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A new attributed relational graph matching algorithm using the nested structure of earth mover's distance

机译:一种新的归属关系图匹配算法使用地球移动器距离的嵌套结构

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In general, object features can be represented as the nodes in attributed relational graph (ARG) with the connecting edges implying their relations. Therefore, the ARG matching plays a significant role in object recognition. Actually, the ARG matching can be implemented as a 2-step procedure, composed of constructing a distance matrix and establishing the correspondence based on the distance matrix, which seems to be similar to the point matching procedure. In this paper, we present a new ARG matching algorithm using the nested structure of earth mover's distance (EMD). More specifically, the nested structure of the EMD consists of inner EMD and outer EMD: The inner EMD reflects the difference of both nodes and edges between a pair of nodes in two ARG's in a perceptual manner, and the outer EMD establishes the correspondence between nodes in the two ARG's in a natural way. In order to demonstrate the robustness of the proposed algorithm against noise, we have conducted synthetic experiments for fully connected and undirected ARG's.
机译:通常,对象特征可以表示为属性关系图(arg)中的节点,其中连接边框暗示它们的关系。因此,arg匹配在对象识别中发挥着重要作用。实际上,Arg匹配可以实现为由构造距离矩阵并基于距离矩阵建立对应关系的2步骤,这似乎类似于点匹配过程。在本文中,我们使用地球移动器距离(EMD)的嵌套结构来提出了一种新的Arg匹配算法。更具体地,EMD的嵌套结构包括内部EMD和外部EMD:内部EMD以感知方式反映了两个arg中的一对节点之间的节点和边的差异,并且外部EMD在节点之间建立对应关系在两个arg的自然方式。为了展示所提出的抗噪声算法的稳健性,我们对完全连接和无向arg的合成实验进行了合成实验。

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