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Many-to-Many Graph Matching via Metric Embedding

9 years 8 months ago
Many-to-Many Graph Matching via Metric Embedding
Graph matching is an important component in many object recognition algorithms. Although most graph matching algorithms seek a one-to-one correspondence between nodes, it is often the case that a more meaningful correspondence exists between a cluster of nodes in one graph and a cluster of nodes in the other. We present a matching algorithm that establishes many-to-many correspondences between nodes of noisy, vertex-labeled weighted graphs. The algorithm is based on recent developments in efficient lowdistortion metric embedding of graphs into normed vector spaces. By embedding weighted graphs into normed vector spaces, we reduce the problem of many-to-many graph matching to that of computing a distribution-based distance measure between graph embeddings. We use a specific measure, the Earth Mover's Distance, to compute distances between sets of weighted vectors. Empirical evaluation of the algorithm on an extensive set of recognition trials demonstrates both the robustness and e...
Yakov Keselman, Ali Shokoufandeh, M. Fatih Demirci
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2003
Where CVPR
Authors Yakov Keselman, Ali Shokoufandeh, M. Fatih Demirci, Sven J. Dickinson
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