This paper describes an algorithm which automatically creates an accurate and realistic reconstruction of buildings from high resolution, large-format digitized aerial stereo photographs. The system makes use of both reflectance and disparity data. Given a stereo pair of reflectance images of a scene containing buildings, the program automatically builds up a wireframe description of buildings and outputs a modified elevation map for the scene in which building edges are reconstructed accurately. A wide spectrum of computer vision techniques have been employed in this system- a fast stereo correlation technique; a robust, discontinuity preserving surface approximation algorithm to patch in uncorrelated areas; and knowledge based vision techniques to segment buildings from background and then reconstruct the building. A geometric model, in the form of a wing-edged data structure, is used to keep the wireframe while building up the structure. We also employ texture mapping to overlay the reflectance image back on the elevation data in order to provide a realistic display.