Gruen, Armin 
  
5 CONCLUSIONS 
Site recording and modeling from images has become a key issue in photogrammetry. Over the past 20 years or so a 
wealth of automated approaches to object extraction from satellite, aerial and terrestrial images has been developed. 
While some of these procedures work fine with highly structured images, as they are found in industrial measurement 
applications, they will inevitably fail in cases of complex image content. Therefore more emphasis has been put recently 
on semi-automated procedures, combining the human ability of image understanding with the numbercrunching 
capacity of computers. This has led to a number of promising approaches, some of which are briefly mentioned in this 
paper. 
Progress on the research side is not matched yet by achievements in system development. Digital Stations are either 
providing only manual functions for information extraction, or the fully automated procedures show unstable 
performance. 
One way to overcome the fundamental deficiencies in image understanding, which creates a serious obstacle towards 
successful automation, is simplification of the problem. This can be achieved by adding more and different kind of 
information to the primary data. Recently sensor and data fusion became relevant research topics. The integration of 
laser scans, existing DTMs, map and GIS data, hyperspectral and InSAR data shows very first promising results. 
However, when developing new approaches to object recording one should keep in mind that user specifications do not 
remain unchanged over time. We see already now an increased request for highresolution data. As an example, in 
central Europe there is already a remarkable demand for buildings with modeled overhanging roofs. Also, facility 
management applications require a detailed modelling of the interior of buildings. The requirements for high level of 
detail, both in terms of geometric and texture models, must lead to a critical evaluation of our extraction methods. 
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