Title
A system for the semantic multimodal analysis of news audio-visual content
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.
Year
DOI
Venue
2010
10.1155/2010/645052
EURASIP J. Adv. Sig. Proc.
Keywords
Field
DocType
proposed analysis architecture,news-related multimedia content,news-related content,knowledge-assisted multimodal analysis,user-generated news content,news content,news audio-visual content,news broadcast video,semantic multimodal analysis,automatic generation,individual modality analysis result,automatic analysis,modal analysis
Broadcasting,Computer vision,Architecture,Annotation,Media sharing,Information retrieval,Semantic annotation,Computer science,Multimodal analysis,Artificial intelligence,Multimedia
Journal
Volume
Issue
ISSN
2010,
1
1687-6180
Citations 
PageRank 
References 
6
0.46
30
Authors
10