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A generic news story segmentation system and its evaluation

O'Hare, Neil, Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389, Czirjék, Csaba, O'Connor, Noel E. orcid logoORCID: 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.

Abstract
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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:face recognition; feature extraction; image segmentation; learning (artificial intelligence); object detection; support vector machines; television broadcasting; video signal processing;
Subjects:Engineering > Signal processing
Computer Science > Digital video
Computer Science > Image processing
DCU Faculties and Centres:Research Institutes and Centres > Centre for Digital Video Processing (CDVP)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/ICASSP.2004.1326723
Copyright Information:Copyright © 2004 IEEE. Reprinted from ICASSP 2004 - IEEE International Conference on Acoustics, Speech, and Signal Processing. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Funders:EU IST-2000-32795
ID Code:242
Deposited On:06 Mar 2008 by DORAS Administrator . Last Modified 08 Nov 2018 11:12
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