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.
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.
This paper describes a novel aircraft noise simulation technique developed at RWTH Aachen University, which makes use of aircraft noise auralization and 3D visualization to make aircraft noise both heard and seen in immersive Virtual Reality (VR) environments. This technique is intended to be used to increase the residents’ acceptance of aircraft noise by presenting noise changes in a more directly relatable form, and also aid in understanding what contributes to the residents’ subjective annoyance via psychoacoustic surveys. This paper describes the technique as well as some of its initial applications. The reasoning behind the development of such a technique is that the issue of aircraft noise experienced by residents in airport vicinities is one of subjective annoyance. Any efforts at noise abatement have been conventionally presented to residents in terms of noise level reductions in conventional metrics such as A-weighted level or equivalent sound level Leq. This conventional approach however proves insufficient in increasing aircraft noise acceptance due to two main reasons – firstly, the residents have only a rudimentary understanding of changes in decibel and secondly, the conventional metrics do not fully capture what the residents actually find annoying i.e. characteristics of aircraft noise they find least acceptable. In order to allow least resistance to air-traffic expansion, the acceptance of aircraft noise has to be increased, for which such a new approach to noise assessment is required.
Virtual Reality (VR) has been an active field of research for several decades, with 3D interaction and 3D User Interfaces (UIs) as important sub-disciplines. However, the development of 3D interaction techniques and in particular combining several of them to construct complex and usable 3D UIs remains challenging, especially in a VR context. In addition, there is currently only limited reusable software for implementing such techniques in comparison to traditional 2D UIs. To overcome this issue, we present ViSTA Widgets, a software framework for creating 3D UIs for immersive virtual environments. It extends the ViSTA VR framework by providing functionality to create multi-device, multi-focus-strategy interaction building blocks and means to easily combine them into complex 3D UIs. This is realized by introducing a device abstraction layer along sophisticated focus management and functionality to create novel 3D interaction techniques and 3D widgets. We present the framework and illustrate its effectiveness with code and application examples accompanied by performance evaluations.
In the simulation of multi-component systems, we often encounter a problem with a lack of ground-truth data. This situation makes the validation of our simulation methods and models a difficult task. In this work we present a guideline to design validation methodologies that can be applied to the validation of multi-component simulations that lack of ground-truth data. Additionally we present an example applied to an Ultrasound Image Simulation for medical training and give an overview of the considerations made and the results for each of the validation methods. With these guidelines we expect to obtain more comparable and reproducible validation results from which other similar work can benefit.
Understanding the performance behaviour of high-performance computing (hpc) applications based on performance profiles is a challenging task. Phenomena in the performance behaviour can stem from the hpc system itself, from the application’s code, but also from the simulation domain. In order to analyse the latter phenomena, we propose a system that visualizes profile-based performance data in its spatial context in the simulation domain, i.e., on the geometry processed by the application. It thus helps hpc experts and simulation experts understand the performance data better. Furthermore, it reduces the initially large search space by automatically labeling those parts of the data that reveal variation in performance and thus require detailed analysis.
Understanding the performance behaviour of massively parallel high-performance computing (HPC) applications based on call-path performance profiles is a time-consuming task. In this paper, we introduce the concept of directed variance in order to help analysts find performance bottlenecks in massive performance data and in the end optimize the application. According to HPC experts’ requirements, our technique automatically detects severe parts in the data that expose large variation in an application’s performance behaviour across system resources. Previously known variations are effectively filtered out. Analysts are thus guided through a reduced search space towards regions of interest for detailed examination in a 3D visualization. We demonstrate the effectiveness of our approach using performance data of common benchmark codes as well as from actively developed production codes.
Finding and understanding correlated performance behaviour of the individual functions of massively parallel high-performance computing (HPC) applications is a time-consuming task. In this poster, we propose filtered correlation analysis for automatically locating interdependencies in call-path performance profiles. Transforming the data into the frequency domain splits a performance phenomenon into sub-phenomena to be correlated separately. We provide the mathematical framework and an overview over the visualization, and we demonstrate the effectiveness of our technique.
Best Poster Award!
Computer-controlled virtual humans can serve as assistants in virtual scenes. Here, they are usually in an almost constant contact with the user. Nonetheless, in some applications assistants are required only temporarily. Consequently, presenting them only when needed, i.e, minimizing their presence time, might be advisable.
To the best of our knowledge, there do not yet exist any design guidelines for such agent-based support systems. Thus, we plan to close this gap by a controlled qualitative and quantitative user study in a CAVE-like environment.We expect users to prefer assistants with a low presence time as well as a low fallback time to get quick support. However, as both factors are linked, a suitable trade-off needs to be found. Thus, we plan to test four different strategies, namely fading, moving, omnipresent and busy. This work presents our hypotheses and our planned within-subject design.
In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.
Interactive visual data analysis is a well-established class of methods to gather knowledge from raw and complex data. A broad variety of examples can be found in literature presenting its applicability in various ways and different scientific domains. However, fully fledged solutions for visual analysis addressing learning analytics are still rare. Therefore, this paper will discuss visual and interactive data analysis for learning analytics by presenting best practices followed by a discussion of a general architecture combining interactive visualization employing the Information Seeking Mantra in conjunction with the paradigm of coordinated multiple views. Finally, by presenting a use case for ubiquitous learning analytics its applicability will be demonstrated with the focus on temporal and spatial relation of learning data. The data is gathered from a ubiquitous learning scenario offering information for students to identify learning partners and provides information to teachers enabling the adaption of their learning material.
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.
Phenomena in the performance behaviour of high-performance computing (HPC) applications can stem from the HPC system itself, from the application's code, but also from the simulation domain. In order to analyse the latter phenomena, we propose a system that visualizes profile-based performance data in its spatial context, i.e., on the geometry, in the simulation domain. It thus helps HPC experts but also simulation experts understand the performance data better. In addition, our tool reduces the initially large search space by automatically labelling large-variation views on the data which require detailed analysis.
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!
Virtual Agents (VAs) are embedded in virtual environments for two reasons: they enliven architectural scenes by representing more realistic situations, and they are dialogue partners. They can function as training partners such as representing students in a teaching scenario, or as assistants by, e.g., guiding users through a scene or by performing certain tasks either individually or in collaboration with the user. However, designing such VAs is challenging as various requirements have to be met. Two relevant factors will be briefly discussed in the talk: Collision Avoidance and Presence Strategies.
Experimental economics uses controlled and incentivized lab and field experiments to learn about economic behavior. By means of three examples, we illustrate how experiments conducted in immersive virtual environments emerge as a new methodological tool that can benefit behavioral economic research.