Open Access

Simulations and serious games require realistic behavior of multiple intelligent agents in real-time. One particular issue is how attention and multi-modal sensory memory can be modeled in a natural but effective way, such that agents controllably react to salient objects or are distracted by other multi-modal cues from their current intention. We propose a conceptual framework that provides a solution with adherence to three main design goals: natural behavior, real-time performance, and controllability. As a proof of concept, we implement three major components and showcase effectiveness in a real-time game engine scenario. Within the exemplified scenario, a visual sensor is combined with static saliency probes and auditory cues. The attention model weighs bottom-up attention against intention-related top-down processing, controllable by a designer using memory and attention inhibitor parameters. We demonstrate our case and discuss future extensions.

This paper presents the implementation and evaluation of a computer vision task on a Field Programmable Gate Array (FPGA). As an experimental approach for an application-specific image-processing problem, it provides results about gained performance and precision compared with similar solutions on General Purpose Processor (GPP) architectures. The problem of detecting Binary Large OBjects (BLOBs) in a continuous video stream and computation of their center points has been addressed. Most existing solutions are realized on GPP platforms, where resolution of image material and sequential processing define the performance barrier. FPGA based approaches perform implemented algorithms as fast as hardware circuits and in addition offer parallelization abilities. The evaluation compares precision and performance gain against similar approaches on GPP platforms. The paper discusses different concepts for BLOB detection and shows the implementation of one common method for BLOB detection, including design problems and performance evaluation.

The objective of the FIVIS project is to develop a bicycle simulator which is able to simulate real life bicycle ride situations as a virtual scenario within an immersive environment. A sample test bicycle is mounted on a motion platform to enable a close to reality simulation of turns and balance situations. The visual field of the bike rider is enveloped within a multi-screen visualisation environment which provides visual data relative to the motion and activity of the test bicycle. That means the bike rider has to pedal and steer the bicycle as a usual bicycle, while the motion is recorded and processed to control the simulation. Furthermore, the platform is fed with real forces and accelerations that have been logged by a mobile data acquisition system during real bicycle test drives. Thus, using a feedback system makes the movements of the platform match to the virtual environment and the reaction of the driver (e.g. steering angle, step rate).

This paper presents the newly founded Institute of Visual Computing at the Bonn-Rhine-Sieg University of Applied Sciences in Sankt Augustin, Germany. The research focuses as well as an overview of current projects are going to be part of this presentation.

Grailog embodies a systematics to visualize knowledge sources by graphical elements. Its main benefit is that the resulting visual presentations are easier to read for humans than the original symbolic source code. In this paper we introduce a methodology to handle the mapping from Datalog RuleML, serialized in XML, to an SVG representation of Grailog, also serialized in XML, via eXtensible Stylesheet Language Transformations (XSLT) 2.0/XML; the SVG is then rendered visually by modern Web browsers. This initial mapping is realized to target Grailog's "fully node copied" normal form. Elements can thus be translated one at a time, separating the fundamental Datalog-to-SVG translation concern from the concern of merging node copies for optimal (hyper)graph layout and avoiding its high computational complexity in this online tool. The resulting open source Grailog Knowledge-Source Visualizer (Grailog KS Viz) supports Datalog RuleML with positional relations of arity n>1. The on-the-fly transformation was shown to run on all recent major Web browsers and should be easy to understand, use, and extend.

In interactive multi-screen visualization environments, every output device has to be constantly supplied with video information. Such visualization environments often use large projection screens, which require high resolution visualization data. An efficient approach to master this challenge is to distribute the workload to multiple low-cost computer systems. Nowadays’ game consoles are very powerful and specialized for interactive graphics applications; therefore they are well suited to be applied for computational expensive rendering purposes in real-time applications. The proposed solution (dXNA) has been developed on Microsoft’s XNA Game Studio. It supports interactive distributed rendering on multiple Xbox 360 and PC setups. Application logic synchronization and network session management are completely handled by dXNA. The interface of dXNA is similar to XNA Game Studio’s interface, which allows for efficient porting of existing projects. It has been proven that dXNA is an efficient and lightweight solution for distributed rendering for interactive multi-screen visualization environments.

Virtual reality environments are increasingly being used to encourage individuals to exercise more regularly, including as part of treatment in those with mental health or neurological disorders. The success of virtual environments likely depends on whether a sense of presence can be established, where participants become fully immersed in the virtual environment. Exposure to virtual environments is associated with physiological responses, including cortical activation changes. Whether the addition of a real exercise within a virtual environment alters sense of presence perception, or the accompanying physiological changes, is not known. In a randomized and controlled study design, trials of moderate-intensity exercise (i.e. self-paced cycling) and no-exercise (i.e. automatic propulsion) were performed within three levels of virtual environment exposure. Each trial was 5-min in duration and was followed by post-trial assessments of heart rate, perceived sense of presence, EEG, and mental state. Changes in psychological strain and physical state were generally mirrored by neural activation patterns. Furthermore these change indicated that exercise augments the demands of virtual environment exposures and this likely contributed to an enhanced sense of presence.

"Visual Computing" (VC) fasst als hochgradig aktuelles Forschungsgebiet verschiedene Bereiche der Informatik zusammen, denen gemeinsam ist, dass sie sich mit der Erzeugung und Auswertung visueller Signale befassen. Im Fachbereich Informatik der FH Bonn-Rhein-Sieg nimmt dieser Aspekt eine zentrale Rolle in Lehre und Forschung innerhalb des Studienschwerpunktes Medieninformatik ein. Drei wesentliche Bereiche des VC werden besonders in diversen Lehreinheiten und verschiedenen Projekten vermittelt: Computergrafik, Bildverarbeitung und Hypermedia-Anwendungen. Die Aktivitäten in diesen drei Bereichen fließen zusammen im Kontext immersiver virtueller Visualisierungsumgebungen.

Recently, virtual environments (VEs) are suggested to encourage users to exercise regularly. The benefits of chronic exercise on cognitive performance are well documented in non-VE neurophysiological and behavioural studies. Based on event-related potentials (ERP) such as the N200 and P300, cognitive processing may be interpreted on a neuronal level. However, exercise-related neuroelectric adaptation in VE remains widely unclear and thus characterizes the primary aim of the present study. Twenty-two healthy participants performed active (moderate cycling exercise) and passive (no exercise) sessions in three VEs (control, front, surround), each generating a different sense of presence. Within sessions, conditions were randomly assigned, each lasting 5 min and including a choice reaction-time task to assess cognitive performance. According to the international 10:20 system, EEG with real-time triggered stimulus onset was recorded, and peaks of N200 and P300 components (amplitude, latency) were exported for analysis. Heart rate was recorded, and sense of presence assessed prior to and following each session and condition. Results revealed an increase in ERP amplitudes (N200: p < 0.001; P300: p < 0.001) and latencies (N200: p < 0.001) that were most pronounced over fronto-central and occipital electrode sites relative to an increased sense of presence (p < 0.001); however, ERP were not modulated by exercise (each p > 0.05). Hypothesized to mirror cognitive processing, decreases of cognitive performance's accuracy and reaction time failed significance. With respect to previous research, the present neuroelectric adaptation gives reason to believe in compensative neuronal resources that balance demanding cognitive processing in VE to avoid behavioural inefficiency.

For almost all modern means of transportation (car, train, airplane) driving simulators exist that provide realistic models of complex traffic situations under defined laboratory conditions. For many years, these simulators have been successfully used for drivers’ training and education and have considerably contributed to the overall road safety. Unfortunately, there is no such advanced system for the bicycle, although the number of bike accidents has been increasing against the common trend during the last decade. Hence the objective of this project is to design a real bicycle simulator that is able to generate any desired traffic situation within an immersive visualization environment. For this purpose the bike is mounted onto a motion platform with six degrees of freedom that enables a close-to-reality simulation of external forces acting on the bike. This system is surrounded by three projection walls displaying a virtual scenario.