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Large scale news video database browsing and retrieval via information visualization

Published: 11 March 2007 Publication History

Abstract

In this paper, we have developed a novel framework to enable more effective visual analysis and retrieval of large-scale news videos via interactive visualization, so that the audiences can find news stories of interest at first glance. Keyframes and keywords are automatically extracted from news video clips and visually represented according to their interestingness measurement and relations. A computational approach is also developed to quantify the interestingness measurement of video clips. Our experimental results have shown that our techniques for intelligent news video analysis have the capacity to enable more effective visualization and retrieval of large-scale news videos. Our visualization-based news video analysis and retrieval system is very useful for security applications and for general audiences to quickly find the news stories of interest from large-scale news videos among many channels.

References

[1]
A. W. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, "Content-base image retrieval at the end of the early years," IEEE Trans. on PAMI, vol. 22, pp. 1349--1380, December 2000.
[2]
N. Dimitrova, H.-J. Zhang, B. Shahraray, I. Sezan, T. Huang, and A. Zakhor, "Applications of video-content analysis and retrieval," IEEE MultiMedia, vol. 9, no. 3, pp. 42--55, 2002.
[3]
J. Wagstaff, "On news visualization," http://www.loosewireblog.com/2005/05/on_news_visuali.html, 2005.
[4]
H. Luo, J. Fan, J. Yang, W. Ribarsky, and S. Satoh, "Exploring large-scale video news via interactive visualization," in IEEE VAST 2006, 10 2006.
[5]
H. Luo and J. Fan, "Concept-oriented video skimming and adaptation via semantic classification (poster paper)," in ACM Multimedia Workshop on MIR, (New York), October 2004.

Cited By

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  • (2011)A middleware to enhance current multimedia retrieval systems with content-based functionalitiesMultimedia Systems10.1007/s00530-010-0217-617:2(149-164)Online publication date: 1-Mar-2011
  • (2008)An integrated approach to video retrievalProceedings of the nineteenth conference on Australasian database - Volume 7510.5555/1378307.1378320(49-55)Online publication date: 1-Jan-2008

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cover image ACM Conferences
SAC '07: Proceedings of the 2007 ACM symposium on Applied computing
March 2007
1688 pages
ISBN:1595934804
DOI:10.1145/1244002
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 March 2007

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Author Tags

  1. semantic video classification
  2. video visualization

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

View all
  • (2011)A middleware to enhance current multimedia retrieval systems with content-based functionalitiesMultimedia Systems10.1007/s00530-010-0217-617:2(149-164)Online publication date: 1-Mar-2011
  • (2008)An integrated approach to video retrievalProceedings of the nineteenth conference on Australasian database - Volume 7510.5555/1378307.1378320(49-55)Online publication date: 1-Jan-2008

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