CONSISTENT ESTIMATION OF BUILDING PARAMETERS CONSIDERING GEOMETRIC REGULARITIES BY SOFT CONSTRAINTS

This paper describes a model for the consistent estimation of building parameters that is a part of a method for automatic building reconstruction from airborne laser scanner (ALS) data. The adjustment model considers the building topology by GESTALT observations, i.e. observations of points being situated in planes. Geometric regularities are considered by “soft constraints” linking neighbouring vertices or planes. Robust estimation can be used to eliminate false hypotheses about such geometric regularities. Sensor data provide the observations to determine the parameters of the building planes. The adjustment model can handle a variety of sensor data and is shown to be also applicable for semi-automatic building reconstruction from image and/or ALS data. A test project is presented in order to evaluate the accuracy that can be achieved using our technique for building reconstruction from ALS data, along with the improvement caused by adjustment and regularisation. The planimetric accuracy of the building walls is in the range of or better than the ALS point distance, whereas the height accuracy is in the range of a few centimetres. Regularisation was found to improve the planimetric accuracy by 545%.