K-Space is a network of leading research teams from academia and industry conducting integrative research and dissemination activities in semantic inference for automatic and semi-automatic annotation and retrieval of multimedia content. The aim of K-Space research is to narrow the gap between low-level content descriptions that can be computed automatically by a machine and the richness and subjectivity of semantics in high-level human interpretations of audiovisual media.
K-Space integrative research focus on three key areas:
-Content-based multimedia analysis: Tools and methodologies for low and medium-level signal processing, natural language, audio and speech processing, text analysis, low-level feature fusion and content description.
-Knowledge extraction: Building of a multimedia ontology infrastructure, knowledge-assisted multimedia analysis multimedia reasoning and annotation, context based multimedia mining and intelligent user relevance feedback.
-Semantic multimedia: Adaptation of existing languages, representation of extracted semantic information, knowledge representation for multimedia, semantics-based interaction with multimedia and knowledge extraction from complementary sources.
An important objective of the Network is to implement an open and expandable framework for collaborative research based on a common reference system made up of modular technology: The Knowledge Space of Shared Technology to Bridge the Semantic Gap, "K-Space".
K-Space will integrate complementary expertise, enable resource optimization and sharing, and foster innovative research in semantic inference for semi-automatic annotation and retrieval of multimedia content. Specific dissemination objectives of K-Space are:
-Dissemination of the technical developments of the network across the broad research community
-Influencing and contributing to related knowledge-based multimedia standardisation activities.
Fields of science
Funding SchemeNoE - Network of Excellence
Glasnevin, Dublin 9
75634 Paris 13
94366 Bry Sur Marne
G12 8QQ Glasgow
130 67 Praha