Comment 72 for bug 507511

I have been thinking about this for a while, and working with OpenCV face detection seems to be quiet good, even if it not 100% accurate.

However, I am still struggling with a way to do face recognition. K a simple way, like using histogram is quiet easy, but what I have in mind is this:

The training of the classifier for the face recognition has to be done continually, e.i. the more it works the better it gets. Learns from itself. But I am struggling to find how that could be done. OpenCV has a haartraining and it would be nice if one could use it to update with the fresh set of the positive and negative data, that has been aquired in between last time the training was run and now. Then use current classifier with this data to produce new one, a better version of the old one. However, I don;t know wheather that is possible in current OpenCV haartraining.

Any other thought on how it could be done?