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A general non-linear method for modelling shape and locating image objects

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5 Author(s)
Lanitis, A. ; Dept. of Med. Biophys., Manchester Univ., UK ; Sozou, P.D. ; Taylor, C.J. ; Cootes, T.F.
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Objects of the same class often exhibit variation in shape. This shape variation has previously been modelled by means of point distribution models (PDMs) in which there is a linear relationship between a set of shape parameters and the positions of points on the shape. Here we present a new form of PDM, which uses a multilayer perceptron (MLP) to carry out nonlinear principal component analysis. We demonstrate that MLP-PDMs can model the shape variability in classes of object for which the linear model fails. We describe the use of MLP-PDMs in image search and present quantitative results for a practical application (face recognition), demonstrating the ability to locate image structures accurately starting from a very poor initial approximation to their pose and shape

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996