一种基于谱相关性的概率松弛匹配算法

Matching Algorithm Based on Probabilistic Relaxation of Spectral Correlation

为了可靠实现点模式匹配,提出了一种基于谱相关性的概率松弛匹配算法。先根据待匹配点集的形状上下文计算初始匹配概率,然后由待匹配点集构造亲近矩阵并进行奇异值分解,将得到的谱的相关性作为初始支持度。最后利用概率松弛迭代方法实现两个点集之间的匹配。实验结果表明该算法匹配精度较高。

To match reliably point pairs,a matching algorithm based on the probabilistic relaxation of the spectral correlation is proposed.Firstly,the initial matching probabilities are obtained from the shape context of the two point sets.Then,two proximity matrices are defined from the point sets respectively,and the spectral correlation of the matrices as the initial support is acquired by the singular value decomposion（SVD）.Finally,the matching of the two point sets is implemented by using the method of probabilistic relaxation.Experimental results show the high accuracy of the algorithm.