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Correlative multi-label image annotation

  • US 7,996,762 B2
  • Filed: 02/13/2008
  • Issued: 08/09/2011
  • Est. Priority Date: 09/21/2007
  • Status: Active Grant
First Claim
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1. A method for correlative multi-label image annotation, the method comprising:

  • creating a concept feature modeling portion responsive to low-level features of an image to model connections between the low-level features of the image and individual concepts that are to be annotated;

    creating a concept correlation modeling portion to model correlations among at least a subset of the concepts that are to be annotated;

    forming a combination feature vector responsive to the concept feature modeling portion and the concept correlation modeling portion;

    solving a labeling function responsive to the combination feature vector to produce a concept label vector for the image, the concept label vector including label indicators respectively associated with the concepts that are to be annotated; and

    learning a classifier for the labeling function using a kernelized version of the combination feature vector that includes a dot product over at least a vector for low-level features of images to be classified.

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