Ontology Based Semantic Image Interpretation

Abstract. Semantic image interpretation (SII) leverages Semantic Web ontologies for generating a mathematical structure that describes the content of images. SII algorithms consider the ontologies only in a late phase of the SII process to enrich these structures. In this research proposal we study a well-founded framework that combines logical knowledge with low-level image features in the early phase of SII. The image content is represented with a partial model of an ontology. Each element of the partial model is grounded to a set of segments of the image. Moreover, we propose an approximate algorithm that searches for the most plausible partial model. The comparison of our method with a knowledgeblind baseline shows that the use of ontologies significantly improves the results.

• Type: Journal
• Year: 2015
• Where: AIIA
• Authors: Ivan Donadello
• Keywords: AIIA 2015, Artificial Intelligence