A Survey On Graph Matching In Computer Vision

Abstract

Graph matching (GM) which is the problem of finding vertex correspondence among two or multiple graphs is a fundamental problem in computer vision and pattern recognition. GM problem is a discrete combinatorial optimization problem. the property of this problem is NP-hard. Starting with a detailed introduction for modeling methods of graph matching. We walk through the recent development of two-graph matching and multi-graph matching. In two-graph matching, we focus on the continuous domain algorithms and briefly introduce the discrete domain algorithms. In the continuous domain method, we explain the method of transforming the problem from the discrete domain to the continuous domain and those state-of-the-arts algorithms in each type of algorithms in detail, including spectral methods, continuous methods, and deep learning methods. After two-graph matching, we introduce some typical multi-graph matching algorithms. In addition, the research activities of graph matching applications in computer vision and multimedia are displayed. In the end, several directions for future work are discussed.