期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 3 B
页码：63-66
出版社：Copernicus Publications
摘要：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 pro- cessed 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
