In recent years significant advances have been made in the area of automatic extraction of low-level features from audiovisual content. However, little progress has been achieved in the identification of high-level semantic features or the effective combination of semantic features derived from different modalities. Knowledge acquisition is becoming a key-enabling factor of the above tasks towards more scalable and reliable solutions, and thus its automation is becoming critical.

As the deployment of knowledge enhances the robustness of extraction while on the other hand the continuous extraction of semantic information can enrich this knowledge, synergistic approaches that combine multimedia extraction and knowledge evolution in a bootstrapping common framework to introduce new opportunities in semantic multimedia applications. Integration with additional sources of information, e.g. by using human annotation tools or real-time event services, may further simplify and disambiguate semantic multimedia information systems. Moreover, adaptation to a particular domain, for example to sports events, such as the Olympic games, is essential in order to reduce the complexity of multimedia analysis. In this context, unified modelling and representation of multimedia and domain-specific knowledge, ontology evolution, and standard and non-standard inference services for multimodal semantic knowledge fusion, form cutting edge technologies.

Key note speakers at the workshop:
Fabio Ciravegna, University of Sheffield
Alan Smeaton, Dublin City University