Abstract
In order to browse the news video effectively, classification and skimming of news articles are positively essential. In this paper, we propose the classification and skimming of articles for an effective news browsing. The classification method uses tags to distinguish speakers in the closed-caption. The skimming method extracts the representative sentence from the part of article introduced by the anchor in the closed-caption and the representative frames consisting of anchor frame, open-caption frames, and frames synchronized with high-frequency terms. In the experiment, we have applied the proposed classification and skimming methods to news video with Korean closed-captions, and have empirically confirmed that the proposed methods could support effective browsing of news videos.
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References
Vittorio, C., Lawrence, D.B.: Image Databases. John Wiley & Sons, Inc, Chichester (2002)
Alexander, G.H., Michael, J.W.: Informedia: News-on-Demand Multimedia Information Acquisition and Retrieval. In: Intelligent Multimedia Information Retrieval, pp. 215–240. AAAI Press/The MIT Press (1997)
Ariki, Y., Matsuura, K.: Automatic classification of TV news articles based on telop character recognition. IEEE International Conference on Multimedia Computing and Systems 2, 148–152 (1999)
HongJiang, Z., Yihong, G., Smoliar, S.W., Shuang, Y.T.: Automatic parsing of news video. In: Proc. of the Int. Conf. on Multimedia Computing and Systems, pp. 45–54 (1994)
Smith, M.A., Kanade, T.: Video skimming and characterization through the combination of image and language understanding. In: International Workshop on Content-Based Access of Image and Video Database, pp. 61–70 (1998)
HongJiang, Z., Chien, Y.L., Stephen, W.S., JianHua, W.: Video Parsing, Retrieval and Brows-ing: an Integrated and Content-based Solution. In: Intelligent Multimedia Information Retrieval, pp. 139–158. AAAI Press/The MIT Press (1997)
Girgensohn, A., Boreczky, J.: Time-constrained keyframe selection technique. In: IEEE International Conference on Multimedia Computing and Systems, vol. 1, pp. 756–761 (1999)
Christel, M.G., Hauptmann, A.G., Warmack, A.S., Crosby, S.A.: Adjustable filmstrips and skims as abstractions for a digital video library. In: ADL 1999. Proceedings. IEEE Forum on Research and Technology Advances in Digital Libraries, pp. 98–104 (1999)
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© 2005 Springer-Verlag Berlin Heidelberg
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Cho, J., Jeong, S., Choi, B. (2005). Classification and Skimming of Articles for an Effective News Browsing. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_100
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DOI: https://doi.org/10.1007/11553939_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28896-1
Online ISBN: 978-3-540-31990-0
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