Operating and managing single three-dimensional building model individually are critical in the application of oblique photography models. However, these models are usually complete and continuous, and the single three-dimensional building model in these models cannot be managed individually. Generally, achieving a single three-dimensional building model requires a human-computer interaction to determine the cutting range, but this process is time-consuming and inefficient. To overcome this problem, this study proposed a new method for automatically achieving single three-dimensional building model without the need for human-computer interaction. First, the point clouds of an oblique photography model are divided into virtual grids, and the point clouds in each virtual grid are seen as a whole. In this way, the number of point clouds involved in the calculation is reduced, thereby improving computing efficiency. Second, the point clouds of a building facade are extracted by setting the height difference. By comparing the height difference between the highest point and the lowest point of the grid with height difference threshold, all point clouds in the grid that do not meet the requirements are eliminated. Third, the point clouds of the building facade are classified, and the contour line is extracted by the classified point clouds. Finally, the single three-dimensional building model is achieved by reconstructing the triangles that intersect with the extracted contour line. Experimental results show that the proposed method can effectively achieve single bodies automatically from an oblique photography building model. This method is then useful for achieving single three-dimensional building model from massive oblique photography data.
A New Method of Achieving Single Three-Dimensional Building Model Automatically Based on Oblique Photography Data