An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision

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 ef...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 26; no. 9; pp. 1124 - 1137
Main Authors:	Boykov, Y., Kolmogorov, V.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.09.2004 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Application software Artificial Intelligence Cluster Analysis Clustering algorithms Computer vision Energy Transfer graph algorithms Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image restoration Image segmentation Imaging, Three-Dimensional - methods Index Terms- Energy minimization Information Storage and Retrieval - methods Iterative algorithms Labeling maximum flow Minimization methods minimum cut multicamera scene reconstruction Pattern Recognition, Automated - methods Photogrammetry - methods Photography - methods Reproducibility of Results segmentation Sensitivity and Specificity Simulated annealing stereo Stereo vision Studies
ISSN:	0162-8828, 1939-3539
Online Access:	Get full text
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