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A generic news story segmentation system and its evaluation |
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
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The paper presents an approach to segmenting broadcast TV news programmes automatically into individual news stories. We first segment the programme into individual shots, and then a number of analysis tools are run on the programme to extract features to represent each shot. The results of these feature extraction tools are then combined using a support vector machine trained to detect anchorperson shots. A news broadcast can then be segmented into individual stories based on the location of the anchorperson shots within the programme. We use one generic system to segment programmes from two different broadcasters, illustrating the robustness of our feature extraction process to the production styles of different broadcasters.
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Keyword(s):
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Signal processing; Digital video; Image processing; face recognition; feature extraction; image segmentation; learning (artificial intelligence); object detection; support vector machines; television broadcasting; video signal processing |
Publication Date:
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2004 |
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Type:
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Other |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Dublin City University |
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Citation(s):
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O'Hare, Neil, Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <https://orcid.org/0000-0003-1028-8389>, Czirjék, Csaba, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135> and Murphy, Noel (2004) A generic news story segmentation system and its evaluation. In: ICASSP 2004 - IEEE International Conference on Acoustics, Speech, and Signal Processing, 17-21 May 2004, Montreal, Quebec, Canada. |
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Publisher(s):
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Institute of Electrical and Electronics Engineers |
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File Format(s):
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application/pdf |
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Related Link(s):
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http://doras.dcu.ie/242/1/ieee_icassp_2004.pdf,
http://dx.doi.org/10.1109/ICASSP.2004.1326723 |
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First Indexed:
2009-11-05 02:00:26 Last Updated:
2019-02-09 07:04:49 |
