Image interpretation aims not only at detecting and recognizing objects in a scene but also at deriving a semantic description considering contextual information in the whole scene. Image interpretation can be formalized as an abductive reasoning problem, i.e. an inference to the best explanation using a background knowledge. In this work, we present a framework using a tableau method for generating and selecting potential explanations of the given image when the background knowledge is encoded in description logics, and includes concepts describing objects and their spatial relations. The best explanation is selected according to a minimality criterion based on the satisfaction degree of spatial relations between the objects, computed in concrete domains.
image interpretation, abduction, description logics, semantic tableau, spatial relations, fuzzy representations, concrete domains
Ce travail a été financé par l’ANR (projet LOGIMA).
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