More and more universities are looking for solutions to integrate virtual reality (VR) into teaching and research. But most of the VR systems available for educational purposes are difficult to use without technical expertise, yet. This ability to operate easily, however, would make VR particularly valuable in the classroom. Therefore, this paper describes an exploratory study of university teachers' perceptions on authoring tools in an immersive virtual reality environments. The goal was to get an overview which of these tools, e.g. creation of 3D objects and annotations, teachers consider usable and useful. Overall, all 14 participants in the study were enthusiastic about the possibilities of content creation in VR. For the most part, they found the authoring tools easy to use and see their usefulness for teaching with respect to this first impression.

State-of-the-art (SOTA) object detectors are generally evaluated on object detection challenge datasets. However, automotive domain-specific quantitative analysis of detectors is limited and often incomplete. Moreover, evaluation of detectors is mainly focused on average precision (AP) metric, ignoring AP’s limitation such as insensitive to shape of the precision-recall curve. These issues are addressed in this paper by evaluating the most popular SOTA detectors on autonomous driving and autonomous parking datasets. AP weakness is addressed by evaluating detectors using the Localization-Recall-Precision (LRP) metric, which also provides a detailed understanding of a detector. Motivated from LRP, this paper also presents the optimal AP (oAP) metric for the fair comparison of detectors, which was ignored until now. The proposed oAP metric can be easily used with any object detector. In addition, a complete object detection pipeline starting from data collection to deployment on an embedded device is demonstrated in this work. Experimental results are presented graphically to analyze detector from a different perspective.

No abstract available.

Large, high-resolution displays demonstrated their effectiveness in lab settings for cognitively demanding tasks in single user and collaborative scenarios. The effectiveness is mostly reached through inherent displays» properties - large display real estate and high resolution - that allow for visualization of complex datasets, and support of group work and embodied interaction. To raise users» efficiency, however, more sophisticated user support in the form of advanced user interfaces might be needed. For that we need profound understanding of how large, tiled displays impact users work and behavior. We need to extract behavioral patterns for different tasks and data types. This paper reports on study results of how users, while working collaboratively, process spatially fixed items on large, tiled displays. The results revealed a recurrent pattern showing that users prefer to process documents column wise rather than row wise or erratic.

Head-mounted displays (HMDs) with integrated eye trackers have opened up a new realm for gaze-contingent rendering. The accurate estimation of gaze depth is essential when modeling the optical capabilities of the eye. Most recently multifocal displays are gaining importance, requiring focus estimates to control displays or lenses. Deriving the gaze depth solely by sampling the scene's depth at the point-of-regard fails for complex or thin objects as eye tracking is suffering from inaccuracies. Gaze depth measures using the eye's vergence only provide an accurate depth estimate for the first meter. In this work, we combine vergence measures and multiple depth measures into feature sets. This data is used to train a regression model to deliver improved estimates. We present a study showing that using multiple features allows for an accurate estimation of the focused depth (MSE<0.1m) over a wide range (first 6m).

In this research demo, we show different examples for the integration of multisensory cues to enhance user engagement and trigger emotional responses in immersive environments. Our primary focus is to use this modular-designed system for the supportive treatment of different anxiety disorders.

In presence of conflicting or ambiguous visual cues in complex scenes, performing 3D selection and manipulation tasks can be challenging. To improve motor planning and coordination, we explore audio-tactile cues to inform the user about the presence of objects in hand proximity, e.g., to avoid unwanted object penetrations. We do so through a novel glove-based tactile interface, enhanced by audio cues. Through two user studies, we illustrate that proximity guidance cues improve spatial awareness, hand motions, and collision avoidance behaviors, and show how proximity cues in combination with collision and friction cues can significantly improve performance.

We present a novel forearm-and-glove tactile interface that can enhance 3D interaction by guiding hand motor planning and coordination. In particular, we aim to improve hand motion and pose actions related to selection and manipulation tasks. Through our user studies, we illustrate how tactile patterns can guide the user, by triggering hand pose and motion changes, for example to grasp (select) and manipulate (move) an object. We discuss the potential and limitations of the interface, and outline future work.

In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.

Enhancing touch screen interfaces through non-visual cues has been shown to improve performance. In this paper we report on a novel system that explores the usage of a forcesensitive motion-platform enhanced tablet interface to improve multi-modal interaction based on visuo-haptic instead of tactile feedback. Extending mobile touch screen with force-sensitive haptic feedback has potential to enhance performance interacting with GUIs and to improve perception of understanding relations. A user study was performed to determine the perceived recognition of different 3D shapes and the perception of different heights. Furthermore, two application scenarios are proposed to explore our proposed visuo-haptic system. The studies show the positive stance towards the feedback, as well as the found limitations related to perception of feedback.

Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real-time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel (high dynamic range, wider color gamut/fidelity), increasing refresh rates (better motion depiction), and an increasing number of displayed views per pixel (stereo, multi-view, all the way to holographic or lightfield displays). These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.

In this paper, we report on novel zooming interface methods that deploy a small handheld projector. Using mobile projections to visualize object/environment-related information on real objects introduces new aspects for zooming interfaces. Different approaches are investigated that focus on maintaining a level of context while exploring detailed information. Doing so, we propose methods that provide alternative contextual cues within a single projector and deploy the potential of zoom lenses to support a multilevel zooming approach. Furthermore, we look into the correlation between pixel density, distance to the target, and projection size. Alongside these techniques, we report on multiple user studies, in which we quantified the projection limitations and validated various interactive visualization approaches. Thereby, we focused on solving issues related to pixel density, brightness, and contrast that affect the design of more effective legible zooming interfaces for handheld projectors.

Supported by their large size and high resolution, display walls suit well for different collaboration types. However, in order to foster instead of impede collaboration processes, interaction techniques need to be carefully designed, taking into regard the possibilities and limitations of the display size, and their effects on human perception and performance. In this paper we investigate the impact of visual distractors (which, for instance, might be caused by other collaborators' input) in peripheral vision on short-term memory and attention. The distractors occur frequently when multiple users collaborate in large wall display systems and may draw attention away from the main task, as such potentially affecting performance and cognitive load. Yet, the effect of these distractors is hardly understood. Gaining a better understanding thus may provide valuable input for designing more effective user interfaces. In this article, we report on two interrelated studies that investigated the effect of distractors. Depending on when the distractor is inserted in the task performance sequence, as well as the location of the distractor, user performance can be disturbed: we will show that distractors may not affect short term memory, but do have an effect on attention. We will closely look into the effects, and identify future directions to design more effective interfaces.

Abstract Head‐mounted displays with dense pixel arrays used for virtual reality applications require high frame rates and low latency rendering. This forms a challenging use case for any rendering approach. In addition to its ability of generating realistic images, ray tracing offers a number of distinct advantages, but has been held back mainly by its performance. In this paper, we present an approach that significantly improves image generation performance of ray tracing. This is done by combining foveated rendering based on eye tracking with reprojection rendering using previous frames in order to drastically reduce the number of new image samples per frame. To reproject samples a coarse geometry is reconstructed from a G‐Buffer. Possible errors introduced by this reprojection as well as parts that are critical to the perception are scheduled for resampling. Additionally, a coarse color buffer is used to provide an initial image, refined smoothly by more samples were needed. Evaluations and user tests show that our method achieves real‐time frame rates, while visual differences compared to fully rendered images are hardly perceivable. As a result, we can ray trace non‐trivial static scenes for the Oculus DK2 HMD at 1182 × 1464 per eye within the the VSync limits without perceived visual differences.

This paper introduces a novel zooming interface deploying a pico projector that, instead of a second visual display, leverages audioscapes for contextual information. The technique enhances current flashlight metaphor approaches, supporting flexible usage within the domain of spatial augmented reality to focus on object or environment-related details. Within a user study we focused on quantifying the projection limitations related to depiction of details through the pico projector and validated the interaction approach. The quantified results of the study correlate pixel density, detail and proximity, which can greatly aid to design more effective, legible zooming interfaces for pico projectors - the study can form an example testbed that can be applied well for testing aberrations with other projectors. Furthermore, users rated the zooming technique using audioscapes well, showing the validity of the approach. The studies form the foundation for extending our work by detailing out the audio-visual approach and looking more closely in the role of real-world features on interpreting projected content.

Position awareness in unknown and large indoor spaces represents a great advantage for people, everyday pedestrians have to search for specific places, products and services. In this work a positioning solution able to localize the user based on data measured with a mobile device is described and evaluated. The position estimate uses data from smartphone built-in sensors, WiFi (Wireless Fidelity) adapter and map information of the indoor environment (e.g. walls and obstacles). A probability map derived from statistical information of the users tracked location over a period of time in the test scenario is generated and embedded in a map graph, in order to correct and combine the position estimates under a Bayesian representation. PDR (Pedestrian Dead Reckoning), beacon-based Weighted Centroid position estimates, map information obtained from building OpenStreetMap XML representation and probability map users path density are combined using a Particle Filter and implemented in a smartphone application. Based on evaluations, this work verifies that the use of smartphone hardware components, map data and its semantic information represented in the form of a OpenStreetMap structure provide 2.48 meters average error after 1,700 travelled meters and a scalable indoor positioning solution. The Particle Filter algorithm used to combine various sources of information, its radio WiFi-based observation, probability particle weighting process and the mapping approach allowing the inclusion of new indoor environments knowledge show a promising approach for an extensible indoor navigation system.

A person has to deal with large and unknown scenarios, for example a client searching for a expositor in a trade fair or a passenger looking for a gate in an airport. Due to the fact that position awareness represents a great advantage for people, a navigation system implemented for a commercial smartphone can help the user to save time and money. In this work a navigation example application able to localize and provide directions to a desired destination in an indoor environment is presented and evaluated. The position of the user is calculated with information from the smartphone builtin sensors, WiFi adapter and floor-plan layout of the indoor environment. A commercial smartphone is used as the platform to implement the example application, due to it's hardware features, computational power and the graphic user interface available for the users. Evaluations verified that room accuracy is achieved for robust localization by using the proposed technologies and algorithms. The used optimal sensor fusion filter for different sources of information and the easy to deploy infrastructure in a new environment show promise for mobile indoor navigation systems.

We present a system for interactive magnetic field simulation in an AR-setup. The aim of this work is to investigate how AR technology can help to develop a better understanding of the concept of fields and field lines and their relationship to the magnetic forces in typical school experiments. The haptic feedback is provided by real magnets that are optically tracked. In a stereo video see-through head-mounted display, the magnets are augmented with the dynamically computed field lines.

We present an interactive system that uses ray tracing as a rendering technique. The system consists of a modular Virtual Reality framework and a cluster-based ray tracing rendering extension running on a number of Cell Broadband Engine-based servers. The VR framework allows for loading rendering plugins at runtime. By using this combination it is possible to simulate interactively effects from geometric optics, like correct reflections and refractions.

We present an application that allows users to interactively visualise data of medical studies. This application enables the users to get a view on the data set, to interact with the data in an intuitive way and to analyse it collaboratively. The goal of these first studies of the data sets is to find relations between measured values.

The Render Cache [1,2] allows the interactive display of very large scenes, rendered with complex global illumination models, by decoupling camera movement from the costly scene sampling process. In this paper, the distributed execution of the individual components of the Render Cache on a PC cluster is shown to be a viable alternative to the shared memory implementation.As the processing power of an entire node can be dedicated to a single component, more advanced algorithms may be examined. Modular functional units also lead to increased flexibility, useful in research as well as industrial applications.We introduce a new strategy for view-driven scene sampling, as well as support for multiple camera viewpoints generated from the same cache. Stereo display and a CAVE multi-camera setup have been implemented.The use of the highly portable and inter-operable CORBA networking API simplifies the integration of most existing pixel-based renderers. So far, three renderers (C++ and Java) have been adapted to function within our framework.

Two query problems for visibility are considered. The first one is to find the visibility set of two query objects A and B of the same type as the objects of the given scene. The visibility set is characterized by those line segments connecting points on A and B which do not intersect scene objects between A and B. We show that scenes consisting of disjoint line segments in the plane can be processed into a data structure of about linear size so that the visibility set can be found in sublinear time per component of the representation chosen for the visibility set. The construction can also be applied to scenes of disjoint triangles in space. The disadvantage of possibly many components can be diminished by pre-clipping against the viewing hull of A and B. The query version of the clipping problem can also be solved in about linear space and sublinear query time. The result of the first problem is used for an efficient solution of the second problem which is to calculate the visibility sets between query object A and all scene objects visible from A.

The authors present an analysis of the impacts of different interpolation methods on the reconstruction of the radiosity function across a patch. Two groups of methods are compared: one group based on regular grids and the other based on adaptive patch subdivisions. They handle points on adaptive subdivisions as scattered data points which opens the field of scattered data interpolation. Visual and numerical results are presented.