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：2012
卷号：XXXIX-B3
页码：41-46
DOI：10.5194/isprsarchives-XXXIX-B3-41-2012
出版社：Copernicus Publications
摘要：Automatically detection, extraction and re-construction of 3D building modelling are difficult yet potentially high-payoff challenges for photogrammetric applications. Solution usually requires integrating various sources, including LIDAR, imagery, and digital surface models (DSM). However, highly automated and robust geometric modelling remains unsolved. We will present a 2D modelling technique which represents a building’s outline in an as-is way. It gives visually accurate corners and lines for buildings. Aerial remotely sensed imagery and a DSM are used to detect and segment building masks. A refining footprint modelling is implemented through line modelling, edge refining, and segment merging and generating. A district grouping based main orientation algorithm is proposed. This approach has the ability of successive improvement, moving from a prototype to a subtle end product. Experiments with Japanese data show that the models generated automatically fit the manual models very well
