CHARACTERIZING BUILDING FACADES FROM VERTICAL AERIAL IMAGES

Information is being extracted from vertical aerial photography and various data products for an efficient interpretation of terrain objects. Our focus lies on characterizing individual properties as accurately as possible, using aerial imagery. We want to determine the size of buildings, their number of floors, the number and size of windows, the existence of impervious surfaces, status of vegetation, roof shapes with chimneys and sky lights etc. To achieve robust results it is very important to incorporate all data that a set of images can offer. A key aspect therefore is the inclusion of the 3rd dimension when interpreting facade images and to deal with the different imaging angles when interpreting the details of building facades from vertical aerial photography. This paper first addresses the question which incidence angles are sufficiently large to get useful results. And secondly it describes a plane sweep algorithm to detect 3D facade objects such as eaves, balconies and porches. We expect to achieve an enhanced quality of the floor counts and window detection results. The topics are closely related since one first needs to understand which facade images have been taken under an angle that is too small, so that the facades excessively distorted. Second, the plane sweep algorithm needs images with as small a distortion as possible, and given a high degree of overlaps, one will need to prune-down the set of images actually used.