Abstract
It is a challenging issue to analyze video content for video mining due to the difficulty in video representation. A hierarchical model of video representation is proposed with a schema for content-based analysis of news video in this paper. The research problem targeted in this paper is to mine a massive video database to retrieve specific clip based on content defined by users. This is frequently encountered in entertainment and video editing. A novel solution to this problem is developed in this paper, in which the consecutive news video is segmented into shots, scenes and news items using multimodal features based on the hierarchical model. To summarize the content of video, a video abstract is developed. The experimental evaluation demonstrates the effectiveness of the approaches discussed in this paper.
This paper is financially supported by Natural Science Foundation of Hubei Province (2004AA101C94).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Fayyad, U.: Data Mining and Knowledge Discovery in Database: Implications for Scientific databases. In: Proceeding of Ninth International Conference on Scientific and Statistical Database Management, pp. 2–11 (1997)
Chen, M.S., Han, J., Yu, P.S.: Data mining: An Overview from a Database Perspective. IEEE Transactions on Knowledge and Data Engineering 8(6), 866–883 (1996)
Pan, J.-Y., Faloutsos, C.: VideoCube: A New Tool for Video Mining and Classification. In: ICADL, vol. 12 (2002)
Zhu, X., Aref, W.G., Fan, J., Catlin, A.C., Elmagarmid, A.K.: Medical Video Mining for Efficient Database Indexing, Management and Access. In: ICDE, pp. 569–580 (2003)
Zhu, X., Wu, X.: Sequential Association Mining for Video Summarization. In: Proceedings of International Conference on Multimedia and Expo, pp. 333–336 (2003)
Mohan, R.: Text-based Search of TV News Stories. In: SPIE Proc. of Multimedia and Archiving Systems, pp. 2–13. SPIE Press, NJ (1996)
Chen, L., Faudemay, P.: Multi-Criteria Video Segmentation for TV News. In: Proc. of 1st Multimedia Signal Processing Workshop, pp. 319–324. IEEE Press, NJ (1997)
Zhang, H.J., Tan, S.Y., Smoliar, S.W.: Automatic Parsing and Indexing of News Video. Multimedia Systems (2), 256–266 (1995)
Hauptmann, A, Witbrock, M.: Story Segmentation and Detection of Commercials in Broadcast News Video (October 2000), http://www.ieee.org/ieeexplore
Hauptman, A.G., Smith, M.: Text, Speech and Vision for Video Segmentation: The Informedia Project. In: Working Notes of IJCAL Workshop on Intelligent Multimedia Information Retrieval, pp. 17–22. IEEE Press, NJ (1995)
Huang, J., Liu, Z., Wang, Y., Chen, Y.: Integration of Multimedia Features for Video Classification Based on HMM (October 2000), http://vision.poly.edu
Liu, Z., Huang, Q., Rosenberg, A.: Automated Generation of News Content Hierarchy by Intetrating Audio, Video, and Text Information. In: ICASSP 1999, pp. 3025–3028. IEEE Press, NJ (1999)
Huang, J., Liu, Z., Wang, Y.: Integration of Audio and Visual Information for Content-based Video Segmentation and Classification. Journal of VLSI Signal Processing System for Signal, Image, and Video Technology 20(2), 61–79 (1998)
Junqing, Y.: Research of Content-Based Video Abstract. Wuhan University, Wuhan (2002)
Weiqiang, W., Wen, G.: Automatic Parsing of News Video Using Multimodal Analysis. Journal of Software 12(9), 1271–1278 (2001)
Lienhart, R., Pfeiffer, S., Effelsberg, W.: Video Abstracting. Communications of the ACM 40(12), 55–62 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, J., He, Y., Li, S. (2005). Content-Based News Video Mining. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_52
Download citation
DOI: https://doi.org/10.1007/11527503_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27894-8
Online ISBN: 978-3-540-31877-4
eBook Packages: Computer ScienceComputer Science (R0)