Maximum flows by incremental breadth-First search

Andrew V. Goldberg; Sagi Hed; Haim Kaplan; Robert E. Tarjan; Renato F. Werneck

doi:10.1007/978-3-642-23719-5_39

Maximum flows by incremental breadth-First search

Andrew V. Goldberg^*, Sagi Hed, Haim Kaplan, Robert E. Tarjan, Renato F. Werneck

^*Corresponding author for this work

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

58 Scopus citations

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.

Original language	English
Title of host publication	Algorithms, ESA 2011 - 19th Annual European Symposium, Proceedings
Pages	457-468
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-642-23719-5_39
State	Published - 2011
Event	19th Annual European Symposium on Algorithms, ESA 2011 - Saarbrucken, Germany Duration: 5 Sep 2011 → 9 Sep 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6942 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th Annual European Symposium on Algorithms, ESA 2011
Country/Territory	Germany
City	Saarbrucken
Period	5/09/11 → 9/09/11

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10.1007/978-3-642-23719-5_39

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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 Algorithms, ESA 2011 - 19th Annual European Symposium, Proceedings (pp. 457-468). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6942 LNCS). https://doi.org/10.1007/978-3-642-23719-5_39

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title = "Maximum flows by incremental breadth-First search",

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.",

author = "Goldberg, {Andrew V.} and Sagi Hed and Haim Kaplan and Tarjan, {Robert E.} and Werneck, {Renato F.}",

year = "2011",

doi = "10.1007/978-3-642-23719-5_39",

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Goldberg, AV, Hed, S, Kaplan, H, Tarjan, RE & Werneck, RF 2011, Maximum flows by incremental breadth-First search. in Algorithms, ESA 2011 - 19th Annual European Symposium, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6942 LNCS, pp. 457-468, 19th Annual European Symposium on Algorithms, ESA 2011, Saarbrucken, Germany, 5/09/11. https://doi.org/10.1007/978-3-642-23719-5_39

Maximum flows by incremental breadth-First search. / Goldberg, Andrew V.; Hed, Sagi; Kaplan, Haim et al.
Algorithms, ESA 2011 - 19th Annual European Symposium, Proceedings. 2011. p. 457-468 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6942 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Maximum flows by incremental breadth-First search

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