Given two feature points sets, we define Laplace matrices respectively, analysis the eigenvalues and eigenvectors of the matrices, and obtain the initial correspondence probabilities. Then; the final matching results are acquired by using the method of probabilistic relaxation.
该方法首先给定两个特征点集，然后分别定义其Laplace矩阵，再通过分析该矩阵的特征值及特征向量来获得特征点匹配的初始概率，最后通过概率松弛迭代的方法获得匹配的最终解。
参考来源 - 基于图谱理论的图像匹配和图像分割算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Lastly, the probabilistic relaxation iteration algorithm is used to optimize the information after fully considering the context information.
最后充分考虑上下文信息，利用概率松弛迭代算法对粗检测信息进行优化。
This paper presents an algorithm of point correspondence in which the spectral theory, partial characteristics of points and the method of probabilistic relaxation are combined.
文章提出了一种将谱图理论、特征点的局部特征和概率松弛法相结合的特征点匹配算法。
A novel algorithm for point correspondence is proposed, which combines graph spectral analysis and partial characteristics of the point together via the method of probabilistic relaxation.
文章提出了一种将谱图理论、特征点的局部特征和概率松弛法相结合的特征点匹配算法。
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