Maximum flows by incremental breadth-first search

Authors:
Andrew V. Goldberg;Sagi Hed;Haim Kaplan;Robert E. Tarjan;Renato F. Werneck
Affiliations:
Microsoft Research Silicon Valley;Tel Aviv University;Tel Aviv University;Princeton University and HP Labs;Microsoft Research Silicon Valley
Venue:
ESA'11 Proceedings of the 19th European conference on Algorithms
Year:
2011

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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.