Building Reconstruction from Optical and Range Images

A technique is introduced for extracting and reconstructing a wide class of building types from a registered range image and optical image. An attentional focus stage, followed by model indexing, allows topdown robust surface fittting to reconstruct the 3D nature of the buildings in the data. Because of the effectiveness of model selection, top-down processing of noisy range data still succeeds and the algorithm is capable of detecting and reconstructing several different building roof classes, including flat single level, flat multi-leveled, peaked, and curved rooftops. The algorithm is applicable to range data that may have been collected from several different range sensor types. We demonstrate reconstructions of different buildings classes in the presence of large amounts of noise. Our results underline the usefuless of range data when processed in the context of a focus-ofattention area derived from the monocular optical image. 1 Introduction We introduce a solution to the prob..