Interpretation Models and reasoning Strategies in 
Scene analysis 
Toni Schenk 
Department of Geodetic Science and Surveying 
The Ohio State University 
1958 Neil Ave., Columbus, OH 43210 
ABSTRACT 
The presentation begins with a brief overview of reasoning strategies, ranging from 
simple constructs to more sophisticated inference schemes. This is followed by a 
discussion of how reasoning fits in to the vision paradigm. Next, basic assumptions are 
discussed, including the fact that input data like digital imagery for solving vision tasks— 
or photogrammetric problems for that matter—are incomplete and ambiguous. Therefore, 
only inferences can be drawn, not deductions. I also believe that the (automatic) solution 
of photogrammetric problems does not permit shortcuts. For example, an interpreted 
aerial scene cannot be obtained in one single step from the digital image. Rather, several 
processes are involved which result into increasingly more abstract representations. 
Inference methods must deal with knowledge and information derived from the input 
data. Ultimately, the data driven processes must be supported (guided) by domain 
specific knowledge. 
The second part of the presentation will focus on abductive inference and its application to 
recognizing objects in aerial scenes. After a brief overview and the motivation for using 
abduction, specifications of a system under development are discussed. The presentation 
ends with conclusions, including a brief discussion of numeric vs. symbolic reasoning. 
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