Open Access

Background: Virtual reality combined with spherical treadmills is used across species for studying neural circuits underlying navigation. New Method: We developed an optical flow-based method for tracking treadmil ball motion in real-time using a single high-resolution camera. Results: Tracking accuracy and timing were determined using calibration data. Ball tracking was performed at 500 Hz and integrated with an open source game engine for virtual reality projection. The projection was updated at 120 Hz with a latency with respect to ball motion of 30 ± 8 ms. Comparison: with Existing Method(s) Optical flow based tracking of treadmill motion is typically achieved using optical mice. The camera-based optical flow tracking system developed here is based on off-the-shelf components and offers control over the image acquisition and processing parameters. This results in flexibility with respect to tracking conditions – such as ball surface texture, lighting conditions, or ball size – as well as camera alignment and calibration. Conclusions: A fast system for rotational ball motion tracking suitable for virtual reality animal behavior across different scales was developed and characterized.

„Industrie 4.0“ und weitere Schlagwörter wie „Big Data“, „Internet der Dinge“ oder „Cyber-physical Systems“ werden gegenwärtig in der Wirtschaft häufig aufgegriffen. Ausgangspunkt hierfür ist die Vernetzung von IT-Technologien sowie die durchgängige Digitalisierung. Nicht nur die Geschäftsfelder und Business-Modelle der Unternehmen selbst unterliegen dabei ei-nem entsprechend radikalen Wandel, dieser bezieht sich auch auf die Arbeitsumgebungen der Mitarbeiter, sowie den privaten und den öffentlichen Raum (Botthof, 2015; Hartmann, 2015).

Die Entwicklung intelligenter Technologien zur Unterstützung im Alltag und in den eigenen vier Wänden begleitet unsere Gesellschaft schon seit dem Zeitalter des Personal Computers. Mit dem Aufkommen des Internet der Dinge und begünstigt durch immer kleiner und günstiger werdende Hardware ergeben sich neue Potenziale, die das Thema Smart Home attraktiver als je zuvor werden lassen. Eine Vielzahl der aktuell im Markt verfügbaren Lösungen adressiert die Bedürfnisse Komfort, Sicherheit und effiziente Energienutzung. Die versprochene Intelligenz – smartness, wie sie der Begriff selbst suggeriert – wird vor allem bei Lösungen im privaten Nachrüstbereich überwiegend durch die Interaktion der Nutzer selbst und entsprechende regelbasierte Konfigurationen erzeugt. Diese notwendige Art der Interaktion und die damit verbundenen Aufwände sind jedoch von starker Bedeutung für das gesamte Nutzungserlebnis Smart Home und führen nicht selten zu Frustration oder gar Resignation in der Nutzung.

Computer graphics research strives to synthesize images of a high visual realism that are indistinguishable from real visual experiences. While modern image synthesis approaches enable to create digital images of astonishing complexity and beauty, processing resources remain a limiting factor. Here, rendering efficiency is a central challenge involving a trade-off between visual fidelity and interactivity. For that reason, there is still a fundamental difference between the perception of the physical world and computer-generated imagery. At the same time, advances in display technologies drive the development of novel display devices. The dynamic range, the pixel densities, and refresh rates are constantly increasing. Display systems enable a larger visual field to be addressed by covering a wider field-of-view, due to either their size or in the form of head-mounted devices. Currently, research prototypes are ranging from stereo and multi-view systems, head-mounted devices with adaptable lenses, up to retinal projection, and lightfield/holographic displays. Computer graphics has to keep step with, as driving these devices presents us with immense challenges, most of which are currently unsolved. Fortunately, the human visual system has certain limitations, which means that providing the highest possible visual quality is not always necessary. Visual input passes through the eye’s optics, is filtered, and is processed at higher level structures in the brain. Knowledge of these processes helps to design novel rendering approaches that allow the creation of images at a higher quality and within a reduced time-frame. This thesis presents the state-of-the-art research and models that exploit the limitations of perception in order to increase visual quality but also to reduce workload alike - a concept we call perception-driven rendering. This research results in several practical rendering approaches that allow some of the fundamental challenges of computer graphics to be tackled. By using different tracking hardware, display systems, and head-mounted devices, we show the potential of each of the presented systems. The capturing of specific processes of the human visual system can be improved by combining multiple measurements using machine learning techniques. Different sampling, filtering, and reconstruction techniques aid the visual quality of the synthesized images. An in-depth evaluation of the presented systems including benchmarks, comparative examination with image metrics as well as user studies and experiments demonstrated that the methods introduced are visually superior or on the same qualitative level as ground truth, whilst having a significantly reduced computational complexity.