Large-scale news video retrieval via visualization

  • Authors:
  • Hangzai Luo;Jianping Fan;Yuli Gao;William Ribarsky;Shin'ichi Satoh

  • Affiliations:
  • UNC-Charlotte;UNC-Charlotte;UNC-Charlotte;UNC-Charlotte;National Inst. of Informatics

  • Venue:
  • MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
  • Year:
  • 2006

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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.