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Tagging Image with Informative and Correlative Tags

  • Xiaoming Zhang
  • Heng Tao Shen
  • Zi Huang
  • Zhoujun Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6612)

Abstract

Automatic tagging can automatically label images with semantic tags to significantly facilitate multimedia search and organization. Existing tagging methods often use probabilistic or co-occurring tags, which may result in ambiguity and noise. In this paper, we propose a novel automatic tagging algorithm which tags a test image with an Informative and Correlative Tag (ICTag) set. The assigned ICTag set can provide a more precise description of the image by exploring both the information capability of individual tags and the tag-to-set correlation. Measures to effectively estimate the information capability of individual tags and the correlation between a tag and the candidate tag set are designed. To reduce the computational complexity, we also introduce a heuristic method to achieve efficient automatic tagging. The experiment results confirm the efficiency and effectiveness of our proposed algorithm.

Keywords

image tagging tag information capability tag correlation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xiaoming Zhang
    • 1
  • Heng Tao Shen
    • 2
  • Zi Huang
    • 2
  • Zhoujun Li
    • 1
  1. 1.School of computerBeihang UniversityBeijingChina
  2. 2.Information technology and electrical engineeringUniversity of QueenslandAustralia

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