Accounting for the Relative Importance of Objects in Image Retrieval

@inproceedings{Hwang2010AccountingFT,
  title={Accounting for the Relative Importance of Objects in Image Retrieval},
  author={Sung Ju Hwang and Kristen Grauman},
  booktitle={BMVC},
  year={2010}
}
We introduce a method for image retrieval that leverages the implicit information about object importance conveyed by the list of keyword tags a person supplies for an image. We propose an unsupervised learning procedure based on Kernel Canonical Correlation Analysis that discovers the relationship between how humans tag images (e.g., the order in which words are mentioned) and the relative importance of objects and their layout in the scene. Using this discovered connection, we show how to… CONTINUE READING

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