Modelling Intermittently Present Features Using Nonlinear Point Distribution Models
We present in this paper a new compact model to represent a data set based on the main idea of the Point Distribution Model (PDM). Our model overcomes PDM in two aspects, first, it is not needed all the objects to have the same number of points. This is a very important feature, since in real applications, not all the landmarks are represented in the images. And second, the model captures the nonlinearity of the data set. Some research have been presented that couples both aspects separately but no model have been presented until now that couples them as a whole. A case study shows the efficiency of our model and its improvement respect the models in the literature.
KeywordsPoint Distribution Models intermittently present land-marks missing data statistical shape modelling imputation
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