Expectation maximization in opencv

Question

My problem is this: I have to approximate a distribution with a mixture of two-component Gaussian model. In particular I need to two variances of the two Gaussian distributions. In openCv I can use the class EM; problem is that I can obtain only two covariance matrices but not the variances. Is there a solution in order to find variance values?

Answer 1

In 2D case you can imagine variance as radius of circle. Covariavce matrix defines ellipse semiaxes (eigen vectors (directions), and eigenvalues(lengths)), so the problem is can you transform ellipse to circle? If yes, then you should decide which way you'll do it. You can get as radius long or short axis of ellipse, or you can find average.