Preface

In recent years significant advances have been made in the area of automatic ex-traction of low-level features from audiovisual content. However, little progress has been achieved in the identification of high-level semantic features or the effec-tive combination of semantic features derived from different modalities. Knowl-edge acquisition is becoming a key-enabling factor of the above tasks towards more scalable and reliable solutions, and thus its automation is becoming criti-cal. As the deployment of knowledge enhances the robustness of extraction while on the other hand the continuous extraction of semantic information can en-rich this knowledge, synergistic approaches that combine multimedia extraction and knowledge evolution in a bootstrapping common framework 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 informa-tion systems. Moreover, adaptation to a particular domain, for example to sports events, such as the Olympic games, is essential in order to reduce the complex