pygmtools.multi_graph_solvers
Classic (learning-free) multi-graph matching solvers. These multi-graph matching solvers are recommended to solve the joint matching problem of multiple graphs.
Note
Multi-graph matching means jointly matching \(\geq\) 3 graphs. It is different from two-graph matching because multi-graph matching is a more challenging problem and requires different solvers.
What makes multi-graph matching more challenging is the so-called cycle-consistency constraint: a multi-graph
matching solution has to be cycle-consistent, meaning that any pairwise matching result should be the same as
the result propagated from a third graph. For example, denote \(\mathbf{X}_{i,j}\) as the matching matrix
between graph i and graph j, it requires
\(\forall i,j,k, \mathbf{X}_{i,j} = \mathbf{X}_{i,k} \mathbf{X}_{k,j}\).
Such an extra constraint offers an extra source of information, but makes the problem itself more challenging
to solve.
Functions
Composition based Affinity Optimization (CAO) solver for multi-graph matching. |
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Graduated Assignment-based multi-graph matching solver. |
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Multi-Graph Matching based on Floyd shortest path algorithm. |