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Large-scale news video retrieval via visualization

Published: 23 October 2006 Publication History

Abstract

As the content of everyday news reports is unpredictable, keyword based news search engine can't provide effective services to audiences because the audiences may not be able to figure out proper keywords to search. In this paper, a novel framework is proposed to help audiences browse and retrieve news video clips without the need of keywords. Interesting keyframes and keywords are automatically extracted from news video clips and visually represented according to their interestingness and informativeness measurement. A computational approach is also developed to quantify the interestingness measurement of video clips. The keyframes and keywords are carefully organized so that the audiences can find news stories of interest at first glance.

References

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Jianping Fan, Hangzai Luo, and Ahmed K. Elmagarmid. Concept-oriented indexing of video database toward more effective retrieval and browsing. IEEE Trans. on Image Processing, 13, 2004.
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A. Hartmann and R. Lienhart. Automatic classification of images on the web. Proc. SPIE, 4676, 2002.
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A.K. Jain and B. Yu. Automatic text location in images and video frames. Pattern Recognition, 13(12):2055--2076, 1998.
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B. Li, K. Goh, and E. Chang. Confidence-based dynamic ensamble for image annotation and semantic discovery. ACM Multimedia, 2003.
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Hangzai Luo, Jianping Fan, Jin Yang, William Ribarsky, and Shin'ichi Satoh. Exploring large-scale video news via interactive visualization. In IEEE VAST 2006, 10 2006.
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Shin'ichi Satoh. News video analysis based on identical shot detection. In ICME, pages 69--72, 2002.
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Shin'ichi Satoh and Norio Katayama. An efficient implementation and evaluation of robust face sequence matching. In ICIAP'99, pages 266--271, 1999.

Cited By

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  • (2011)STREAMIT: Dynamic visualization and interactive exploration of text streams2011 IEEE Pacific Visualization Symposium10.1109/PACIFICVIS.2011.5742382(131-138)Online publication date: Mar-2011
  • (2007)Incorporating Concept Ontology for Hierarchical Video Classification, Annotation, and VisualizationIEEE Transactions on Multimedia10.1109/TMM.2007.9001439:5(939-957)Online publication date: 1-Aug-2007

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cover image ACM Conferences
MM '06: Proceedings of the 14th ACM international conference on Multimedia
October 2006
1072 pages
ISBN:1595934472
DOI:10.1145/1180639
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: 23 October 2006

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Author Tags

  1. semantic video classification
  2. video visualization

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MM06
MM06: The 14th ACM International Conference on Multimedia 2006
October 23 - 27, 2006
CA, Santa Barbara, USA

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all
  • (2011)STREAMIT: Dynamic visualization and interactive exploration of text streams2011 IEEE Pacific Visualization Symposium10.1109/PACIFICVIS.2011.5742382(131-138)Online publication date: Mar-2011
  • (2007)Incorporating Concept Ontology for Hierarchical Video Classification, Annotation, and VisualizationIEEE Transactions on Multimedia10.1109/TMM.2007.9001439:5(939-957)Online publication date: 1-Aug-2007

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