K-Space Work Package 4

Knowledge Extraction

This Work Package aims at exploiting the development and results of Content based Multimedia Analysis and Semantic Multimedia to provide techniques for the semantic analysis, annotation and retrieval of multimedia content. The overall approach will be based on knowledge assisted content analysis and annotation using a multimedia ontology infrastructure. More specifically, semantic and low-level attributes of the objects to be detected in combination with appropriately defined rules developed within Semantic Multimedia will determine the set of algorithms, which will be the aim of Knowledge Extraction, and parameters required for the detection of semantic objects. Semantic concepts within the context of specific domains will be defined in ontologies, extended with qualitative attributes of the semantic objects (e.g.colour homogeneity), multimedia processing methods (e.g. colour clustering), and numerical data or lowlevel features (e.g. colour models, also defined in the ontology). Semantic Web technologies will be used for knowledge representation including rules to describe how tools for multimedia analysis should be applied according to different object attributes and low-level features as extracted in Content based Multimedia Analysis .

Activity 4.1 - Specification of a Multimedia Ontology Infrastructure

Activity 4.2 - Knowledge-assisted Multimedia Analysis

Activity 4.3 - Multimedia Reasoning and Annotation

Activity 4.4 - Content based Multimedia Mining

Activity 4.5 - Intelligent User Relevance Feedback

Partners Involved

Informatics and Telematics Institute (ITI) & Centre for Research and Technology Hellas (CERTH)

Queen Mary, University of London (QMUL)

Koblenz University, (Uni Ko-Ld)

Joanneum Research Forschungsgesellschaft mbH, (JRS)

German Research Centre for Artificial Intelligence (DFKI)

Dublin City University, (DCU)