Approximate labeling via graph cuts based on linear programming
A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the...
Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1998. - 29(2007), 8 vom: 14. Aug., Seite 1436-53 |
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Format: | Aufsatz |
Sprache: | English |
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2007
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Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
Schlagworte: | Journal Article |