3D visibility analysis plays a key role in urban planning for assessing the visual impact of proposed buildings on the cityscape. A call for proposals typically yields around 30 candidate buildings that need to be evaluated with respect to selected viewpoints. Current visibility analysis methods are very time-consuming and limited to a small number of viewpoints. Further, analysts neither have measures to evaluate candidates quantitatively, nor to compare them efficiently. The primary contribution of this work is the design study of Vis-A-Ware, a visualization system to qualitatively and quantitatively evaluate, rank, and compare visibility data of candidate buildings with respect to a large number of viewpoints. Vis-A-Ware features a 3D spatial view of an urban scene and non-spatial views of data derived from visibility evaluations, which are tightly integrated by linked interaction. To enable a quantitative evaluation we developed four metrics in accordance with experts from urban planning. We illustrate the applicability of Vis-A-Ware on the basis of a use case scenario and present results from informal feedback sessions with domain experts from urban planning and development. This feedback suggests that Vis-A-Ware is a valuable tool for visibility analysis allowing analysts to answer complex questions more efficiently and objectively.
In order to provide a highly performant rendering system while maintaining a scene graph structure with a high level of abstraction, we introduce improved rendering caches, that can be updated incrementally without any scene graph traversal. The basis of this novel system is the use of a dependency graph, that can be synthesized from the scene graph and links all sources of changes to the affected parts of rendering caches. By using and extending concepts from incremental computation we minimize the computational overhead for performing the necessary updates due to changes in any inputs. This makes it possible to provide a high-level semantic scene graph, while retaining the opportunity to apply a number of known optimizations to the rendering caches even for dynamic scenes. Our evaluation shows that the resulting rendering system is highly competitive and provides good rendering performance for scenes ranging from completely static geometry all the way to completely dynamic geometry.
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