Multi-label classification for image annotation via sparse similarity voting

  title={Multi-label classification for image annotation via sparse similarity voting},
  author={Tomoya Sakai and Hayato Itoh and Atsushi Imiya},
  booktitle={ACCV Workshops},
We present a supervised multi-label classification method for automatic image annotation. Our method estimates the annotation labels for a test image by accumulating similarities between the test image and labeled training images. The similarities are measured on the basis of sparse representation of the test image by the training images, which avoids similarity votes for irrelevant classes. Besides, our sparse representation-based multi-label classification can estimate a suitable combination… CONTINUE READING


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