An evaluation of recent graph matching algorithms

Yulong Tian, Yuncai Liu
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Abstract

Graph matching is a fundamental problem in computer vision and image processing and is widely used in object detection. Recently, many methods formulate it as integer quadratic programming problem to find inexact solutions by relaxing it in continuous domain. In this paper we classify these methods in 3 categories based on the relaxed constraints, hypothesis, solving methods, and convergence properties separately. For evaluation purpose we modify these methods and add some toy modifications to compare the detail configuration of these algorithms under different situations. Finally we try to give some explanation based on experimental results.
最近的图匹配算法的评价
图匹配是计算机视觉和图像处理中的一个基本问题,在目标检测中有着广泛的应用。近年来,许多方法将其表述为整数二次规划问题,在连续域上松弛求非精确解。本文分别根据松弛约束、假设、求解方法和收敛性将这些方法分为三类。为了评估目的,我们对这些方法进行了修改,并添加了一些简单的修改,以比较这些算法在不同情况下的详细配置。最后,结合实验结果对其进行了解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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