Multi-resolution search with active shape models

We describe a multiresolution approach to image search using flexible shape models. This is an extension of work on active shape models (ASMs)-statistical models which iteratively deform to match image data. An ASM consists of a shape model controlling a set of landmark points, together with a stati...

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Bibliographic Details
Published inPattern Recognition, 1994 12th International Conference On. Vol. 1 Vol. 1; pp. 610 - 612 vol.1
Main Authors Cootes, T.F., Taylor, C.J., Lanitis, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1994
Subjects
Active shape model
Biomedical imaging
Biophysics
Deformable models
Image converters
Image resolution
Iterative methods
Pixel
Shape control
Statistics
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ISBN0818662654
9780818662652
DOI10.1109/ICPR.1994.576375

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Summary:We describe a multiresolution approach to image search using flexible shape models. This is an extension of work on active shape models (ASMs)-statistical models which iteratively deform to match image data. An ASM consists of a shape model controlling a set of landmark points, together with a statistical model of the grey-levels expected around each landmark. Both the shape model and the grey-level models are trained on sets of labelled example images. In order to apply a coarse-to-fine search strategy it is necessary to train a set of grey-level models for each landmark, one for every level of a multiresolution image pyramid. We demonstrate the approach and give results of quantitative experiments which show a significant increase in both speed, robustness and quality of fit compared to previous methods.
ISBN:0818662654
9780818662652
DOI:10.1109/ICPR.1994.576375