31 July 2002 Eigenspaces for graphs from spectral features
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Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477068
Event: Second International Conference on Image and Graphics, 2002, Hefei, China
Abstract
In this paper we explore how to embed symbolic relational graphs with unweighted edges in eigenspaces. We adopt a graph-spectral approach. The leading eigenvectors of the graph adjacency matrix are used to define clusters of nodes. For each cluster, we compute vectors of spectral properties. We embed these vectors in a pattern-space using principal components analysis and multidimensional scaling techniques. We demonstrate both methods result in well-structured view spaces for graph-data extracted from 2D views of 3D objects.
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Bin Luo, Bin Luo, Richard C. Wilson, Richard C. Wilson, Edwin R. Hancock, Edwin R. Hancock, } "Eigenspaces for graphs from spectral features", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477068; https://doi.org/10.1117/12.477068
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