Automatic description of complex buildings with multiple images

Abstract

3-D building detection and description is a practical application of 3-D object description, a key task of computer vision. We present an approach to detecting and describing buildings of polygonal rooftops by using multiple, overlapping images of the scene. First, 3-D features are generated by using multiple images, and rooftop hypotheses are generated by neighborhood searches on those features. For robust generation of 3-D features, we present a probabilistic approach to address the epipolar alignment problem in line matching. Image-derived unedited elevation data is used to assist feature matching, and to generate rough cues of the presence of 3-D structures. These cues help reduce the search space significantly. Experimental results are shown on some complex buildings.