New function for initializing a tensorGMM using k-means. Already tested.

init_tensorGMM_kmeans.m

+function model = init_tensorGMM_kmeans(Data, model)
+% Author:   Leonel Rozo, 2014
+%           http://programming-by-demonstration.org/LeonelRozo
+%
+
+diagRegularizationFactor = 1E-4;
+
+%Matricization/flattening of tensor
+DataAll = reshape(Data, size(Data,1)*size(Data,2), size(Data,3)); 
+
+%The function 'kmeans' below is from the Matlab Statistics Toolbox (see note above)
+[Data_id, Centers] = kmeans(DataAll', model.nbStates);
+
+% Setting means and covariance matrices
+Mu = Centers';
+Sigma = zeros(model.nbFrames*model.nbVar, model.nbFrames*model.nbVar, model.nbStates);
+for i = 1 : model.nbStates
+  idtmp = find(Data_id==i);
+  model.Priors(i) = length(idtmp);
+  Sigma(:,:,i) = cov(DataAll(:,idtmp)') + eye(size(DataAll,1))*diagRegularizationFactor;
+end
+model.Priors = model.Priors / sum(model.Priors);
+
+%Reshape GMM parameters into a tensor 
+for m = 1 : model.nbFrames
+  for i = 1 : model.nbStates
+    model.Mu(:,m,i) = Mu((m-1)*model.nbVar+1:m*model.nbVar,i); 
+    model.Sigma(:,:,m,i) = Sigma((m-1)*model.nbVar+1:m*model.nbVar,(m-1)*model.nbVar+1:m*model.nbVar,i); 
+  end
+end
+
+