Corpus ID: 11129153

A Multiscale Framework for Challenging Discrete Optimization

@article{Bagon2012AMF,
  title={A Multiscale Framework for Challenging Discrete Optimization},
  author={Shai Bagon and Meirav Galun},
  journal={ArXiv},
  year={2012},
  volume={abs/1210.7070}
}
  • Shai Bagon, Meirav Galun
  • Published in ArXiv 2012
  • Computer Science, Mathematics
  • Current state-of-the-art discrete optimization methods struggle behind when it comes to challenging contrast-enhancing discrete energies (i.e., favoring different labels for neighboring variables). This work suggests a multiscale approach for these challenging problems. Deriving an algebraic representation allows us to coarsen any pair-wise energy using any interpolation in a principled algebraic manner. Furthermore, we propose an energy-aware interpolation operator that efficiently exposes the… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 17 REFERENCES

    On the Statistical Analysis of Dirty Pictures

    VIEW 9 EXCERPTS
    HIGHLY INFLUENTIAL

    Convergent Tree-Reweighted Message Passing for Energy Minimization

    • Vladimir Kolmogorov
    • Computer Science, Medicine
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • 2005
    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    MRF Energy Minimization and Beyond via Dual Decomposition

    VIEW 1 EXCERPT

    A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors

    VIEW 1 EXCERPT