Abstract
Automatic identification and extraction of man-made objects from aerial images for cartographic purposes are currently the most challenging problems in photogrammetry. Automating the identification and extraction procedures can significantly improve the efficiency of photogrammetric tasks, such as map compilation, DEM and orthophoto generation and city modeling. This paper presents an approach for object extraction from large-scale aerial images. The approach comprises two key concepts: extraction is performed from the object view point, and objects are extracted semiautomatically. Integration of both concepts in a conventional, well-established photogrammetric procedure complies with the primary requirement of the mapping community, which is to have an efficient procedure, while maintaining the necessary accuracy and reliability. The paper presents the idea and the motivations, and discusses basic tools for extracting two types of common man-made objects: buildings and roads. Preliminary results are shown and discussed as well.
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