As far as in my mind, there are three approaches that people have taken to detect hands using openCV, though not all of them have been tested by myself (a little shame). One is to use accurate HAAR-classifiers to locate and detect gestures which is considered as quite stable way but costing very much. Another is to use adaptive skin detection algorithms combined with motion analysis which seems easier to do than previous one. And the last is to use human skin colour segmentation to detect the contours of hands combined with hand convexity detection to recognise hands’ gestures [please refer to: hand gesture recognition using openCV].
HAAR-classifier database is rarely provided with open source projects. But we found some helpful papers which may give some thoughts of classifier training and test.
About hands database:
Application of classifiers:
Alternative skin detection based approach gesture recognition through angle space:
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