Contextual classification with functional Max-Margin Markov Networks

@article{Munoz2009ContextualCW,
  title={Contextual classification with functional Max-Margin Markov Networks},
  author={Daniel Munoz and J. Andrew Bagnell and Nicolas Vandapel and Martial Hebert},
  journal={2009 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2009},
  pages={975-982}
}
We address the problem of label assignment in computer vision: given a novel 3D or 2D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To this end, the Markov Random Field framework has proven to be a model of choice as it uses contextual information to yield improved classification results over locally independent classifiers. In this work we adapt a functional gradient approach for learning high-dimensional parameters of random fields in order to perform… CONTINUE READING
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Directional amn for 3-d point cloud classification

  • D. Munoz, N. Vandapel, M. Hebert
  • 3DPVT
  • 2008
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