Knowledge-based building reconstruction from terrestrial video sequences
The paper presents an automatic method for the reconstruction of building models from video image sequences. These videos may be recorded using a hand-held camera or a camera mounted on a moving car. Such terrestrial video sequences are economic and flexible. Presenting buildings as geometric modelsrather than for instance a representation from a simple meshing of 3D pointsenables one to perform a wide range of analyses. However, sparse 3D points and 3D edges do not contain topological relations. Therefore, integrating building structure knowledge into the reconstruction steps plays an important role in our method. First, some rules are applied to reasonably group the extracted features. Then, a suitable outline and normal direction are specified for each surface patch. Based on these surface patches, a hybrid model- and data-driven method is used to recover a building model from both the extracted surface patches and hypothesized parts. Using the building structure knowledge leads to a simple and fast reconstruction method, and also enables one to obtain the main structures of buildings. The results show that this method correctly sets up topological relationships between generated surface patches and also obtains reasonable structure models in occluded areas. Therefore, the reconstructed models satisfy requirements for both visualization and analysis.
knowledge reconstruction image sequence faade