{"intvolume":"        26","title":"An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision","publisher":"IEEE","doi":"10.1109/TPAMI.2004.60","author":[{"last_name":"Boykov","first_name":"Yuri","full_name":"Boykov, Yuri"},{"full_name":"Vladimir Kolmogorov","first_name":"Vladimir","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","last_name":"Kolmogorov"}],"publication_status":"published","day":"01","date_updated":"2021-01-12T07:41:36Z","abstract":[{"text":"Minimum cut/maximum flow algorithms on graphs have emerged as an increasingly useful tool for exactor approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time complexity. Their practical efficiency, however, has to date been studied mainly outside the scope of computer vision. The goal of this paper is to provide an experimental comparison of the efficiency of min-cut/max flow algorithms for applications in vision. We compare the running times of several standard algorithms, as well as a new algorithm that we have recently developed. The algorithms we study include both Goldberg-Tarjan style &quot;push -relabel&quot; methods and algorithms based on Ford-Fulkerson style &quot;augmenting paths.&quot; We benchmark these algorithms on a number of typical graphs in the contexts of image restoration, stereo, and segmentation. In many cases, our new algorithm works several times faster than any of the other methods, making near real-time performance possible. An implementation of our max-flow/min-cut algorithm is available upon request for research purposes.","lang":"eng"}],"_id":"3178","extern":1,"quality_controlled":0,"issue":"9","date_created":"2018-12-11T12:01:51Z","date_published":"2004-09-01T00:00:00Z","volume":26,"publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","year":"2004","page":"1124 - 1137","citation":{"ama":"Boykov Y, Kolmogorov V. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2004;26(9):1124-1137. doi:<a href=\"https://doi.org/10.1109/TPAMI.2004.60\">10.1109/TPAMI.2004.60</a>","ista":"Boykov Y, Kolmogorov V. 2004. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(9), 1124–1137.","ieee":"Y. Boykov and V. Kolmogorov, “An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 26, no. 9. IEEE, pp. 1124–1137, 2004.","mla":"Boykov, Yuri, and Vladimir Kolmogorov. “An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 26, no. 9, IEEE, 2004, pp. 1124–37, doi:<a href=\"https://doi.org/10.1109/TPAMI.2004.60\">10.1109/TPAMI.2004.60</a>.","short":"Y. Boykov, V. Kolmogorov, IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (2004) 1124–1137.","chicago":"Boykov, Yuri, and Vladimir Kolmogorov. “An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE, 2004. <a href=\"https://doi.org/10.1109/TPAMI.2004.60\">https://doi.org/10.1109/TPAMI.2004.60</a>.","apa":"Boykov, Y., &#38; Kolmogorov, V. (2004). An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE. <a href=\"https://doi.org/10.1109/TPAMI.2004.60\">https://doi.org/10.1109/TPAMI.2004.60</a>"},"status":"public","type":"journal_article","publist_id":"3507","month":"09"}