Semiautomatic building extraction from stereo image pair based on lines grouping and least squares matching

The paper presents a general paradigm of semiautomatic building extraction from aerial stereo image pair. In the semiautomatic extraction system, the building model is defined by selected roof type through human-machine interface and input the approximation of area where the extracted building exists. Then under the knowledge of the roof type, low-level and mid-level processing including edge detection, straight line segments extraction and line segments grouping are used to establish the initial geometrical model of the roof-top. However, the initial geometrical model is not so accurate in geometry. To attain accurate results, a general least squares adjustment integrating the linear templates matching model with geometrical constraints in object-space is applied to refine the initial geometrical model. The adjustment model integrating the straight edge pattern and 3D constraints together is a well-studied optimal and anti-noise method. After gaining proper initial values, this adjustment model can flexibly process extraction of kinds of roof types by changing or assembling the geometrical constraints in object-space.