Expectation Maximization of Gausian Mixture Models in VTK

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Expectation Maximization of Gausian Mixture Models in VTK

David Doria, “Expectation Maximization of Gausian Mixture Models in VTK“. The VTK Journal, September 2010

 

Expectation maximization (EM) is a common technique for estimating the parameters of a model after having collected observations of data generated by the model. We first explain the algorithm, then present our impelementation. We focus on estimation of the parameters of a Gaussian Mixture Model (GMM). The implementation is written in the VTK framework and is provided as a new class, vtkExpectationMaximization.

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