I have installed OpenCV and IntraFace, now the code can detect landmarks on the face, like this :

enter image description here

Now how can I convert this to a smile detector?

I have the landmark points as an array, so I should probably first find which ones belong to the mouth. How can I do that? Are there any tutorials for IntraFace? I could not find any.

Any help would be appreciated. Thanks !


IntraFace has an expression detector built in. However, if you would like to do a custom smile detector, then what you should do is to convert your spatial facial fiducial points to some kind of a feature vector, which could be input to a non-linear classifier such as SVM or MLP.

A trivial way to do this would be to use angular relations (if the face is fronto-parallel) or else you could use projective invariants such as cross ratio to find out the geometric relationships.

Two types of classifiers can be trained :

Two-Class: You would first prepare a training set of smiling and non-smiling people. Then train your learning machine with this input.

Novelty-Detection : If you use something like GMM or a variant of SVM you could model only the smile features (build a hyper-envolope around those features). And then during the runtime, you could query if the test feature falls into this hyper-envelope or not.

Finally, regarding the mouth part : You are right that it can help you, and IntraFace would have that built in. In the worst scenario, you might not need to separate anything. If you have a good training set you could as well run a dimensionality reduction on your features.

Of course there are more advanced methods published to accomplish what you like to do. Just as an example here.


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