Search-Based Automatic Web Image Annotation Using Latent Visual and Semantic Analysis

  • Authors:

  • Dingyin Xia;Fei Wu;Yueting Zhuang

  • Affiliations:

  • College of Computer Science and Technology, Zhejiang University, China;College of Computer Science and Technology, Zhejiang University, China;College of Computer Science and Technology, Zhejiang University, China

  • Venue:
  • PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
  • Year:
  • 2008

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Abstract

Automatic web image annotation is a practical and effective way for both web image retrieval and image understanding. In this paper, we proposed a search-based automatic web image annotation using latent visual and semantic analysis. At first, the semantic content of web images and visibility of the words are combined to compute the probability that the initial annotations are present in the images. And then, it is extended by using latent visual and semantic analysis to find the synonyms of initial annotations. The final rankings are estimated by using commercial image search engines by mining content-based correlation. Experiments conducted on real-world web images demonstrate the effectiveness of the proposed approach.