Automatic web image selection with a probabilistic latent topic model

ABSTRACT

We propose a new method to select relevant images to the given keywords from images gathered from theWeb based on the Probabilistic Latent Semantic Analysis (PLSA) model which is a probabilistic latent topic model originally proposed for text document analysis. The experimental results shows that the results by the proposed method is almost equivalent to or outperforms the results by existing methods. In addition, it is proved that our method can select more various images compared to the existing SVM-based methods.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.m Miscellaneous

General Terms:
Algorithms, Experimentation

Keywords:
image recognition, web image mining