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Extending Continuous Cuts: Anisotropic Metrics and Expansion Moves

Författare

Summary, in English

The concept of graph cuts is by now a standard method for all sorts of low level vision problems. Its popularity is largely due to the fact that globally or near globally optimal solutions can be computed using efficient max flow algorithms. On the other hand it has been observed that this method may suffer from metrication errors. Recent work has begun studying continuous versions of graph cuts, which give smaller metrication errors. Another advantage is that continuous cuts are straightforward to parallelize. In this paper we extend the class of functionals that can be optimized in the continuous setting to include anisotropic TV-norms. We show that there is a so called coarea formula for these functionals making it possible to minimize them by solving a convex problem. We also show that the concept of α-expansion moves can be reformulated to fit the continuous formulation, and we derive approximation bounds in analogy with the discrete case. A continuous version of the Potts model for multi-class segmentation problems is presented, and it is shown how to obtain provably good solutions using continuous α-expansions.

Avdelning/ar

Publiceringsår

2009

Språk

Engelska

Sidor

405-412

Publikation/Tidskrift/Serie

Proceedings of 2009 IEEE 12th International Conference on Computer Vision (ICCV)

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Conference name

IEEE International Conference on Computer Vision (ICCV), 2009

Conference date

2009-09-27 - 2009-10-04

Conference place

Kyoto, Japan

Status

Published

Forskningsgrupp

  • Mathematical Imaging Group

ISBN/ISSN/Övrigt

  • ISBN: 978-1-4244-4419-9