Refining graph matching using inherent structure information

Abstract

We present a graph matching refinement framework that improves the performance of a given graph matching algorithm. Our method synergistically uses the inherent structure information embedded globally in the active association graph, and locally on each individual graph. The combination of such information reveals how consistent each candidate match is with its global and local contexts. In doing so, the proposed method removes most false matches and improves precision. The validation on standard benchmark datasets demonstrates the effectiveness of our method.