Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Classification of Models and Strategies <s> The Ascender system acquires, extends, and refines 3D geometric site models from calibrated aerial imagery. To acquire a new site model, an automated building detector is run on one image to hypothesize potential building rooftops. Supporting evidence is located in other images via epipolar line segment matching in constrained search regions. The precise 3D shape and location of each building is then determined by multiimage triangulation under geometric constraints of 3D orthogonality, parallelness, colinearity, and coplanarity of lines and surfaces. Projective mapping of image intensity information onto these polyhedral building models results in a realistic site model that can be rendered using virtual “fly-through” graphics. As new images of the site become available, model extension and refinement procedures are performed to add previously unseen buildings and to improve the geometric accuracy of the existing 3D building models. In this way, the system gradually accumulates evidence over time to make the site model more complete and more accurate. An extensive performance evaluation of component algorithms and the full system has been carried out. Two-dimensional building detection accuracy, as well as accuracy of the three-dimensional building reconstruction, are presented for a representative data set. <s> BIB001 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Classification of Models and Strategies <s> This paper addresses two major issues: 3-D building reconstruction and the role of color attributes and similarity grouping. We present ARUBA, a general framework for automated 3-D building reconstruction from multiple color aerial images. After highlighting the strategy and concisely describing the framework and its 2-D and 3-D processing modules, we will evaluate the reconstructed roofs with respect to accurate reference data. The second part of the paper shows that geometry, although important, should not be the only source of information exploited in the reconstruction process. The main objectives are to demonstrate that (1) color is a very important cue in reconstructing a general class of objects, (2) it is crucial to retain all information during the entire processing chain, (3) a general class of objects parts can be efficiently extracted by grouping edges and lines by means of similarity, and (4) a mutual interaction between 2-D and 3-D processing is important. <s> BIB002
The classification of the different approaches regarding their models and strategies is done in two ways: First, by comparing it with the ultimate goal, the extraction of objects for GIS databases or for site models, and second, by showing the most sophisticated approaches. Compared to the ultimate goal, the results based on the models and strategies of all presented approaches are for images of different characteristics and complex contents far from being useful in practice. Nevertheless, for restricted domains the most recent approaches are getting closer to being useful in practice. This might be the reason why quantitative performance evaluation has received much interest recently   BIB001  . As is to be expected, the most sophisticated approaches for building extraction are the newest ones  BIB002 .