Modelling Profiles with a Mixture of Gaussians
نویسندگان
چکیده
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data, to reduce the dimensionality of the representation. However, a single multivariate Gaussian model of the probability density, estimated from the principle covariances, can be substantially inaccurate. In this paper, we examine how the specificity of a model can be improved by using a mixture of Gaussians, trained with the ExpectationMaximization algorithm, with reference to hand and vehicle profiles.
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تاریخ انتشار 2000