Proceedings of the Korean Society of Broadcast Engineers Conference (한국방송∙미디어공학회:학술대회논문집)

The Korean Institute of Broadcast and Media Engineers (한국방송∙미디어공학회)
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COMMUNITY-GENERATED ONLINE IMAGE DICTORNARY

  • Li, Guangda (School of Computing National University of Singapore) ;
  • Li, Haojie (School of Computing National University of Singapore) ;
  • Tang, Jinhui (School of Computing National University of Singapore) ;
  • Chua, Tat-Seng (School of Computing National University of Singapore)
  • Published : 2009.01.12
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Abstract

Online image dictionary has become more and more popular in concepts cognition. However, for existing online systems, only very few images are manually picked to demonstrate the concepts. Currently, there is very little research found on automatically choosing large scale online images with the help of semantic analysis. In this paper, we propose a novel framework to utilize community-generated online multimedia content to visually illustrate certain concepts. Our proposed framework adapts various techniques, including the correlation analysis, semantic and visual clustering to produce sets of high quality, precise, diverse and representative images to visually translate a given concept. To make the best use of our results, a user interface is deployed, which displays the representative images according the latent semantic coherence. The objective and subjective evaluations show the feasibility and effectiveness of our approach.

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