692 research outputs found

    A probabilistic spectral framework for grouping and segmentation

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    Correspondence matching with modal clusters

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    The modal correspondence method of Shapiro and Brady aims to match point-sets by comparing the eigenvectors of a pairwise point proximity matrix. Although elegant by means of its matrix representation, the method is notoriously susceptible to differences in the relational structure of the point-sets under consideration. In this paper, we demonstrate how the method can be rendered robust to structural differences by adopting a hierarchical approach. To do this, we place the modal matching problem in a probabilistic setting in which the correspondences between pairwise clusters can be used to constrain the individual point correspondences. We demonstrate the utility of the method on a number of synthetic and real-world point-pattern matching problems
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