Semantic annotation of images and videos for multimedia analysis

  • Authors:

  • Stephan Bloehdorn;Kosmas Petridis;Carsten Saathoff;Nikos Simou;Vassilis Tzouvaras;Yannis Avrithis;Siegfried Handschuh;Yiannis Kompatsiaris;Steffen Staab;Michael G. Strintzis

  • Affiliations:

  • Institute AIFB, University of Karlsruhe, Karlsruhe, Germany;Informatics and Telematics Institute, Thermi-Thessaloniki, Greece;Institute for Computer Science, University of Koblenz-Landau, Koblenz, Germany;School of Electrical and Computer Engineering, National Technical University of Athens, Zographou, Athens, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Zographou, Athens, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Zographou, Athens, Greece;Institute AIFB, University of Karlsruhe, Karlsruhe, Germany;Informatics and Telematics Institute, Thermi-Thessaloniki, Greece;Institute for Computer Science, University of Koblenz-Landau, Koblenz, Germany;Informatics and Telematics Institute, Thermi-Thessaloniki, Greece

  • Venue:
  • ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
  • Year:
  • 2005

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Abstract

Annotations of multimedia documents typically have been pursued in two different directions. Either previous approaches have focused on low level descriptors, such as dominant color, or they have focused on the content dimension and corresponding annotations, such as person or vehicle. In this paper, we present a software environment to bridge between the two directions. M-OntoMat-Annotizer allows for linking low level MPEG-7 visual descriptions to conventional Semantic Web ontologies and annotations. We use M-OntoMat-Annotizer in order to construct ontologies that include prototypical instances of high-level domain concepts together with a formal specification of corresponding visual descriptors. Thus, we formalize the interrelationship of high- and low-level multimedia concept descriptions allowing for new kinds of multimedia content analysis and reasoning.