to interactively create and manage complex annotations is often not covered in detail. In this paper, we strive to improve this situation by focusing on the design of data annotation workflows and their evaluation. We propose a workflow design that facilitates the most important annotation operations, i.e., annotation creation, review, and modification. Our workflow design is easily extensible in terms of supported annotation and metadata types as well as interaction techniques, which makes it suitable for a variety of application scenarios. To evaluate it, we have conducted a user study in a CAVE-like virtual environment in which we compared our design to two alternatives in terms of a realistic annotation creation task. Our design obtained good results in terms of task performance and user experience.

This article wants to give some impulses for a discussion about how an “ultimate” display should look like to support the Neuroscience community in an optimal way. In particular, we will have a look at immersive display technology. Since its hype in the early 90’s, immersive Virtual Reality has undoubtedly been adopted as a useful tool in a variety of application domains and has indeed proven its potential to support the process of scientific data analysis. Yet, it is still an open question whether or not such non-standard displays make sense in the context of neuroscientific data analysis. We argue that the potential of immersive displays is neither about the raw pixel count only, nor about other hardware-centric characteristics. Instead, we advocate the design of intuitive and powerful user interfaces for a direct interaction with the data, which support the multi-view paradigm in an efficient and flexible way, and – finally – provide interactive response times even for huge amounts of data and when dealing multiple datasets simultaneously.

With the increase in data availability and data volume it becomes increasingly important to extract information and actionable knowledge from data. Information Visualization helps the user to understand data by utilizing vision as a relatively parallel input channel to the user’s mind. Decision Support systems on the other hand help users in making information actionable, by suggesting beneficial decisions and presenting them in context. Both fields share a common need for understanding the interface between the computer and the human. This makes human factors research critical for both fields. Understanding limitations of human perception, cognition and action, as well as their variance must be understood to fully leverage information visualization and decision support. This article reflects on research agendas for investigating human factors in the aforementioned fields.

Provenance tracking for visual analysis workflows is still a challenge as especially interaction and collaboration aspects are poorly covered in existing realizations. Therefore, we propose a first prototype addressing these issues based on the PROV model. Interactions in multiple applications by multiple users can be tracked by means of a web interface and, thus, allowing even for tracking of remote-located collaboration partners. In the end, we demonstrate the applicability based on two use cases and discuss some open issues not addressed by our implementation so far but that can be easily integrated into our architecture.

An immersive virtual environment is the ideal platform for the planning and training of on-orbit servicing missions. In such kind of virtual assembly simulation, grasping virtual objects is one of the most common and natural interactions. In this paper, we present a novel, small and lightweight electrotactile feedback device, specifically designed for immersive virtual environments. We conducted a study to assess the feasibility and usability of our interaction device. Results show that electrotactile feedback improved the user’s grasping in our virtual on-orbit servicing scenario. The task completion time was significantly lower and the precision of the user’s interaction was higher.

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.

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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.

Best Technote!