Shape Modelling Using Markov Random Field Restoration of Point Correspondences

Rasmus Reinhold Paulsen, Klaus Baggesen Hilger

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    Abstract

    A method for building statistical point distribution models is proposed. The novelty in this paper is the adaption of Markov random field regularization of the correspondence field over the set of shapes. The new approach leads to a generative model that produces highly homogeneous polygonized shapes and improves the capability of reconstruction of the training data. Furthermore, the method leads to an overall reduction in the total variance of the point distribution model. Thus, it finds correspondence between semilandmarks that are highly correlated in the shape tangent space. The method is demonstrated on a set of human ear canals extracted from 3D-laser scans.
    Original languageEnglish
    Title of host publicationInformation Processing in Medical Imaging
    Publication date2003
    Pages1-12
    Publication statusPublished - 2003
    EventInformation Processing in Medical Imaging -
    Duration: 1 Jan 2003 → …

    Conference

    ConferenceInformation Processing in Medical Imaging
    Period01/01/2003 → …

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