Abstract. In this paper we present an eicient modeling framework
for large scale urban scenes. Taking surface meshes derived from multiview-stereo systems as input, our algorithm outputs simpliied models
with semantics at diferent levels of detail (LODs). Our key observation
is that urban building is usually composed of planar roof tops connected
with vertical walls. There are two major steps in our framework: segmentation and building modeling. The scene is irst segmented into four
classes with a Markov random ield combining height and image features. In the following modeling step, various 2D line segments sketching
the roof boundaries are detected and slice the plane into faces. Through
assigning each face with a roof plane, the inal model is constructed by
extruding the faces to the corresponding planes. By combining geometric
and appearance cues together, the proposed method is robust and fast
compared to the state-of-the-art algorithms.