Building footprint database improvement for 3D reconstruction: A split and merge approach and its evaluation

We present a general framework to improve a vectorial building footprint database consisting of a set of 2D polygons. The aim of this improvement is to make the database more proper to subsequent 3D building reconstruction at a large scale. Each polygon is split into several simple polygons guided by a digital elevation model (DEM). We say that this segmentation is vectorial as we produce segmentations that intrinsically have simple polygonal shapes, instead of doing a raster segmentation of the DEM within the polygon then trying to simplify it in a vectorization step. The method is based on a Mumford and Shah like energy functional characterizing the quality of the segmentation. We simplify the problem by imposing that the segmentation edges have directions present in the input polygon over which the DEM is defined. We evaluate the validity of the proposed method on a very large dataset and discuss its pros and cons based on this evaluation.