Data originating from nadir airborne laser scanning (ALS) of urbanregions is commonly used as a basis for 3D city modeling. These dataare lacking information concerning the facades of buildings, whereasstructures of roofs are missing in terrestrial laser data. To closethis gap, the scene can be captured from several directions withan oblique looking airborne laser scanner, requiring an accurateco-registration of different data sets. This paper aims at automaticfiltering of 3D points recorded at an urban region and subsequentco-registration of multiple data sets on the basis of detected rooftops.Instead of applying a standard Iterative Closest Point (ICP) approach,we identify corresponding planar structures in the data sets. Twovariations of a method for automatic co-registration are proposedand tested with four ALS data sets showing the urban test area TUM(Technische Universität München) from different views.     «

Data originating from nadir airborne laser scanning (ALS) of urbanregions is commonly used as a basis for 3D city modeling. These dataare lacking information concerning the facades of buildings, whereasstructures of roofs are missing in terrestrial laser data. To closethis gap, the scene can be captured from several directions withan oblique looking airborne laser scanner, requiring an accurateco-registration of different data sets. This paper aims at automaticfiltering of 3D points recorded at...     »