点模式匹配谱图分析的一种新方法
首发时间:2011-05-05
摘要:点模式匹配在计算机视觉领域是一个很重要的研究课题,本文通过分析Scott和Longuet-Higgins,Shapiro和Brady两种点模式匹配谱图分析法的不足,提出了一种新的点模式匹配的谱图分析方法。方法的核心部分是构造了一种新的相似性矩阵,这种方法在图片大幅度转换和特征点抖动的情况下得到的结果要好于前面两种方法,在算法的复杂度上具有谱图法的优点,效率比近几年提出的一些需要迭代的方法高。本文提出的新方法经过了较为全面的测试,包括在合成数据和真实数据上的测试,都取得了较好的效果。
关键词: 计算机视觉 点模式匹配 图谱法 转换和对应 相似性矩阵
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A new approach of point set pattern matching using spectral graph method
Abstract:Point set matching is an essential part of many computer version tasks. This work analyzed the drawback of Scott and Longuet-Higgins method and Shapiro and Brady method, proposed a novel approach of graph spectral method. The most important part of this new method is constructing a new-type proximity matrix. This method does pretty well in the condition of large scale transformation and point-jitter of images, and has the advantages of graph spectral method: algorithmic complexity is better than iterative method proposed in last two decades. The new method proposed in this work were tested extensively in heterogeneous case, include synthetic data and real image taken from benchmark of computer version.
Keywords: Computer vision Point set matching Graph spectral method Transformations and correspondences Proximity matrix
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