Multiscale conditional random fields for image labeling

  title={Multiscale conditional random fields for image labeling},
  author={Xuming He and Richard S. Zemel and Miguel {\'A}. Carreira-Perpi{\~n}{\'a}n},
  journal={Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.},
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a probabilistic framework, which combines the outputs of several components. Components differ in the information they encode. Some focus on the image-label mapping, while others focus solely on patterns within the label field. Components also differ in their scale, as some focus on fine-resolution patterns while others… CONTINUE READING
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