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International Institute for Geo-Information Science and Earth Observation, Hengelosestraat 99, P.O. Box 6, 7500 AA Enschede, The Netherlands





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Abstract With the increasing point densities provided by airborne laser scanner ALS data the requirements on derived products also increase. One major application of ALS data is to provide input for 3D city models. Modeling of roof faces, 3D road and terrain surfaces can partially be done in an automated manner, although many such approaches are still in a development stage. Problems in automatic building reconstruction lie in the dynamic area between assumptions and reality. Not every object in the data appears as the algorithm expects. Challenges are to detect areas that cannot be reconstructed automatically. This paper describes our contribution to the field of building reconstruction by proposing a target based graph matching approach that can handle both complete and incomplete laser data. Match results describe which target objects appear topologically in the data. Complete match results can be reconstructed in an automated manner. Quality parameters store information on how the model fits to the input data and which data has not been used. Areas where laser data only partly matches with target objects are detected automatically. Four datasets are analyzed in order to describe the quality of the automatically reconstructed roofs, and to point out the reasons why segments are left out from the automatic reconstruction. The reasons why these areas are left out include lack of data information and limitations of our initial target objects. Potential improvement to our approach is to include likelihood functions to the existence of topological relations. View Full-Text

Keywords: building reconstruction; laser scanner data; target graph matching; incomplete data building reconstruction; laser scanner data; target graph matching; incomplete data





Autor: Sander Oude Elberink * and George Vosselman

Fuente: http://mdpi.com/



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