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. © 2011 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Goldberg, A. V., Hed, S., Kaplan, H., Tarjan, R. E., & Werneck, R. F. (2011). Maximum flows by incremental breadth-First search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6942 LNCS, pp. 457–468). https://doi.org/10.1007/978-3-642-23719-5_39
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