Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> 1. Introduction.- 2. System Architecture and Reasoning Scheme in SIGMA.- 3. Algorithms for Evidence Accumulation.- 4. LLVE: Expert System for Top-Down Image Segmentation.- 5. Experimental Results and Performance Evaluation.- 6. Conclusion.- References. <s> BIB001 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> Abstract The paper discusses the modeling necessary for recovering man made objects—in this case buildings—in complex scenes from digital imagery. The approach addresses all levels of image analysis for deriving semantically meaningful descriptions of the scene from the image, via the geometrical/physical model of the objects and their counterparts in the image. The central link between raster image and scene are network-like organized aspects of parts of the objects. This is achieved by generically modeling the objects using parametrized volume primitives together with the application-specific constraints, which seems to be adequate for many types of buildings. The paper sketches the various interrelationships between the different models and their use for feature extraction, hypothesis generation, and verification. <s> BIB002 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> S. Airault, O. Jamet and F. Leymarie, "From Manual to Automatic Stereoplotting: Evaluation of Different Road Network Capture Processes". In: International Archives of Photogrammetry and Remote Sensing, Vol. 31(3), ISPRS, pp. 14-18, 1996. <s> BIB003 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> An approach is presented for imposing generic hard constraints on deformable models at a low computational cost, while preserving the good convergence properties of snake-like models. We believe this capability to be essential not only for the accurate modeling of individual objects that obey known geometric and semantic constraints but also for the consistent modeling of sets of objects. <s> BIB004 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> A number of different definitions of artificial intelligence is considered and their possible significance for the domain of reconstruction of man-made objects from aerial images is discussed. A useful property of AI is its inclination towards exploratory work which has helped to launch many new research areas. It is shown that contributions of AI can be found in various subdomains which are important for the field of man-made object reconstruction as a whole, namely perceptual organization, modeling and knowledge representation, control, handling of uncertainties, to name but the most important ones. As the field is far from mature at this very moment, AI can and will further contribute to its advancement. <s> BIB005 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> We present in this article a strategy and methodology for an efficient generation of even fairly complex building models. Within this concept we request the operator to measure the house roofs from a stereomodel in form of an unstructured point cloud. According to our experience this can be done very quickly. In a second step we fit generic building models fully automatically to these point clouds. The structure information is inherently included in these building models. In such a way geometric, topologic and even semantic data can be handed over to a CAD-system, in our case AutoCad, for further visualization and manipulation. <s> BIB006 </s> Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, <s> Introduction <s> The use of three-dimensional site models in a variety of applications is hampered by the fact that the models are costly and time-consuming to extract from imagery. Automated algorithms, which are as yet imperfect can even now contribute to speeding up the model-building process in a production environment. This paper describes an effort to validate and quantify that contention through implementation of a loosely coupled testbed, which allows an algorithm’s potential effectiveness to be determined without extensive re-coding and integration. The testbed is based on SOCET SET®, the commercial photogrammetric workstation, developed by GDE Systems and widely used for building site models, and involves efficient interactive tools to supply parameters and cues to the automated algorithms and to correct the results delivered by the algorithms. <s> BIB007
Automatic extraction of objects such as buildings or roads from digital aerial imagery is not only scientifically challenging but also of major practical importance for data acquisition and update of Geographic Information System (GIS) databases or site models. In this paper, the term "extraction" is used for the detection as well as for the reconstruction of objects. "Detection" means that objects are found based on simpler features and camera models resulting in simple two-(2D) or three-dimensional (3D) models. On the other hand, for a highly accurate "reconstruction", knowledge about the object's geometry and especially topology is assumed to be given and more complex camera models as well as high quality data are used. The basic reason why the two terms are combined in this paper is their interdependence: The semantics of an object (detection) depends directly on its geometric extent (reconstruction). More practically speaking, some recent approaches give an indication that only by a precise reconstruction of an object enough evidence can be achieved to exclude wrong object types. The paper surveys the state-of-the-art automatic object extraction techniques from (digital) aerial imagery. The survey is extensive, but it does not claim to be complete. Some surveys give an overview of the whole area BIB001  , whereas others review only building extraction techniques  BIB002 , or the role of Artificial Intelligence (AI) BIB005 . This survey includes approaches for object extraction from satellite images, which influence the extraction from aerial imagery. It only covers models and strategies. Specific algorithms or techniques derived from them are not reviewed, to limit the extent of the survey. Though the combination and integration of the models and strategies with human interaction to build semi-automatic systems  BIB003 BIB004 BIB006  BIB007 is of major practical importance, the survey only deals with the automatic parts of the extraction. This is due to the fact that the problems linked to human-computer interaction constitute a challenge in their own right. The basic idea of the survey is to present a combined model and strategy covering the knowledge in the field. To give insight into how it arose, some approaches for building extraction were selected which are described in more detail and assessed according to some well-defined criteria. The detailed analysis is given only for the building extraction approaches, because they present the majority of the work.