Subgraph Matching with Semidefinite Programming

We present a convex programming approach to the problem of matching subgraphs which represent object views against larger graphs which represent scenes. Starting from a linear programming formulation for computing optimal matchings in bipartite graphs, we extend the linear objective function in order to take into account the relational constraints given by both graphs. The resulting combinatorial optimization problem is approximately solved by a semidefinite program. Preliminary results are promising with respect to view-based object recognition subject to relational constraints.