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图匹配算法

Graph Matching Algorithms
课程网址: http://videolectures.net/mlss05au_caelli_gma/  
主讲教师: Terry Caelli
开课单位: 澳大利亚信息通信技术研究中心
开课时间: 2007-04-25
课程语种: 英语
中文简介:
图匹配在计算机视觉到网络的许多计算领域中扮演着关键的角色,在这些领域中,需要确定两个属性化结构的组件(顶点和边缘)之间的对应关系。近年来,出现了三种新的图形匹配方法来替代传统的启发式方法。这些新方法是:*最小二乘法,其中根据导出集之间最佳拟合置换矩阵确定最佳对应关系。*光谱法-通过图特征空间中的子空间投影得出最佳对应。*图形模型-使用诸如连接树算法之类的算法来推断一个图的节点相对于另一个图的最佳标记,并满足顶点和边之间的相似性约束。在本课中,我们回顾和比较这些方法,并演示适用于点集和线匹配的示例。
课程简介: Graph matching plays a key role in many areas of computing from computer vision to networks where there is a need to determine correspondences between the components (vertices and edges) of two attributed structures. In recent years three new approaches to graph matching have emerged as replacements to more traditional heuristic methods. These new methods are: * Least squares - where the optimal correspondence in determined in terms of deriving the best fitting permutation matrix between sets. * Spectral methods - where optimal correspondences are derived via subspace projections in the graph eigenspaces. * Graphical models - where algorithms such as the junction tree algorithm are used to infer the optimal labeling of the nodes of one graph in terms of the other and that satisfy similarity constraints between vertices and edges. In this lecture we review and compare these methods and demonstrate examples where this applies to point set and line matching.
关 键 词: 图匹配; 光谱方法; 特征空间; 图形化模型; 结树算法
课程来源: 视频讲座网
最后编审: 2020-06-06:zyk
阅读次数: 63