Using laser scanning is well suited to the task of deformation monitoring. The sensor class allows a fast, high resolution and dense acquisition of 3D information. However, to detect deformations and changes in multi-temporal point clouds is difficult as no discrete points are measured and only changes in line of sight can be clearly detected as distance variation. Image analysis techniques, in contrast, are very sensible for identifying displacements in transverse direction. Hence, a combined acquisition and analysis of point cloud and image data complement each other very well.
We will present existing concepts as well as new approaches for a fused analysis of both sensor datasets manly based on deformation monitoring but also to be used in other applications areas. It will be shown that the sensor fusion will give additional information of the measured object and thus facilitate further data interpretation.
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Using laser scanning is well suited to the task of deformation monitoring. The sensor class allows a fast, high resolution and dense acquisition of 3D information. However, to detect deformations and changes in multi-temporal point clouds is difficult as no discrete points are measured and only changes in line of sight can be clearly detected as distance variation. Image analysis techniques, in contrast, are very sensible for identifying displacements in transverse direction. Hence, a combined a...
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