A comparative study of energy minimization methods for Markov random fields with smoothness-based priors
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation. It has been known for decades that such problems can be elegantly expressed as Markov random fields, yet the resulting...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 30(2008), 6 vom: 20. Juni, Seite 1068-80
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| 1. Verfasser: |
Szeliski, Richard
(VerfasserIn) |
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| Weitere Verfasser: |
Zabih, Ramin,
Scharstein, Daniel,
Veksler, Olga,
Kolmogorov, Vladimir,
Agarwala, Aseem,
Tappen, Marshall,
Rother, Carsten |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2008
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Comparative Study
Evaluation Study
Journal Article |
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