Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Automatic, context-of-capture based, categorization, structure detection and segmentation of news telecasts

Christodoulakis Stavros, Arne Jacobs, George T. Ioannidis, Martha Larson, Nektarios Moumoutzis

Simple record

URIhttp://purl.tuc.gr/dl/dias/0C4F67BB-ABA9-464A-BBF6-D310ED320123-
Identifierhttps://doi.org/10.1007/978-3-540-77088-6_27 -
Languageen-
Extent10 pagesen
TitleAutomatic, context-of-capture based, categorization, structure detection and segmentation of news telecastsen
CreatorChristodoulakis Stavrosen
CreatorΧριστοδουλακης Σταυροςel
CreatorArne Jacobsen
CreatorGeorge T. Ioannidisen
CreatorMartha Larsonen
CreatorNektarios Moumoutzisen
Content SummaryThe objective of the work reported here is to provide an automatic, context-of-capture categorization, structure detection and segmentation of news broadcasts employing a multimodal semantic based approach. We assume that news broadcasts can be described with context-free grammars that specify their structural characteristics. We propose a system consisting of two main types of interoperating units: The recognizer unit consisting of several modules and a parser unit. The recognizer modules (audio, video and semantic recognizer) analyze the telecast and each one identifies hypothesized instances of features in the audiovisual input. A probabilistic parser analyzes the identifications provided by the recognizers. The grammar represents the possible structures a news telecast may have, so the parser can identify the exact structure of the analyzed telecast.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-05-
Date of Publication2007-
Bibliographic CitationA. Jacobs, G. T. Ioannidis,M. Larson ,S. Christodoulakis, N. Moumoutzis , "Automatic, context-of-capture based, categorization, structure detection and segmentation of news telecasts ",in 2007 First Intern. DELOS Conf., pp.278-287.doi :10.1007/978-3-540-77088-6_27en

Available Files

Services

Statistics

 

Copyright © DIAS 2013