Expectation Maximization for Gaussian Mixture Model in OpenCV

I recently wrote code for Gaussian Mixture Model (GMM) based clustering in C++. As always, I found it much convenient to use OpenCV for manipulating matrices. Although there already exist an implementation of Expectation Maximization-based GMM, I tried to understand it by writing my own implementation.

The basic idea of GMM is to first randomly assign each sample to a cluster. This provides initial mixture model for clustering. This is then optimized using Expectation - or the probability/score of assigning each sample to each component in GMM - and Maximization - or updating the characteristics of each mixture component with the given probability/score . An attractive attribute of GMM is its ability to cluster data that does not have clear boundaries for clusters. This is achieved by having a probability/score for each sample from each cluster component.

What if I told you, you can use OpenCV code with Matlab mex!!

Matlab is probably one of the best tools for quickly prototyping and testing your research ideas. As quick and flexible it is, sometimes Matlab code can consume a lot of execution time. This is specifically a big hurdle when multiple experiments need to be run. A real-time execution alternative is to implement Matlab compatible C++ code and compile it with mex-compiler. While this works most of the time, it is well known that quickly implementing ideas in C++ is not possible.

Compiling OpenCV-3.0 with Matlab Support

A big uppercase HELLO to everyone!  I am back and after a long time (yet again) I am going to write a tutorial. The thing I am able to achieve here is awesome for us computer vision researchers. Yes! you heard it correct, exciting stuff.

I have been using OpenCV for quite sometime now. As good as it is for real-time computer vision applications, it can also be time consuming when it comes to exploring and implementing new research designs. Matlab on the other hand has always been flexible and a quick work around to achieve my research goals. The only problem, though, with matlab is that it is not real-time or even worse is that if you plan to implement code in OpenCV for real-time application, you would have to write the algorithms all over again as the usage of Matlab toolboxes is different than using the same methods in OpenCV.

Now comes the fun part, what if you can access OpenCV function calls within Matlab code? What if you can have easily transferable code from Matlab to C++?  This is all possible now with the OpenCV 3.0 Dev including matlab mex wrappers, which really is a good big step in the right direction. So lets start compiling the code.