With deep learning becoming a more prominent approach for automatic classification of three-dimensional point cloud data, a key bottleneck is the amount of high quality training data, especially when
C3DO is a 3D point cloud reconstruction of concrete buildings, with an emphasis on damaged façades. It was generated by reconstructing a 4.5-acre region in the Disaster City® facility using a Terrestr
Point cloud generated from photos taken from an UAV platform using photo-stereography techniques. Nominal pixel size is 5 cm. The points contain a value for color, from RGB...
