FILTERING REFLECTED POINTS IN A 3D LIDAR SCAN BY JOINT EVALUATION OF LIDAR DATA AND IMAGE DATA WITH A REFLECTION POINT CLASSIFIER

3D LiDAR scanning for generating a 3D point cloud of an environment, e.g. for surveying a construction side or for building surveying. Data points within the 3D laser scan data originating from multiple reflections within the environment, referred to as reflection points, are automatically identified and removed from the point cloud, by making use of a joined analysis of paired 3D laser scan data and image data captured with a measuring device. Points belonging to objects which appear in the 3D scan data but do not appear in the image data are classified as reflection points. Detection of the reflection points is provided by a reflection point classifier, which is trained to find semantic similarity and dissimilarity of 3D laser scan data and image data.