Stephan Olbrich

A metadata model for capturing presentations

We describe the design of a metadata model for capturing presentations developed as part of the VACE project (video and audio capturing and embedding). VACE is a modular, open, distributed framework for capturing presentations like lectures by using standard presentation and publishing tools for different media types. Different media formats can be used in one recording session in order to suit the needs of different presentation types, e.g. slides plus the talk of a lecturer. Metadata are necessary to combine these media data in an efficient way. The combination of content based and synchronisation metadata is utilized for the integration of recorded material e.g. in Web based learning systems, to provide navigation and search functions but can also be used for other post production purposes, e.g. video editing or DVD authoring.

Virtual reality movies-real-time streaming of 3D objects

Powerful servers for computation and storage, high-speed networking resources, and high-performance 3D graphics workstation, which are typically available in scientific research environments, potentially allow the development and productive application of advanced distributed high-quality multimedia concepts. Several bottlenecks, often caused by inefficient design and software implementation of current systems, prevent utilization of the offered performance of existing hardware and networking resources. We present a system architecture, which supports streamed online presentation of series of 3D objects. In the case of expensive simulations on a supercomputer, results are increasingly represented as 3D geometry to support immersive exploration, presentation, and collaboration techniques. Accurate representation and high-quality display are fundamental requirements to avoid misinterpretation of the data. Our system consists of the following parts: a preprocessor to create a special 3D representation ‐ optimized under transmission and streamed presentation issues in a high-performance working environment, an efficiently implemented streaming server, and a client. The client was implemented as a web browser plugin, integrating a viewer with high-quality virtual reality presentation (stereoscopic displays), interaction (tracking devices), and hyperlinking capabilities.

An efficient system for collaboration in tele-immersive environments

The paper describes the development of a high-performance system for visualizing complex scientific models in real-time. The architecure of the system is a client/server model, in which the simulator generates lists of 3D graphics objects in parallel to the simulation, from where they are sent to a streaming server. The server transfers the 3D objects to viewer clients. Clients communicate over a second connection with each other, which adds the ability to perform collaborative tasks. An application related to computational fluid dynamics is specified where such a tele-immersive system can be used. The approach differs to other solutions because it offers a large set of graphics primitives for visualization, and it is optimized for distributed, heterogenous environments.

Covase: Collaborative Visualization for Constructivist Learning

The paper specifies CoVASE, a software for teachers to create and view networked learning environments (VE). Students carry out virtual experiments in CoVASE, at the same time and different places. ...

Evaluation of a Scalable In-Situ Visualization System Approach in a Parallelized Computational Fluid Dynamics Application

Current parallel supercomputers provide sufficient performance to simulate unsteady three-dimensional fluid dynamics in high resolution. However, the visualization of the huge amounts of result data cannot be handled by traditional methods, where post-processing modules are usually coupled to the raw data source, either by files or by data flow. To avoid significant bottlenecks of the storage and communication resources, efficient techniques for data extraction and preprocessing at the source have been realized in the parallel, network-distributed chain of our Distributed Simulation and Virtual Reality Environment(DSVR). Here the 3D data extraction is implemented as a parallel library (libDVRP) and can be done in-situ during the numerical simulations, which avoids the storage of raw data for visualization at all.

Design and Psychophysical Study of Volume Compression for Haptic Rendering

The paper specifies a novel coder/decoder that compresses sequences of 3D texture data to support the haptic rendering of animated volumes. Lossy compression gives 25% of the original size. Lossy compression and clipping gives 3% but requires the renderer to query for new data when the point of contact moves. We evaluated the codec by means of rendering volumes on a 3-DOF Phantom 1.5A that simulated viscosity for each texture element. In this setting, we studied the impact of information loss in controlled experiments. We validated that our codec preserves haptic perception. An area of application is the development of network-distributed virtual environments that generate visual and haptic feedback

Strukturkonzepte für die Informations- und Kommunikationsversorgung von Hochschulen

Dr. Markus von der Heyde studierte Naturwissenschaftliche Informatik an der Universität Bielefeld. Nach einem Forschungsaufenthalt in den USA promovierte er am Max-Planck-Institut für biologische Kybernetik in Tübingen. Nach erfolgreicher wissenschaftlicher Laufbahn in DFGund EUProjekten wechselte er als Leiter des Servicezentrums für Computersysteme und -kommunikation an die Bauhaus-Universität Weimar. Das dort etablierte IuK Versorgungskonzept wurde 2008 vom Stifterverband im Wettbewerb „Campus Online“ ausgezeichnet. In den Vereinigungen ZKI, EUNIS und itSMF engagiert sich Dr. Markus von der Heyde vor allem für die IT-Themen Strategie, Service Management und Sicherheit.

A tele-immersive, virtual laboratory approach based on real-time streaming of 3D scene sequences

In this paper we describe a distributed system approach for three-dimensional exploration in the context of high-performance com¿puting, which supports postprocessing, online-visualization and in¿teractive steering scenarios. Our processing chain consists of three instances (data source, streaming server, viewer), which can be dis¿tributed in high-performance networks and operated either in a full pipeline (on-the-fly 3D visualization, computational steering) or in asynchronously running pairs (visualization of prepared 3D scenes). It takes advantage of parallel data extraction, efficient 3D representation, and streaming protocols over TCP/IP.

Verfilmung von Multimediadaten in einem verteilten System

Es werden Motivation, Anforderungen und Realisierungsaspekte eines leistungsfähigen Systems für die Videoverfilmung von Bildsequenzen beschrieben. Dieses System wurde entwickelt, um die Visualisierung zeitlich veränderlicher bzw. allgemein parameterabhängiger Vorgänge z.B• als Ergebnis aufwendiger numerischer Simulationsrechnungen durch hochqualitative, echtzeitfähige Bewegtbild-Darstellung zu unterstützen. Die Produktion der hierzu verwendeten Video-Animationen läßt sich prinzipiell in die Schritte Bildgenerierung und Video-Aufzeichnung zerlegen; diese sind über ein Kommunikationsnetz komfortabel verteilbar.

Scalability Issues of In-Situ Visualization in Parallel Simulation of Unsteady Flows

Grand challenge applications of 3-dimensional high resolution unsteady computational fluid dynamics result in huge amounts of data. To avoid significant bottlenecks of the storage and communication resources, efficient techniques for data extraction and preprocessing at the source have been realized in the parallel, network-distributed process chain called DSVR. Here the 3D data extraction is implemented as a parallel library and can be done in-situ during the numerical simulations, which avoids the storage of raw data for visualization. In this work we present, evaluate, and compare three techniques of parallel in-situ pathline extraction in distributed memory architectures. The gain in parallel scalability is achieved by an innovative trade-off between parallelization of partial tasks and asynchronous execution of suited serialized tasks. It has been shown that advanced parallelization schemes increase the scalability significantly.