A System for the Semantic Multimodal Analysis of News Audio-Visual Content
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 t...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2010-01-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2010/645052 |
| _version_ | 1818827335337508864 |
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| author | Michael G. Strintzis Ioannis Kompatsiaris Franciska de Jong Marijn Huijbregts Roeland Ordelman Jörg Steffen Walter Kasper Georgios Th. Papadopoulos Vasileios Mezaris Spyros Gidaros |
| author_facet | Michael G. Strintzis Ioannis Kompatsiaris Franciska de Jong Marijn Huijbregts Roeland Ordelman Jörg Steffen Walter Kasper Georgios Th. Papadopoulos Vasileios Mezaris Spyros Gidaros |
| author_sort | Michael G. Strintzis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T00:41:55Z |
| format | Article |
| id | doaj.art-41236d4d3b3c4216801c5609ea7ad890 |
| institution | Directory Open Access Journal |
| issn | 1687-6172 1687-6180 |
| language | English |
| last_indexed | 2024-12-19T00:41:55Z |
| publishDate | 2010-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-41236d4d3b3c4216801c5609ea7ad8902022-12-21T20:44:29ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802010-01-01201010.1155/2010/645052A System for the Semantic Multimodal Analysis of News Audio-Visual ContentMichael G. StrintzisIoannis KompatsiarisFranciska de JongMarijn HuijbregtsRoeland OrdelmanJörg SteffenWalter KasperGeorgios Th. PapadopoulosVasileios MezarisSpyros GidarosNews-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.http://dx.doi.org/10.1155/2010/645052 |
| spellingShingle | Michael G. Strintzis Ioannis Kompatsiaris Franciska de Jong Marijn Huijbregts Roeland Ordelman Jörg Steffen Walter Kasper Georgios Th. Papadopoulos Vasileios Mezaris Spyros Gidaros A System for the Semantic Multimodal Analysis of News Audio-Visual Content EURASIP Journal on Advances in Signal Processing |
| title | A System for the Semantic Multimodal Analysis of News Audio-Visual Content |
| title_full | A System for the Semantic Multimodal Analysis of News Audio-Visual Content |
| title_fullStr | A System for the Semantic Multimodal Analysis of News Audio-Visual Content |
| title_full_unstemmed | A System for the Semantic Multimodal Analysis of News Audio-Visual Content |
| title_short | A System for the Semantic Multimodal Analysis of News Audio-Visual Content |
| title_sort | system for the semantic multimodal analysis of news audio visual content |
| url | http://dx.doi.org/10.1155/2010/645052 |
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