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A System for the Semantic Multimodal Analysis of News Audio-Visual Content

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Author(s): Mezaris Vasileios | Gidaros Spyros | Papadopoulos GeorgiosTh | Kasper Walter | Steffen Jörg | Ordelman Roeland | Huijbregts Marijn | de Jong Franciska | Kompatsiaris Ioannis | Strintzis MichaelG

Journal: EURASIP Journal on Advances in Signal Processing
ISSN 1687-6172

Volume: 2010;
Issue: 1;
Start page: 645052;
Date: 2010;
Original page

ABSTRACT
Abstract News-related content is nowadays among the most popular types of content for users in everyday applications. Although the generation and distribution of news content has become commonplace, due to the availability of inexpensive media capturing devices and the development of media sharing services targeting both professional and user-generated news content, the automatic analysis and annotation that is required for supporting intelligent search and delivery of this content remains an open issue. In this paper, a complete architecture for knowledge-assisted multimodal analysis of news-related multimedia content is presented, along with its constituent components. The proposed analysis architecture employs state-of-the-art methods for the analysis of each individual modality (visual, audio, text) separately and proposes a novel fusion technique based on the particular characteristics of news-related content for the combination of the individual modality analysis results. Experimental results on news broadcast video illustrate the usefulness of the proposed techniques in the automatic generation of semantic annotations.
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