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231225s2019 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2018.2819675
|2 doi
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Ajanthan, Thalaiyasingam
|e verfasserin
|4 aut
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| 245 |
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|a Memory Efficient Max Flow for Multi-Label Submodular MRFs
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|c 2019
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Revised 20.11.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Multi-label submodular Markov Random Fields (MRFs) have been shown to be solvable using max-flow based on an encoding of the labels proposed by Ishikawa, in which each variable Xi is represented by l nodes (where l is the number of labels) arranged in a column. However, this method in general requires 2 l2 edges for each pair of neighbouring variables. This makes it inapplicable to realistic problems with many variables and labels, due to excessive memory requirement. In this paper, we introduce a variant of the max-flow algorithm that requires much less storage. Consequently, our algorithm makes it possible to optimally solve multi-label submodular problems involving large numbers of variables and labels on a standard computer
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|a Journal Article
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| 700 |
1 |
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|a Hartley, Richard
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Salzmann, Mathieu
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 41(2019), 4 vom: 26. Apr., Seite 886-900
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
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| 773 |
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|g volume:41
|g year:2019
|g number:4
|g day:26
|g month:04
|g pages:886-900
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|u http://dx.doi.org/10.1109/TPAMI.2018.2819675
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|d 41
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