Many methods of statistical shape description operate by describing shapes in terms of the variations inherent in a training set. This represents a limitation in that a training set must be assembled beforehand, and that only shapes lying within the span of the training data can be succinctly described. We develop a statistical representation that describes a shape in terms of the variations inherent in that shape, without reference to training images. Our new representation is then used to characterise a number of perceptual deformations, with the intent being to investigate how well such deformations can be captured and modelled by our description.


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    Titel :

    A spectral analysis of perceptual shape variation


    Beteiligte:
    Hughes, A. (Autor:in) / Wilson, R.C. (Autor:in)


    Erscheinungsdatum :

    01.01.2003


    Format / Umfang :

    560221 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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