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Semantic AudiovisuaL Entertainment
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Related Projects

K-Space - Knowledge Space of semantic inference for automatic
annotation and retrieval of multimedia content

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. K-Space exploits the complementary expertise of project partners, enables resource optimization and fosters innovative research in the field.

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: The Semantic Gap.
new millennium, new media
nm2 is a collaborative research project which unites leading creative and technology experts from across Europe to address a great opportunity for businesses and consumers: how to develop compelling new media forms which take advantage of the unique characteristics of broadband networks.

nm2 is about creating a variety of new media genres using all of the facilities of modern broadband communication and interactive terminals. The project will create new production tools for the media industry that will allow the easy production of non-linear broadband media that can be personalised to suit the preferences of the individual user. Viewers will be able to interact directly with the medium and influence what they see and hear according to their personal tastes and wishes.
The mission of AIM@SHAPE is to advance research in the direction of semantic-based shape representations and semantic-oriented tools to acquire, build, transmit, and process shapes with their associated knowledge. We foresee a new generation of shapes in which knowledge is explicitly represented and, therefore, can be retrieved, processed, shared, and exploited to construct new knowledge.
focuses on generating value and benefits to end users, content providers, network operators, and multimedia equipment manufacturers, by introducing, developing and implementing a system based on an innovative concept of knowledge assisted, adaptive multimedia content management, addressing user needs.
DIP- Data, Information, and Process Integration with Semantic Web Services
DIP’s objective is to develop and extend Semantic Web and Web Service technologies in order to produce a new technology infrastructure for Semantic Web Services (SWS) - an environment in which different web services can discover and cooperate with each other automatically. DIP's long term mission is to deliver the enormous potential benefits of Semantic Web Services to e-Work and e-Commerce.
Discovering, inter-relating and navigating cross-media campaign knowledge

MediaCampaign's scope is on discovering, inter-relating and navigating cross-media campaign knowledge. The objectives includes the design and implementation of a specific media campaign ontology (MEPCO), a module for cross relation of specific campaigns, algorithms for detecting advertisements over different media, audio analysis algorithms and the detection plus tracking of new campaigns. The main goal is to automate to a large degree the detection and tracking of media campaigns on television, Internet and in the press and in various countries. MediaCampaign's focus is on a concrete example for a media campaign: advertisement campaigns, but the results of the project can be easily used in similar applications (e.g. political and social ones, Public Relation etc.).
Unit E2 - Knowledge & Content Technologies
Our mission is to support the development of semantic-based and context-aware technologies that will provide automated solutions for knowledge representation, acquisition and management. Research work will combine knowledge, multimedia and Web technologies as well as natural language and image processing techniques aimed at enabling capabilities such as multimedia content mining, knowledge sharing across organisation and communities, and automated information analysis and decision support in knowledge-intensive applications.