  This paper aims to address the problem of detecting buildings from remote
sensing images with very high resolution (VHR). Inspired by the observation
that buildings are always more distinguishable in geometries than in texture or
spectral, we propose a new geometric building index (GBI) for accurate building
detection, which relies on the geometric saliency of building structures. The
geometric saliency of buildings is derived from a mid-level geometric
representations based on meaningful junctions that can locally describe
anisotropic geometrical structures of images. The resulting GBI is measured by
integrating the derived geometric saliency of buildings. Experiments on three
public datasets demonstrate that the proposed GBI achieves very promising
performance, and meanwhile shows impressive generalization capability.
