Fisher Kernels on Visual Vocabularies for Image Categorization

@article{Perronnin2007FisherKO,
  title={Fisher Kernels on Visual Vocabularies for Image Categorization},
  author={Florent Perronnin and Christopher R. Dance},
  journal={2007 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2007},
  pages={1-8}
}
Within the field of pattern classification, the Fisher kernel is a powerful framework which combines the strengths of generative and discriminative approaches. The idea is to characterize a signal with a gradient vector derived from a generative probability model and to subsequently feed this representation to a discriminative classifier. We propose to apply this framework to image categorization where the input signals are images and where the underlying generative model is a visual vocabulary… CONTINUE READING
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