Semi-automated Csg Model-based Building Extraction from Photogrammetric Images

Using pre-defined models to extract spatial information of the building, called model-based building extraction, has been considered as a convincible approach to improve the existing photogrammetric techniques. However, there is still a bottleneck on the practical efficiency and accuracy. This paper proposed a semi-automated approach to extracting buildings from multiple aerial images as well as close-range images by a tailored least-squares model-image fitting (LSMIF) algorithm. Compare to the floating mark which is used by conventional photogrammetric techniques, we proposed a naval measuring tool of “floating models” for building extraction. The floating model is an abstract representation of the real object, which can be a point, a line segment, a surface plane, or a volumetric model. Each floating model is associated with a set of pose parameters and a set of shape parameters. By fitting the model to images, these parameters will not only reveal the location of the building but also describe the shape of the building. The semi-automated strategy for building extraction includes following five steps: (1) manually select an appropriate model, (2) manually locate and adjust the model for approximate fitting, (3) automatically compute the optimal fitting, (4) manually edit, and (5) compose the fitted models according to the Constructive Solid Geometry (CSG). An ad hoc computer program which was developed to implementing the proposed semi-automated approach was tested by extracting 10 selected buildings around the NCKU campus. The accuracy achieved was evaluated by comparing the roof corner coordinates with manual measurements.