Gesture recognition with polyhedral conic functions based classifiers

Controlling a machine via detecting and recognising human gestures, becomes important technology especially using for remote controlling a device. In this study we carried about generating clustering based polyhedral conic functions algorithms, investigating and proposing a new method for the feature selection problem, which is very important for the applications like video processing, and finally implementing generated polyhedral conic functions based algorithms to the gesture recognition problem. In implementation step data needed for the classifiers are collected from the camera. The data obtained are used for generating classifiers based polyhedral conic functions and these classifiers are used successfully in the application.