Cue Integration for Figure/Ground Labeling

@inproceedings{Ren2005CueIF,
  title={Cue Integration for Figure/Ground Labeling},
  author={Xiaofeng Ren and Charless C. Fowlkes and Jitendra Malik},
  booktitle={NIPS},
  year={2005}
}
We present a model of edge and region grouping using a conditional random field built over a scale-invariant representation of images to integrate multiple cues. Our model includes potentials that capture low-level similarity, mid-level curvilinear continuity and high-level object shape. Maximum likelihood parameters for the model are learned from human labeled groundtruth on a large collection of horse images using belief propagation. Using held out test data, we quantify the information… CONTINUE READING
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