SAMT2006

Former European Workshop on the Integration of knowledge, semantic and digital Media Technologies (EWIMT)

The SAMT 2006 Program Committee invites proposals for the Tutorial Program of SAMT 2006, the First International Conference on Semantics And digital Media Technology, to be held December 6-8, 2006, in Athens, Greece. Tutorials will be held on Wednesday, December 6, 2006.

Goals
The First International Conference on Semantics And digital Media Technology (SAMT) targets to narrow the large disparity between the lowlevel descriptors that can be computed automatically from multimedia content and the richness and subjectivity of semantics in user queries and human interpretations of audiovisual media - The Semantic Gap.

The purpose of the tutorials is to provide both postgraduate students and general interested audience the latest research work and progress in the field of the Multimedia and the Semantic Web, so that the audience has the opportunity to gain deeper insight into the challenges related to multimedia semantics and the increasingly emerging applications relying on multimedia understanding. We seek therefore high quality proposals for tutorials about topics related to the conference, and particulary one of the following areas:

For tutorials For workshops
 * has topic::Multimedia and the Semantic Web
 * has topic::Multimedia analysis and has topic::ontology-based annotations
 * Knowledge-based, context aware inference for semantic multimedia analysis
 * Scalable has topic::multimedia semantic metadata representation and content transmission
 * Semantic adaptation, personalization and retrieval for multimedia
 * has topic::Multimedia semantics
 * Multimedia representation, annotation
 * has topic::Multimedia interoperability
 * Handling uncertainty in multimedia applications
 * Multimedia web services
 * has topic::Multimedia tools - e.g. annotation, interoperability, analysis
 * Multimedia reasoning
 * Semantic Web language extensions for multimedia
 * Knowledge driven multimedia analysis
 * Profiling personalisation and has topic::context modeling