Scene Analysis in Urban Areas Using a Knowledge-based Interpretation System

In this contribution the way algorithms for object detection in urban areas are integrated into the knowledge-based image interpretation system GeoAIDA is described. Generic scene models are used for object detection in settlement areas, whereas the implementation of the respective algorithms is a collection of stand-alone-operators. With GeoAIDA a system is available which uses these operators in the first phase (model-driven, top-down) in order to generate hypotheses for objects in the scene. In the second phase (data-driven, bottom-up) the hypotheses are further processed using structural knowledge about the scene. Here, detected buildings are grouped using the Relative Neighborhood Graph. An example shows that the combination of low-level image operators and high-level grouping operators leads to enhanced scene analysis results.