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Interactive rendering of complex models has many applications in the Virtual Reality Continuum. The oil&gas industry uses interactive visualizations of huge seismic data sets to evaluate and plan drilling operations. The automotive industry evaluates designs based on very detailed models. Unfortunately, many of these very complex geometric models cannot be displayed with interactive frame rates on graphics workstations. This is due to the limited scalability of their graphics performance. Recently there is a trend to use networked standard PCs to solve this problem. Care must be taken however, because of nonexistent shared memory with clustered PCs. All data and commands have to be sent across the network. It turns out that the removal of the network bottleneck is a challenging problem to solve in this context.In this article we present some approaches for network aware parallel rendering on commodity hardware. These strategies are technological as well as algorithmic solutions.
The Render Cache [1,2] allows the interactive display of very large scenes, rendered with complex global illumination models, by decoupling camera movement from the costly scene sampling process. In this paper, the distributed execution of the individual components of the Render Cache on a PC cluster is shown to be a viable alternative to the shared memory implementation.As the processing power of an entire node can be dedicated to a single component, more advanced algorithms may be examined. Modular functional units also lead to increased flexibility, useful in research as well as industrial applications.We introduce a new strategy for view-driven scene sampling, as well as support for multiple camera viewpoints generated from the same cache. Stereo display and a CAVE multi-camera setup have been implemented.The use of the highly portable and inter-operable CORBA networking API simplifies the integration of most existing pixel-based renderers. So far, three renderers (C++ and Java) have been adapted to function within our framework.
This paper describes the work done at our Lab to improve visual and other quality of Virtual Environments. To be able to achieve better quality we built a new Virtual Environments framework called basho. basho is a renderer independent VE framework. Although renderers are not limited to graphics renderers we first concentrated on improving visual quality. Independence is gained from designing basho to have a small kernel and several plug-ins.
"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.
In this paper we present an approach to efficiently trace single rays on the Cell Processor, instead of using ray packets. To benefit from the performance of this processor, a data structure is chosen which allows traversal without excessive accesses to main memory. Together with careful optimization for SIMD processing, a performance comparable to a packet based ray tracer, running on the same hardware, is achieved. In special cases, when the coherency of the traced rays get very low, it even outperforms the packet based approach.
Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real‐time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel (high dynamic range, wider color gamut/fidelity), increasing refresh rates (better motion depiction), and an increasing number of displayed views per pixel (stereo, multi‐view, all the way to holographic or lightfield displays). These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.
Large, high-resolution displays demonstrated their effectiveness in lab settings for cognitively demanding tasks in single user and collaborative scenarios. The effectiveness is mostly reached through inherent displays' properties - large display real estate and high resolution - that allow for visualization of complex datasets, and support of group work and embodied interaction. To raise users' efficiency, however, more sophisticated user support in the form of advanced user interfaces might be needed. For that we need profound understanding of how large, tiled displays impact users work and behavior. We need to extract behavioral patterns for different tasks and data types. This paper reports on study results of how users, while working collaboratively, process spatially fixed items on large, tiled displays. The results revealed a recurrent pattern showing that users prefer to process documents column wise rather than row wise or erratic.
In western societies a huge percentage of the population suffers from some kind of back pain at least once in their life. There are several approaches addressing back pain by postural modifications. Postural training and activity can be tracked by various wearable devices most of which are based on accelerometers. We present research on the accuracy of accelerometer-based posture measurements. To this end, we took simultaneous recordings using an optical motion capture system and a system consisting of five accelerometers in three different settings: On a test robot, in a template, and on actual human backs. We compare the accelerometer-based spine curve reconstruction against the motion capture data. Results show that tilt values from the accelerometers are captured highly accurate, and the spine curve reconstruction works well.
Robust Indoor Localization Using Optimal Fusion Filter For Sensors And Map Layout Information
(2014)
Current computer architectures are multi-threaded and make use of multiple CPU cores. Most garbage collections policies for the Java Virtual Machine include a stop-the-world phase, which means that all threads are suspended. A considerable portion of the execution time of Java programs is spent in these stop-the-world garbage collections. To improve this behavior, a thread-local allocation and garbage collection that only affects single threads, has been proposed. Unfortunately, only objects that are not accessible by other threads ("do not escape") are eligible for this kind of allocation. It is therefore necessary to reliably predict the escaping of objects. The work presented in this paper analyzes the escaping of objects based on the line of code (program counter – PC) the object was allocated at. The results show that on average 60-80% of the objects do not escape and can therefore be locally allocated.
Improving data acquisition techniques and rising computational power keep producing more and larger data sets that need to be analyzed. These data sets usually do not fit into a GPU's memory. To interactively visualize such data with direct volume rendering, sophisticated techniques for problem domain decomposition, memory management and rendering have to be used. The volume renderer Volt is used to show how CUDA is efficiently utilised to manage the volume data and a GPU's memory with the aim of low opacity volume renderings of large volumes at interactive frame rates.
This article describes an approach to rapidly prototype the parameters of a Java application run on the IBM J9 Virtual Machine in order to improve its performance. It works by analyzing VM output and searching for behavioral patterns. These patterns are matched against a list of known patterns for which rules exist that specify how to adapt the VM to a given application. Adapting the application is done by adding parameters and changing existing ones. The process is fully automated and carried out by a toolkit. The toolkit iteratively cycles through multiple possible parameter sets, benchmarks them and proposes the best alternative to the user. The user can, without any prior knowledge about the Java application or the VM improve the performance of the deployed application and quickly cycle through a multitude of different settings to benchmark them. When tested with the representative benchmarks, improvements of up to 150% were achieved.
In contrast to projection-based systems, large, high resolution multi-display systems offer a high pixel density on a large visualization area. This enables users to step up to the displays and see a small but highly detailed area. If the users move back a few steps they don't perceive details at pixel level but will instead get an overview of the whole visualization. Rendering techniques for design evaluation and review or for visualizing large volume data (e.g. Big Data applications) 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 (VDB) rendering technique renders the user's central field of view in high quality whereas the surrounding is rendered with a level-of-detail approach depending on the distance to the user's central field of view. This approach mimics the physiology of the human eye and conserves the advantage of highly detailed information when standing close to the multi-display system as well as the general overview of the whole scene. In this paper we propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.