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Coarse-to-Fine Minimization of Some Common Nonconvexities

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Book cover Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8932))

Abstract

The continuation method is a popular heuristic in computer vision for nonconvex optimization. The idea is to start from a simplified problem and gradually deform it to the actual problem while tracking the solution. There are many choices for how to map the nonconvex objective to some convex task. One popular principle for such construction is Gaussian smoothing of the objective function. This involves an integration which may be expensive to compute numerically. We argue that often simple tricks at the problem formulation plus some mild approximations can make the resulted task amenable to closed form integral.

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Authors and Affiliations

  1. Computer Science and Artificial Intelligence Lab. (CSAIL), Massachusetts Institute of Technology (MIT), USA

    Hossein Mobahi & John W. Fisher III

Authors
  1. Hossein Mobahi
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  2. John W. Fisher III
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Bergen, 7800, Bergen, Norway

    Xue-Cheng Tai

  2. Department of Mathematics, University of California, Los Angeles, CA, USA

    Egil Bae

  3. The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, S.A.R.

    Tony F. Chan

  4. Telemark University College, Postboks 203, 3901, Porsgrunn, Norway

    Marius Lysaker

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Mobahi, H., Fisher, J.W. (2015). Coarse-to-Fine Minimization of Some Common Nonconvexities. In: Tai, XC., Bae, E., Chan, T.F., Lysaker, M. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2015. Lecture Notes in Computer Science, vol 8932. Springer, Cham. https://doi.org/10.1007/978-3-319-14612-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-14612-6_6

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14611-9

  • Online ISBN: 978-3-319-14612-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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