Semantic knowledge extraction and annotation for web images

  • Authors:
  • Zhigang Hua;Xiang-Jun Wang;Qingshan Liu;Hanqing Lu

  • Affiliations:
  • Chinese Academy of Sciences, Beijing, P.R. China;Chinese Academy of Sciences, Beijing, P.R. China;Chinese Academy of Sciences, Beijing, P.R. China;Chinese Academy of Sciences, Beijing, P.R. China

  • Venue:
  • Proceedings of the 13th annual ACM international conference on Multimedia
  • Year:
  • 2005

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Abstract

Nowadays, images have become widely available on the World Wide Web (WWW). It's essential to develop effective ways for managing and retrieving such abundant images. Advantageously, compared to the traditional images where very little information is provided, the web images contain plentiful context data. This paper introduces a system that can automatically acquire semantic knowledge for web image annotation. By using a page layout analysis method that can precisely assign context to web images, we developed efficient algorithms to extract semantic knowledge for web images, such as description, people, temporal and geographic information. To validate the practicality and efficiency of this system, we applied it to about 6,500 images crawled from Web. Experiments demonstrated that our approach could achieve satisfactory results.