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中文摘要：
提出了一种结合形状上下文分析的Laplace谱匹配算法。工作主要侧重于如何提高Laplace谱匹配算法对点的位置随机抖动的鲁棒性。首先,使用Laplace矩阵的特征向量和特征值以及双随机矩阵的方法计算初始匹配概率。然后,借助于概率松弛算法,将用形状上下文表示的局部相似性融入Laplace谱匹配算法以优化谱匹配的结果。对真实和合成数据的实验表明该方法具有比较高的精度。
英文摘要：
A Laplacian spectral method combined with shape context analysis was proposed for point pattern matching. This work mainly focused on the problem of how to render the Laplacian spectral method robust for random position jitter. Firstly, the initial correspondence probabilities were computed by using the eigenvectors and eigenvalues of the Laplacian matrix as well as the method of doubly stochastic matrix. Secondly, local similarity evaluated by shape context was embedded into the Laplacian spectral method to refine the results of spectral correspondence via a probabilistic relaxation approach. Experiments on both real-world and synthetic data demonstrate that the method possesses comparatively high accuracy.
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Sharp bounds of the zeroth-order general Randi? index of bicyclic graphs with given pendent vertices
The vertex (edge) independence number, vertex (edge) cover number and the least eigenvalue of a grap
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