You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings Helmut Mayer Chair for Photogrammetry and Remote Sensing, 
Chapter Title:  Model 
1. Abstract of Cited Paper (BIB001):  Applications such as landscape planning, environmental monitoring, and flight and driving simulators have a high demand for realistic landscape models. Quantity, precision and the type of models ask for methods which automate the model generation by evaluation of remote sensing data. The presented modelling system AIDA tackles the demand for efficient representation and high realism by integrating a priori knowledge about the appearance of the objects in the scene to drive object specific constraints for 3D reconstruction. This requires an image interpretation to assign a meaning to the objects in the scene. For explicit representation of the declarative and procedural knowledge a problem independent formalism based on semantic nets and rules is used. It provides both a data driven and model driven control strategy. 
2. Abstract of Cited Paper (BIB002):  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. 
3. Abstract of Cited Paper (BIB003):  Thank you very much for downloading semantic modeling for the acquisition of topographic information from images and maps smati97. Maybe you have knowledge that, people have search hundreds times for their chosen readings like this semantic modeling for the acquisition of topographic information from images and maps smati97, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some harmful virus inside their computer.

Literature Review:
The model is organized into general parts and specific parts for buildings. The fact, that the general parts are much larger than the specific parts illustrates that the model is for the most part generic. The General Parts of the Model are: Characteristic Properties Are Often the Consequence of the Function of Objects  BIB004 . Very importantly, they integrate knowledge about the 3D real world into the model. Typical examples for knowledge sources are, apart from constraints concerning the usefulness for humans BIB001 , construction instructions for different types of buildings or roads. For large parts of the knowledge about function it seems to be enough to take them into consideration for modeling. I.e., it is not necessary to integrate them into the system. BIB002 makes that the interpretation is not so much affected by sensor characteristics. This is especially important when different kinds of sensors, like optical and radar are utilized.   BIB003   are used for buildings as well as for road pavements (parallel edges). For buildings they are especially suited for simple Automatic Object Extraction from Aerial Imagery 13 types with, e.g., perpendicular outline and flat roof, and the construction of hypotheses for more complex buildings. Though, for modeling of the latter ones they are not sophisticated enough.