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This thesis deals with the development of an authoring system for modeling 3D environments with physical description. In contrast to creating scenes in other common modeling tools, one can now compute and describe physical entities of a scene additional to the usual geometry. It is very important for those authoring systems to be extendable and customizable for specific requirement of the user. The focus lies on developing simple program architecture, which is easy to extend and to modify.
The present work starts with an introduction of methods for three-dimensional curve skeletonization. Different kinds of historic and recent skeletonization approaches are analysed in detail. Later on, a state-of-the-art skeletonization algorithm is introduced. This algorithm deals as a basis for the own approach presented subsequently. After the description and definition of a new method improving the state-of-the-art algorithm, experiments are conducted to get appraisable results. Next, a ground truth is described which has been set up manually by humans. The human similarity evaluations are compared with the results of the automatic computer-based similarity measures provided by the own approach. For this comparison, standard evaluation criteria from the field of information retrieval have been used.
There are a few systems high and low-cost ones for gaze tracking. Normally low-cost systems go in hand with low-resolution cameras. Here the image quality is poor, so the algorithms for detecting the gaze have to work more precisely. But how to test and analyse them correctly, when there is a bad image quality and no reference point known? The idea of this work is, to generate synthetic eye images, where the reference points are known, because they are mainly manually set and then to test and analyse the algorithms with these synthetic images. By switching on features like gaussian noise or a second glint-like reflection point, it is possible to stepwise approximate the synthetic images close to reality. In fact the experiments will lead to an improvement of the algorithms used in a low-resolution system environment.