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With modern 3D laser scanners we can acquire a large amount of 3D data in only a few minutes. This technology results in agrowing number of applications ranging from the digitalization of historical artifacts to facial authentication. The modeling processdemands a lot of time and work (Tim Volodine, 2007). In comparison with the other two stages, the acquisition and the registration,the degree of automation of the modeling stage is almost zero. In this paper, we propose a new surface reconstruction technique forbuildings to process the data obtained by a 3D laser scanner. These data are called a point cloud which is a collection of pointssampled from the surface of a 3D object. Such a point cloud can consist of millions of points. In order to work more efficiently, weworked with simplified models which contain less points and so less details than a point cloud obtained in situ. The goal of thisstudy was to facilitate the modeling process of a building starting from 3D laser scanner data. In order to do this, we wrote twoscripts for Rhinoceros 5.0 based on intelligent algorithms. The first script finds the exterior outline of a building. With a minimum ofhuman interaction, there is a thin box drawn around the surface of a wall. This box is able to rotate 360° around an axis in a corner ofthe wall in search for the points of other walls. In this way we can eliminate noise points. These are unwanted or irrelevant points. Ifthere is an angled roof, the box can also turn around the edge of the wall and the roof. With the different positions of the box we cancalculate the exterior outline. The second script draws the interior outline in a surface of a building. By interior outline we mean theoutline of the openings like windows or doors. This script is based on the distances between the points and vector characteristics.Two consecutive points with a relative big distance will form the outline of an opening. Once those points are found, the interioroutline can be drawn. The designed scripts are able to ensure for simple point clouds: the elimination of almost all noise points andthe reconstruction of a CAD model

Automatic Reconstruction of 3D Building Models from Terrestrial Laser Scanner Data