A Short Survey of Recent Advances in Graph Matching
A Short Survey of Recent Advances in Graph Matching
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DOI：
10.1145/2911996.2912035
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发表时间：
2016-06
期刊：
影响因子：
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通讯作者：
Junchi Yan;Xu-Cheng Yin;Weiyao Lin;Cheng Deng;H. Zha;Xiaokang Yang
中科院分区：
文献类型：
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作者：
Junchi Yan;Xu-Cheng Yin;Weiyao Lin;Cheng Deng;H. Zha;Xiaokang Yang
图匹配是指寻找图的顶点之间的最佳对应以最小化（最大化）它们的节点和边的不一致（仿射）的一类计算问题，是计算机科学中的一个基本问题，并且涉及到许多领域，例如组合数学、模式识别、多媒体和计算机视觉。与理论上经常考虑的精确图（子）同构相比，不精确加权图匹配由于其灵活性和实用性而受到更多的关注。一个简短的回顾最近的研究活动有关（不精确）加权图匹配，详细介绍了方法，配方和算法。它突出了几个关键的子弹下的方法，例如，有多少图涉及，如何建立亲和力，如何探索的问题顺序，以及如何进行匹配过程等，此外，研究活动在最前沿的图匹配应用程序，特别是在计算机视觉，多媒体和机器学习的报告。其目的是提供一个系统的和紧凑的框架，关于最近的发展和目前的国家的最先进的图匹配。
Graph matching, which refers to a class of computational problems of finding an optimal correspondence between the vertices of graphs to minimize (maximize) their node and edge disagreements (affinities), is a fundamental problem in computer science and relates to many areas such as combinatorics, pattern recognition, multimedia and computer vision. Compared with the exact graph (sub)isomorphism often considered in a theoretical setting, inexact weighted graph matching receives more attentions due to its flexibility and practical utility. A short review of the recent research activity concerning (inexact) weighted graph matching is presented, detailing the methodologies, formulations, and algorithms. It highlights the methods under several key bullets, e.g. how many graphs are involved, how the affinity is modeled, how the problem order is explored, and how the matching procedure is conducted etc. Moreover, the research activity at the forefront of graph matching applications especially in computer vision, multimedia and machine learning is reported. The aim is to provide a systematic and compact framework regarding the recent development and the current state-of-the-arts in graph matching.