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The work at hand outlines a recording setup for capturing hand and finger movements of musicians. The focus is on a series of baseline experiments on the detectability of coloured markers under different lighting conditions. With the goal of capturing and recording hand and finger movements of musicians in mind, requirements for such a system and existing approaches are analysed and compared. The results of the experiments and the analysis of related work show that the envisioned setup is suited for the expected scenario.
We present basho, a light weight and easily extendable virtual environment (VE) framework. Key benefits of this framework are independence of the scene element representation and the rendering API. The main goal was to make VE applications flexible without the need to change them, not only by being independent from input and output devices. As an example, with basho it is possible to switch from local illumination models to ray tracing by just replacing the renderer. Or to replace the graphical representation of the scene elements without the need to change the application. Furthermore it is possible to mix rendering technologies within a scene. This paper emphasises on the abstraction of the scene element representation.
Motion capture, often abbreviated mocap, generally aims at recording any kind of motion -- be it from a person or an object -- and to transform it to a computer-readable format. Especially the data recorded from (professional and non-professional) human actors are typically used for analysis in e.g. medicine, sport sciences, or biomechanics for evaluation of human motion across various factors. Motion capture is also widely used in the entertainment industry: In video games and films realistic motion sequences and animations are generated through data-driven motion synthesis based on recorded motion (capture) data.
Although the amount of publicly available full-body-motion capture data is growing, the research community still lacks a comparable corpus of specialty motion data such as, e.g. prehensile movements for everyday actions. On the one hand, such data can be used to enrich (hand-over animation) full-body motion capture data - usually captured without hand motion data due to the drastic dimensional difference in articulation detail. On the other hand, it provides means to classify and analyse prehensile movements with or without respect to the concrete object manipulated and to transfer the acquired knowledge to other fields of research (e.g. from 'pure' motion analysis to robotics or biomechanics).
Therefore, the objective of this motion capture database is to provide well-documented, free motion capture data for research purposes.
The presented database GraspDB14 in sum contains over 2000 prehensile movements of ten different non-professional actors interacting with 15 different objects. Each grasp was realised five times by each actor. The motions are systematically named containing an (anonymous) identifier for each actor as well as one for the object grasped or interacted with.
The data were recorded as joint angles (and raw 8-bit sensor data) which can be transformed into positional 3D data (3D trajectories of each joint).
In this document, we provide a detailed description on the GraspDB14-database as well as on its creation (for reproducibility).
Chapter 2 gives a brief overview of motion capture techniques, freely available motion capture databases for both, full body motions and hand motions, and a short section on how such data is made useful and re-used. Chapter 3 describes the database recording process and details the recording setup and the recorded scenarios. It includes a list of objects and performed types of interaction. Chapter 4 covers used file formats, contents, and naming patterns. We provide various tools for parsing, conversion, and visualisation of the recorded motion sequences and document their usage in chapter 5.
Lower back pain is one of the most prevalent diseases in Western societies. A large percentage of European and American populations suffer from back pain at some point in their lives. One successful approach to address lower back pain is postural training, which can be supported by wearable devices, providing real-time feedback about the user’s posture. In this work, we analyze the changes in posture induced by postural training. To this end, we compare snapshots before and after training, as measured by the Gokhale SpineTracker™. Considering pairs of before and after snapshots in different positions (standing, sitting, and bending), we introduce a feature space, that allows for unsupervised clustering. We show that resulting clusters represent certain groups of postural changes, which are meaningful to professional posture trainers.
Foreword to the Special Section on the Symposium on Virtual and Augmented Reality 2019 (SVR 2019)
(2020)
Designs for decorative surfaces, such as flooring, must cover several square meters to avoid visible repeats. While the use of desktop systems is feasible to support the designer, it is challenging for a non-domain expert to get the right impression of the appearances of surfaces due to limited display sizes and a potentially unnatural interaction with digital designs. At the same time, large-format editing of structure and gloss is becoming increasingly important. Advances in the printing industry allow for more faithful reproduction of such surface details. Unfortunately, existing systems for visualizing surface designs cannot adequately account for gloss, especially for non-domain experts. Here, the complex interaction of light sources and the camera position must be controlled using software controls. As a result, only small parts of the data set can be properly inspected at a time. Also, real-world lighting is not considered here. This work presents a system for the processing and realistic visualization of large decorative surface designs. To this end, we present a tabletop solution that is coupled to a live 360° video feed and a spatial tracking system. This allows for reproducing natural view-dependent effects like real-world reflections, live image-based lighting, and the interaction with the design using virtual light sources employing natural interaction techniques that allow for a more accurate inspection even for non-domain experts.
In diesem Artikel wird darüber berichtet, ob die Glaubwürdigkeit von Avataren als mögliches Modulationskriterium für die virtuelle Expositionstherapie von Agoraphobie in Frage kommt. Dafür werden mehrere Glaubwürdigkeitsstufen für Avatare, die hypothetisch einen Einfluss auf die virtuelle Expositionstherapie von Agoraphobie haben könnten sowie ein potentielles Expositionsszenario entwickelt. Die Arbeit kann innerhalb einer Studie einen signifikanten Einfluss der Glaubwürdigkeitsstufen auf Präsenz, Kopräsenz und Realismus aufzeigen.
Rendering techniques for design evaluation and review or for visualizing large volume data often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates. A view direction based rendering technique renders the users central field of view in high quality whereas the surrounding is rendered with a level of detail approach depending on the distance to the users central field of view thus giving the opportunity to increase rendering efficiency. We propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.
A recent trend in interactive environments are large, ultra high resolution displays (LUHRDs). Compared to other large interactive installations, like the CAVE tm , LUHRDs are usually flat or (slightly) curved and have a significantly higher resolution, offering new research and application opportunities.
This tutorial provides information for researchers and engineers who plan to install and use a large ultra-high resolution display. We will give detailed information on the hardware and software of recently created and established installations and will show the variety of possible approaches. Also, we will talk about rendering software, rendering techniques and interaction for LUHRDs, as well as applications.
When navigating larger virtual environments and computer games, natural walking is often unfeasible. Here, we investigate how alternatives such as joystick- or leaning-based locomotion interfaces ("human joystick") can be enhanced by adding walking-related cues following a sensory substitution approach. Using a custom-designed foot haptics system and evaluating it in a multi-part study, we show that adding walking related auditory cues (footstep sounds), visual cues (simulating bobbing head-motions from walking), and vibrotactile cues (via vibrotactile transducers and bass-shakers under participants' feet) could all enhance participants' sensation of self-motion (vection) and involement/presence. These benefits occurred similarly for seated joystick and standing leaning locomotion. Footstep sounds and vibrotactile cues also enhanced participants' self-reported ability to judge self-motion velocities and distances traveled. Compared to seated joystick control, standing leaning enhanced self-motion sensations. Combining standing leaning with a minimal walking-in-place procedure showed no benefits and reduced usability, though. Together, results highlight the potential of incorporating walking-related auditory, visual, and vibrotactile cues for improving user experience and self-motion perception in applications such as virtual reality, gaming, and tele-presence.
Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews ofstatic scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.
Abschlussbericht zum BMBF-Fördervorhaben Enabling Infrastructure for HPC-Applications (EI-HPC)
(2020)
Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.
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.