  We address the correspondence search problem among multiple graphs with
complex properties while considering the matching consistency. We describe each
pair of graphs by combining multiple attributes, then jointly match them in a
unified framework. The main contribution of this paper is twofold. First, we
formulate the global correspondence search problem of multi-attributed graphs
by utilizing a set of multi-layer structures. The proposed formulation
describes each pair of graphs as a multi-layer structure, and jointly considers
whole matching pairs. Second, we propose a robust multiple graph matching
method based on the multi-layer random walks framework. The proposed framework
synchronizes movements of random walkers, and leads them to consistent matching
candidates. In our extensive experiments, the proposed method exhibits robust
and accurate performance over the state-of-the-art multiple graph matching
algorithms.
