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Published in:
2005 | OriginalPaper | Chapter
A Linear Generative Model for Graph Structure
Authors : Bin Luo, Richard C. Wilson, Edwin R. Hancock
Published in: Graph-Based Representations in Pattern Recognition
Publisher: Springer Berlin Heidelberg
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This paper shows how to construct a linear deformable model for graph structure by performing principal components analysis (PCA) on the vectorised adjacency matrix. We commence by using correspondence information to place the nodes of each of a set of graphs in a standard reference order. Using the correspondences order, we convert the adjacency matrices to long-vectors and compute the long-vector covariance matrix. By projecting the vectorised adjacency matrices onto the leading eigenvectors of the covariance matrix, we embed the graphs in a pattern-space. We illustrate the utility of the resulting method for shape-analysis.