A Continuous Max-Flow Approach to Multi-Labeling Problems under Arbitrary Region Regularization
This enables more flexible multi-label segmentation for computer vision applications, though it appears incremental as it extends prior max-flow methods.
The paper tackled the limitation of existing max-flow segmentation models that only support specific region regularizations, by introducing Directed Acyclic Graphical Max-Flow (DAGMF) segmentation, which allows for arbitrary region regularization using directed acyclic graphs.
The incorporation of region regularization into max-flow segmentation has traditionally focused on ordering and part-whole relationships. A side effect of the development of such models is that it constrained regularization only to those cases, rather than allowing for arbitrary region regularization. Directed Acyclic Graphical Max-Flow (DAGMF) segmentation overcomes these limitations by allowing for the algorithm designer to specify an arbitrary directed acyclic graph to structure a max-flow segmentation. This allows for individual 'parts' to be a member of multiple distinct 'wholes.'