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 top-down robust surface ttting 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 diierent building roof classes, including at single level, at multi-leveled, peaked, and curved rooftops. The algorithm is applicable to range data that may have been collected from several diierent range sensor types. We demonstrate reconstructions of diier-ent 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-of-attention area derived from the monocular optical image .