Our paper on “Video Annotation and Retrieval Using Ontologies and Rule Learning” was accepted for publication by the International IEEE MultiMedia Magazine.

In this paper we present an approach for automatic annotation and retrieval of video content, based on ontologies and semantic concept classifiers. A novel rule-based method is used to describe and recognize composite concepts and events. Our algorithm learns automatically rules expressed in Semantic Web Rules Language (SWRL), exploiting the knowledge embedded into the ontology. Concepts’ relationship of co-occurrence and the temporal consistency of video data are used to improve the performance of individual concept detectors. Finally, we present a web video search engine, based on ontologies, that permits queries using a composition of boolean and temporal relations between concepts.

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