Semantic visualization of 3D urban environments

The purpose of this work is the semantic visualization of complex 3D city models containing numerous dynamic entities, as well as performing interactive semantic walkthroughs and flights without predefined paths. This is achieved by using a 3D multilayer scene graph that integrates geometric and semantic information as well as by the performance of efficient geometric and what we call semantic view culling. The proposed semantic-geometric scene graph is a 3D structure composed of several layers which is suitable for visualizing geometric data with semantic meaning while the user is navigating inside the 3D city model. BqR-Tree is the data structure specially developed for the geometric layer for the purpose of speeding up rendering time in urban scenes. It is an improved R-Tree data structure based on a quadtree spatial partitioning which improves the rendering speed of the usual R-trees when view culling is implemented in urban scenes. The BqR-Tree is defined by considering the city block as the basic and logical unit. The advantage of the block as opposed to the traditional unit, the building, is that it is easily identified regardless of the data source format, and allows inclusion of mobile and semantic elements in a natural way. The usefulness of the 3D scene graph has been tested with low structured data, which makes its application appropriate to almost all city data containing not only static but dynamic elements as well.