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文件名称:fgm_2012_05_12

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    2016-06-11
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    7.42mb
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介绍说明--下载内容来自于网络,使用问题请自行百度

分解图匹配(Factorized Graph Matching)源码-Graph matching (GM) is a fundamental problem in computer science, and it plays a central role to solve correspondence

problems in computer vision. GM problems that incorporate pairwise constraints can be formulated as a quadratic assignment problem

(QAP). Although widely used, solving the correspondence problem through GM has two main limitations: (1) the QAP is NP-hard and

difficult to approximate (2) GM algorithms do not incorporate geometric constraints between nodes that are natural in computer vision

problems. To address aforementioned problems, this paper proposes factorized graph matching (FGM). FGM factorizes the large

pairwise affinity matrix into smaller matrices that encode the local structure of each graph and the pairwise affinity between edges.

Four are the benefits that follow this factorization: (1) There is no need to compute the costly (in space and time) pairwise affinity

matrix (2) The factorization allows the use of a path-following optimization algorithm
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下载文件列表

fgm/
fgm/.DS_Store
__MACOSX/
__MACOSX/fgm/
__MACOSX/fgm/._.DS_Store
fgm/addPath.m
__MACOSX/fgm/._addPath.m
fgm/data/
fgm/data/.DS_Store
__MACOSX/fgm/data/
__MACOSX/fgm/data/._.DS_Store
fgm/data/cmum/
fgm/data/cmum/.DS_Store
__MACOSX/fgm/data/cmum/
__MACOSX/fgm/data/cmum/._.DS_Store
fgm/data/cmum/house/
fgm/data/cmum/house/.DS_Store
__MACOSX/fgm/data/cmum/house/
__MACOSX/fgm/data/cmum/house/._.DS_Store
fgm/data/cmum/house/images/
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