Unsupervised and Supervised Visual Codes with Restricted Boltzmann Machines

@inproceedings{Goh2012UnsupervisedAS,
  title={Unsupervised and Supervised Visual Codes with Restricted Boltzmann Machines},
  author={Hanlin Goh and Nicolas Thome and Matthieu Cord and Joo-Hwee Lim},
  booktitle={ECCV},
  year={2012}
}
Recently, the coding of local features (e.g. SIFT) for image categorization tasks has been extensively studied. Incorporated within the Bag of Words (BoW) framework, these techniques optimize the projection of local features into the visual codebook, leading to state-of-theart performances in many benchmark datasets. In this work, we propose a novel visual codebook learning approach using the restricted Boltzmann machine (RBM) as our generative model. Our contribution is three-fold. Firstly, we… CONTINUE READING
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