Data driven mean-shift belief propagation for non-gaussian MRFs

@article{Park2010DataDM,
  title={Data driven mean-shift belief propagation for non-gaussian MRFs},
  author={Minwoo Park and Somesh Kashyap and Robert T. Collins and Yanxi Liu},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  year={2010},
  pages={3547-3554}
}
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale space theory, optimization of non-Gaussian, multimodal MRF models using DDMSBP becomes less sensitive to local maxima. This is a significant improvement over standard BP inference, and extends the range of methods that are computationally tractable. In particular, when pair-wise potentials are Gaussians, the time… CONTINUE READING

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