Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling

@article{Kae2013AugmentingCW,
  title={Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling},
  author={Andrew Kae and Kihyuk Sohn and Honglak Lee and Erik G. Learned-Miller},
  journal={2013 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2013},
  pages={2019-2026}
}
Conditional random fields (CRFs) provide powerful tools for building models to label image segments. They are particularly well-suited to modeling local interactions among adjacent regions (e.g., super pixels). However, CRFs are limited in dealing with complex, global (long-range) interactions between regions. Complementary to this, restricted Boltzmann machines (RBMs) can be used to model global shapes produced by segmentation models. In this work, we present a new model that uses the combined… CONTINUE READING
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