Prof. Dr. André Hinkenjann
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- Virtual Reality (3)
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Most VE-frameworks try to support many different input and output devices. They do not concentrate so much on the rendering because this is tradi- tionally done by graphics workstation. In this short paper we present a modern VE framework that has a small kernel and is able to use different renderers. This includes sound renderers, physics renderers and software based graphics renderers. While our VE framework, named basho is still under development we have an alpha version running under Linux and MacOS X.
We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method for stochastic global illumination rendering. Based on the CPU implementation of the original algorithm, we present a naive GPU implementation and the necessary optimization steps. Eventually, we show that our optimizations increase the performance of RHF by two orders of magnitude when compared to the original CPU implementation and one order of magnitude compared to the naive GPU implementation. We show how the quality for identical rendering times relates to unfiltered path tracing and how much time is needed to achieve identical quality when compared to an unfiltered path traced result. Finally, we summarize our work and describe possible future applications and research based on this.
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.
This presentation gives an overview of current research in the area of high quality rendering and visualization at the Institute of Visual Computing (IVC). Our research facility has some unique software and hardware installations of which we will describe a large, ultra- high resolution (72 megapixel) video wall in this presentation.
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.
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.
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.
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.
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.
Real-Time Simulation of Camera Errors and Their Effect on Some Basic Robotic Vision Algorithms
(2013)
Robust Indoor Localization Using Optimal Fusion Filter For Sensors And Map Layout Information
(2014)
Application performance improvements through VM parameter modification after runtime analysis
(2013)
We present the extensible post processing framework GrIP, usable for experimenting with screen space-based graphics algorithms in arbitrary applications. The user can easily implement new ideas as well as add known operators as components to existing ones. Through a well-defined interface, operators are realized as plugins that are loaded at run-time. Operators can be combined by defining a post processing graph (PPG) using a specific XML-format where nodes are the operators and edges define their dependencies. User-modifiable parameters can be manipulated through an automatically generated GUI. In this paper we describe our approach, show some example effects and give performance numbers for some of them.
We present a graph-based framework for post processing filters, called GrIP, providing the possibility of arranging and connecting compatible filters in a directed, acyclic graph for realtime image manipulation. This means that the construction of whole filter graphs is possible through an external interface, avoiding the necessity of a recompilation cycle after changes in post processing. Filter graphs are implemented as XML files containing a collection of filter nodes with their parameters as well as linkage (dependency) information. Implemented methods include (but are not restricted to) depth of field, depth darkening and an implementation of screen space shadows, all applicable in real-time, with manipulable parameterizations.