Special Gesture Recognition Based on Adaboost Method.

The more camera and video capture devises are put in use, the higher request for non-touch gesture recognition becomes. In this article, based on the 0penCV2. 2 visual library and Visual Studio C + +, the authors implement the module of extracting Haar features and multi-scales classification with Adaboost to exploit special gesture recognition to meet this trend. Using the recognition and location of clench fist gesture in real time, the authors have completed the tracking of brush track through the location of gestures, and also worked out an algorithm to decrease the errors in detected points to make the brush go smoothly. According to the experiments, under the indoor condition, the recognition rate can achieve as good as 90%. [ABSTRACT FROM AUTHOR]