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Mobile Mapping is widely used for collecting large amounts of geo-referenced data. An important role plays sensor fusion, in order toevaluate multiple sensors such as laser scanner and cameras jointly. This requires to determine the relative orientation between sensors.Based on data of a <i>RIEGL</i> VMX-250 mobile mapping system equipped with two laser scanners, four optional cameras, and a highlyprecise GNSS/IMU system, we propose an approach to improve camera orientations. A manually determined orientation is used as aninitial approximation for matching a large number of points in optical images and the corresponding projected scan images. The searchspace of the point correspondences is reduced to skylines found in both the optical as well as the scan image. The skyline determinationis based on alpha shapes, the actual matching is done via an adapted ICP algorithm. The approximate values of the relative orientationare used as starting values for an iterative resection process. Outliers are removed at several stages of the process. Our approach is fullyautomatic and improves the camera orientation significantly

Skyline matching based camera orientation from images and mobile mapping point clouds