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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.
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.
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.
A generic approach to describing shape and topography of arbitrary objects is presented, using linguistic variables to combine different features in one fuzzy descriptor. Although the origin of the method lies in molecular visualization and drug design, it can be applied in principle to any surface represented by a polygon mesh. Two approaches to shape description are presented that both lead to linguistic variables that can be used for surface segmentation by means of shape: One approach is based on the calculation of canonical curvatures, the other describes the "embeddedness" of a surface area related to the overall geometry of a 3D object.
The objective of the presented approach is to develop a 3D-reconstruction method for micro organisms from sequences of microscopic images by varying the level-of-focus. The approach is limited to translucent silicatebased marine and freshwater organisms (e.g. radiolarians). The proposed 3D-reconstruction method exploits the connectivity of similarly oriented and spatially adjacent edge elements in consecutive image layers. This yields a 3D-mesh representing the global shape of the objects together with details of the inner structure. Possible applications can be found in comparative morphology or hydrobiology, where e.g. deficiencies in growth and structure during incubation in toxic water or gravity effects on metabolism have to be determined.