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。
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。
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