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The interpretation of aerial photographs requires a lot of knowledge about the scene under consideration. Knowledge about the type of scene: airport, suburban housing development, urban city, aids in low-level and intermediate level image analysis, and will drive high-level interpretation by constraining search for plausible consistent scene models. Collecting and representing large knowledge bases requires specialized tools. In this paper we describe the organization of a set of tools for interactive knowledge acquisition of scene primitives and spatial constraints for interpretation of aerial imagery. These tools include a user interface for interactive knowledge acquisition, the automated compilation of that knowledge from a schema-based representation into productions that are directly executable by our interpretation system, and a performance analysis tool that generates a critique of the final interpretation. Finally, the generality of these tools is demonstrated by the generation of rules for a new task, suburban house scenes, and the analysis of a set of imagery by our interpretation system.
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McKeown et al. (Sat,) studied this question.
synapsesocial.com/papers/6a1ffff39d62e9997c04afee — DOI: https://doi.org/10.1117/12.940080
David M. McKeown
Carnegie Mellon University
Wilson A. Harvey
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
Carnegie Mellon University
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