3D Building Adjustment Using Planar Half-Space Regularities
The automatic reconstruction of 3D building models with complex roof shapes is still an active area of research. In this paper we present a novel approach for local and global regularization rules that integrate building knowledge to improve both the shape of the reconstructed building models and their accuracy. These rules are defined for the planar half-space representation of our models and emphasize the presence of symmetries, co-planarity, parallelism, and orthogonality. By not adjusting building features separately (e.g. ridges, eaves, etc.) we are able to handle more than one feature at a time without considering dependencies between different features. Additionally, we present a new method for reconstructing buildings with concave outlines using half-spaces that avoids the need to partition the models into smaller convex parts. We present both extensions in the context of a fully automatic feature-driven 3D building reconstruction approach where the whole process is suited for processing large urban areas with complex building roofs.