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Maximum Flows by Incremental Breadth-First Search

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Algorithms – ESA 2011 (ESA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6942))

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Abstract

Maximum flow and minimum s-t cut algorithms are used to solve several fundamental problems in computer vision. These problems have special structure, and standard techniques perform worse than the special-purpose Boykov-Kolmogorov (BK) algorithm. We introduce the incremental breadth-first search (IBFS) method, which uses ideas from BK but augments on shortest paths. IBFS is theoretically justified (runs in polynomial time) and usually outperforms BK on vision problems.

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Author information

Authors and Affiliations

  1. Microsoft Research Silicon Valley, USA

    Andrew V. Goldberg & Renato F. Werneck

  2. Tel Aviv University, Israel

    Sagi Hed & Haim Kaplan

  3. Princeton University and HP Labs, USA

    Robert E. Tarjan

Authors
  1. Andrew V. Goldberg
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  2. Sagi Hed
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  3. Haim Kaplan
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  4. Robert E. Tarjan
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  5. Renato F. Werneck
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica e Sistemistica, University of Rome " La Sapienza", via Ariosto 25, 00185, Roma, Italy

    Camil Demetrescu

  2. School of Computer Science, Reykjavik University, Menntavegur 1, 101, Reykjavik, Iceland

    Magnús M. Halldórsson

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© 2011 Springer-Verlag Berlin Heidelberg

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Goldberg, A.V., Hed, S., Kaplan, H., Tarjan, R.E., Werneck, R.F. (2011). Maximum Flows by Incremental Breadth-First Search. In: Demetrescu, C., Halldórsson, M.M. (eds) Algorithms – ESA 2011. ESA 2011. Lecture Notes in Computer Science, vol 6942. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23719-5_39

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  • DOI: https://doi.org/10.1007/978-3-642-23719-5_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23718-8

  • Online ISBN: 978-3-642-23719-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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