Visualization of urban environments
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Modeling and visualization of large geometric environments is a popular research area in computer graphics. In this dissertation, a framework for modeling and stereoscopic visualization of large and complex urban environments is presented. The occlusion culling and view-frustum culling is performed to eliminate most of the geometry that do not contribute to the user’s final view. For the occlusion culling process, the shrinking method is employed but performed using a novel Minkowski-difference-based approach. In order to represent partial visibility, a novel building representation method, called the slice-wise representation is developed. This method is able to represent the preprocessed partial visibility with huge reductions in the storage requirement. The resultant visibility list is rendered using a graphics-processing-unit-based algorithm, which perfectly fits into the proposed slice-wise representation. The stereoscopic visualization depends on the calculated eye positions during walkthrough and the visibility lists for both eyes are determined using the preprocessed occlusion information. The view-frustum culling operation is performed once instead of two for both eyes. The proposed algorithms were implemented on personal computers. Performance experiments show that, the proposed occlusion culling method and the usage of the slice-wise representation increase the frame rate performance by 81 %; the graphics-processing-unit-based display algorithm increases it by an additional 315 % and decrease the storage requirement by 97 % as compared to occlusion culling using building-level granularity and not using the graphics hardware. We show that, a smooth and real-time visualization of large and complex urban environments can be achieved by using the proposed framework.