Georg Güntner

Semantic enhancement for media asset management systems

The socio-economic development of the World Wide Web gathered a large momentum through Web 2.0 and currently, the Web of Data is adding a further technological driver to this. The tremendous growth of media data combined with structured (linked) data promises further opportunities for digital market places. Although the integration of media content with linked data is only beginning there are already working groups and projects addressing this issue. We show how media and existing data sets can be seamlessly integrated and thus give possibilities for an extended user experience while interacting with media content on the web. We focus on automatic semantic enhancement services that can link arbitrary and open accessible data and introduce opportunities for media annotation, fragmentation and presentation. Our use case scenario is based on the Red Bull Content Pool, a media management system for videos, images and articles about Red Bull related content covering a multitude of sports events.

Smart content factory: assisting search for digital objects by generic linking concepts to multimedia content

Search, retrieval and navigation in audiovisual repositories is a task common to all media asset management systems: Users are supported by a wide range of features which are traditionally based on full text search and metadata queries. In this paper we describe an approach to superimpose a semantic indexing infrastructure over the media assets and the metadata associated with them. The infrastructure is based on formal knowledge models and facilitates the use of further navigation dimensions: By identifying semantic concepts we are able to create a dynamic navigation structure which is based on the underlying knowledge model and the conceptual relations defined therein.

Adding wings to red bull media: search and display semantically enhanced video fragments

The Linked Data movement with the aims of publishing and interconnecting machine readable data has originated in the last decade. Although the set of (open) data sources is rapidly growing, the integration of multimedia in this Web of Data is still at a very early stage. This paper describes, how arbitrary video content and metadata can be processed to identify meaningful linking partners for video fragments - and thus create a web of linked media. The video test-set for our demonstrator is part of the Red Bull Content Pool and confined to the Cliff Diving domain. The candidate set of possible link targets is a combination of a Red Bull thesaurus, information about divers from www.redbull.com and concepts from DBPedia. The demo includes both a semantic search on videos and video fragments and a player for videos with semantic enhancements.

The Role of MPEG-7 in semantic Annotation and the Cross-Media Publishing Process

During the development of a knowledge-based audio-visual information system the authors of this article defined a conceptual system architecture based on MPEG-7 as the general description scheme for the media assets in the middleware. This concept was not only used to achieve a high abstraction and independence of the underlying media asset management system, it was also and primarily used as the basis of a semantic indexing process. Based on lightweight ontologies the descriptions of the media assets were associated with semantic concepts. Semantically annotated MPEG-7 assets were then propagated to the presentation layer, thus allowing the implementation of a variety of publication scenarios, including cross-media scenarios for the creation of concise video summaries