期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2000
卷号：XXXIII Part B3(/1+2)
页码：381-388
出版社：Copernicus Publications
摘要：The reconstruction of complex surfaces in . 3 is still a rather uncovered area in the field of Photogrammetry and Geod- esy. Whereas other disciplines, such as CAD, Computer Sciences, Medicine, Geology and others, have developed methods, suitable for their special needs and applications, no satisfactory solutions exist for natural topographic sur- faces. This work offers an approach for the reconstruction of 3D-surfaces, designed to fulfil the requirements of Photo- grammetry and Geodesy. The main idea is the use of as much knowledge as possible for the reconstruction of the surface from the digitised points. This knowledge includes constraints and assumptions about the original surface (e.g. smoothness of the surface), about data sampling (specific characteristics of different data sources) and about additional information (e.g. measured lines). The knowledge is splitted into elementary and autonomous statements, so-called rules. These rules assign evi- dences in favour or against the shape of the reconstructed surface. The surface is modelled with a triangular mesh, which offers the necessary flexibility when modelling natural surfaces. To find the 3D-triangulation a tetrahedral tessellation of the data is computed in a first step. The main reason is the reduction of the amount of possible triangles. From the triangles of this tessellation the ones belonging to the surface are extracted. For this purpose the above rules are applied. The inference of a decision, whether a triangle belongs to the surface or not, uses standard techniques from the field of Artificial Intelligence and Probabilistic Reasoning
