Automatic 3D-reconstruction of buildings using highly resolving video sequences

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We propose a fully automated prototype system to refine building models of an urban 3D GIS using terrestrial image data. Digital video sequences contain a high potential for such photogrammetric applications which is presently not fully used. Projective geometry provides an effective mathematical framework to obtain geometrically precise information from partially calibrated cameras with varying parameters. Presently, it is being combined with object reconstruction methods improving its performance in automation. The main novelty is an intensive Integration of spatial and temporal image matching as weil as geometric and reflectance information. The photogrammetric model is partially reconstructed from the neighboring images of a trifocal camera system, partially from the preceding and following images of the video sequence. The observed buildings consist of planes, polyhedrons and freely formed surfaces. We use generic models of surface assemblies together with particular scene constraints to extract, align and classify the polygonal primitives. Additionally, the knowledge-driven object extraction is used to support the Image orientation and probably to replace control information. The approach is designed for off-line processing of recorded digital video, because the computational requirements to deal with hand-held markerless video streams exceed the capabilities of today real-time systems. We want to develop a mathematically homogeneous framework which incorporates photogrammetric model generation, temporal tracking, and reflectance analysis as weil as object extraction and classification. Such systematic model generation from several trifocal views gives a digital video system its full potential.