In this paper, we describe a framework for the management of semantic metadata that describe audiovisual content. The main objectives of this work are to provide a framework allowing enhanced retrieval performance and better user interfaces for audiovisual data, based on extensions of the well accepted international standards for the digital media, digital broadcasting and TV-Anytime domains like TV-Anytime and MPEG-7, as well as to provide an interoperability framework between TV-Anytime and MPEG-7 for the rapidly expanding set of interoperating digital library and interactive TV applications. The framework was developed in the context of the UP-TV project, which investigates TV-Anytime architectures and services. Our approach is ontology-driven, in the sense that we provide ontology based domain-specific extensions of the standards for describing multimedia content. Several aspects of the framework are based on the existence of ontologies. Our framework allows the creation of more efficient user interfaces for accessing content, better retrieval performance and better support in the indexing phase. It also provides compatibility in indexing between the two standards and interoperability for TV-Anytime and digital library applications supported by TV-Anytime servers. We have developed a domain-specific ontology (football games) to test our framework ideas and implementation. The developed ontology uses as primitive modelling elements those provided by the MPEG-7 metadata model. The mapping of the ontology to TV-Anytime metadata primitives is straightforward. We show in detail the concrete implementation of the framework on top of relational databases and its interfaces with the other system components. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Tsinaraki, C., Fatourou, E., & Christodoulakis, S. (2003). An ontology-driven framework for the management of semantic metadata describing audiovisual information. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2681, 340–356. https://doi.org/10.1007/3-540-45017-3_24
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