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I've been looking into implementations of Hidden Markov Models in C++ lately. I was wondering If I could use any of the existing HMM libraries written in C++ out there to use with Action Recognition (with OpenCV)?

I'm tying to AVOID "re-inventing the wheel"!

Is it possible to use Torch3Vision even though(looks like) it was designed to work for speech recognition?

My idea is that, if we can convert the feature vectors into Symbols/Observations (using Vector Quantization - Kmeans clustering), we can use those symbols for decoding, inference, parameter learning (Baum–Welch algorithm). This way it would work with Torch3Vision in OpenCV.

Any help on this will be truly appreciated.

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Best answer

You should check out this tutorial for the theory behind HMMs

It's quite simple to implement the algorithms by yourself.

For a C-based version, check out this implementation, which I've done for a Google Summer of Code project.

Hope this answer helps you!

If you want to know the real-world applications of Machine Learning, study about Machine Learning Tutorial and then you can go through this video:

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