ausblenden:
Schlagwörter:
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Zusammenfassung:
Recently, a family of global, non-submodular energy functions
has been proposed that is expressed as coupling edges
in a graph cut. This formulation provides a rich modelling
framework and also leads to efficient approximate inference
algorithms. So far, the results addressed binary random variables. Here, we extend these results to the multi-label case, and combine edge coupling with move-making algorithms.