Abstract
Point cloud is a product of laser scanning (terrestrial/airborne) or it can be derived from automatic image matching. Both techniques are very modern and progressive methods of non-selective collection of spatial data. The representation of buildings through point cloud is not appropriate for many applications. Handling with a set of data points, covering large areas is also very hardware consuming. For these reasons, it is suitable to represent individual buildings as spatial objects, called 3D models. This paper is a review of fully automatic generation of 3D building models from point clouds. It compares the solutions of various academic institutes and analyzes current commercial software products that process this task. In this work, data point clouds collected by airborne laser scanning will be used as an input. A major influence on the generation of 3D building models have the density and quality of the point cloud, which are determined by scanning parameters. For this reason, various input datasets will be tested.
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Hron, V., Halounová, L. (2015). Automatic Generation of 3D Building Models from Point Clouds. In: Ivan, I., Benenson, I., Jiang, B., Horák, J., Haworth, J., Inspektor, T. (eds) Geoinformatics for Intelligent Transportation. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-11463-7_8
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DOI: https://doi.org/10.1007/978-3-319-11463-7_8
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