Clique-graph Matching by Preserving Global & Local Structure

This study proposes the clique-graph and further presents a clique-graph matching method by preserving global and local structures. Especially, we formulate the objective function of clique-graph matching with respective to two latent variables, the clique information in the o- riginal graph and the pairwise clique correspondence constrained by the one-to-one matching. Since the objective function is not jointly convex to both latent variables, we decompose it into two consecutive steps for optimization: 1) clique-to-clique similarity measure by preserving local unary and pairwise correspondences; 2) graph-to-graph similarity measure by preserving global clique-to-clique correspondence. Extensive experiments on the synthetic data and real images show that the proposed method can outperform representative methods especially when both noise and outliers exist. You can download the paper is here.


Weizhi Nie Anan Liu Zan Gao Yuting Su


Available at Here

Experiment Results in Virtual dataset

Experiment Results in Real Image

Tianjin University

Last update: 23/12/2014