Open Access

Many modern computer games take place in urban environments. One important fact about such environments is that there are plenty of other people around who might react to whatever the user does. For example in the "FIVIS" project a bicycle simulator is developed that will serve (beside other applications) as an instrument for traffic education which strongly requires other traffic participants reacting to the users actions (see http://www.fivis.eu and [7]). This contribution describes our current work on a general approach for an interactive agent system for urban environments.

This report presents the implementation and evaluation of a computer vision problem on a Field Programmable Gate Array (FPGA). This work is based upon [5] where the feasibility of application specific image processing algorithms on a FPGA platform have been evaluated by experimental approaches. The results and conclusions of that previous work builds the starting point for the work, described in this report. The project results show considerable improvement of previous implementations in processing performance and precision. Different algorithms for detecting Binary Large OBjects (BLOBs) more precisely have been implemented. In addition, the set of input devices for acquiring image data has been extended by a Charge-Coupled Device (CCD) camera. The main goal of the designed system is to detect BLOBs in continuous video image material and compute their center points. This work belongs to the MI6 project from the Computer Vision research group of the University of Applied Sciences Bonn-Rhein-Sieg1 . The intent is the invention of a passive tracking device for an immersive environment to improve user interaction and system usability. Therefore the detection of the users position and orientation in relation to the projection surface is required. For a reliable estimation a robust and fast computation of the BLOB's center-points is necessary. This project has covered the development of a BLOB detection system on an Altera DE2 Development and Education Board with a Cyclone II FPGA. It detects binary spatially extended objects in image material and computes their center points. Two different sources have been applied to provide image material for the processing. First, an analog composite video input, which can be attached to any compatible video device. Second, a five megapixel CCD camera, which is attached to the DE2 board. The results are transmitted on the serial interface of the DE2 board to a PC for validation of their ground truth and further processing. The evaluation compares precision and performance gain dependent on the applied computation methods and the input device, which is providing the image material.

Nowadays Field Programmable Gate Arrays (FPGA) are used in many fields of research, e.g. to create prototypes of hardware or in applications where hardware functionality has to be changed more frequently. Boolean circuits, which can be implemented by FPGAs are the compiled result of hardware description languages such as Verilog or VHDL. Odin II is a tool, which supports developers in the research of FPGA based applications and FPGA architecture exploration by providing a framework for compilation and verification. In combination with the tools ABC, T-VPACK and VPR, Odin II is part of a CAD flow, which compiles Verilog source code that targets specific hardware resources. This paper describes the development of a graphical user interface as part of Odin II. The goal is to visualize the results of these tools in order to explore the changing structure during the compilation and optimization processes, which can be helpful to research new FPGA architectures and improve the workflow.

In interactive visualization environments which use a multiple screen setup, every output device has to be supplied frequently with video information. Such virtual environments often use large projection screens, which require high resolution video data. When increasing scene complexity, it can become a challenge to equip a single computer with graphics hardware powerful enough for the task. An efficient approach is to distribute the workload to multiple low-cost computer systems such as game consoles. Nowadays' game consoles are very powerful and specialized for interactive graphics applications, therefore they are suitable to being used for rendering purposes. A framework has been developed that builds on Microsoft's XNA Game Studio. It enables for interactive distributed rendering on multiple Xbox 360 systems and PCs. Tasks such as game logic synchronization, network session management are fully handled by the framework. A game built with it can focus mostly on its own implementation. The framework's structure follows that of the XNA Game Studio, which allows porting existing game projects quickly. Our evaluation showed that the framework is a lightweight solution which leaves almost the full CPU time to the actual game.

Video surveillance has become a hot research topic due to the recently increased importance of safety and security issues. Usually, security personnel has to monitor a surveillance area and often they have to do this for 24 h a day. Thus, it would be desirable to develop intelligent surveillance systems that support this task automatically. The system described in this contribution is thought of such an automatic surveillance system that has been developed to detect several dangerous situations in subway stations. The workflow and the most important steps from foreground segmentation, shadow detection, tracking and classification to event detection are described, discussed and evaluated in detail. The developed surveillance system yields satisfying results, as dangerous situations that need to be recognized are detected in most cases.

The application of Raman and infrared (IR) microspectroscopy is leading to hyperspectral data containing complementary information concerning the molecular composition of a sample. The classification of hyperspectral data from the individual spectroscopic approaches is already state-of-the-art in several fields of research. However, more complex structured samples and difficult measuring conditions might affect the accuracy of classification results negatively and could make a successful classification of the sample components challenging. This contribution presents a comprehensive comparison in supervised pixel classification of hyperspectral microscopic images, proving that a combined approach of Raman and IR microspectroscopy has a high potential to improve classification rates by a meaningful extension of the feature space. It shows that the complementary information in spatially co-registered hyperspectral images of polymer samples can be accessed using different feature extraction methods and, once fused on the feature-level, is in general more accurately classifiable in a pattern recognition task than the corresponding classification results for data derived from the individual spectroscopic approaches.

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.

Estimation of camera motion from RGB-D images has been an active research topic in recent years. Several RGB-D visual odometry systems were reported in literature and released under open-source licenses. The objective of this contribution is to evaluate the recently published approaches to motion estimation. A publicly available dataset of RGB-D sequences with precise ground truth data is applied and results are compared and discussed. Experiments on a mobile robot used in the RoboCup@Work league are discussed as well. The system showing the best performance is capable of estimating the motion with drift as small as 1 cms under special conditions, though it has been proven to be robust against shakey motion and moderately non-static scenes.

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).

"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.