In this paper, we investigate the use of invariants derived from the heat kernel as a means of clustering graphs. We turn to the heat-content, i.e. the sum of the elements of the heat kernel. The heat content can be expanded as a polynomial in time, and the coefficients of the polynomial are known to be permutation invariants. We demonstrate how the polynomial coefficients can be computed from the Laplacian eigen-system. Graph-clustering is performed by applying principal components analysis to vectors constructed from the polynomial coefficients. We experiment with the resulting algorithm on the COIL database, where it is demonstrated to outperform the use of Laplacian eigenvalues.


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    Title :

    Clustering shapes using heat content invariants


    Contributors:
    Bai Xiao, (author) / Hancock, E.R. (author)


    Publication date :

    2005-01-01


    Size :

    327081 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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