A method of controlling a mobile or stationary terminal comprising of the steps of one of multiple ways for 3D sensing a hand or face, recognizing the visual command input by trained hardware that does not incorporate instruction based programming and then causing some useful function to be performed by the recognized gesture on the terminal. This method is to enhance gross body gesture recognition in practice today. Gross gesture recognition has been made accessible by providing accurate skeleton tracking information down to the location of a person's hands or head. Notably missing from the skeleton tracking data, however, are the detailed positions of the person's fingers or facial gestures. Recognizing the arrangement of the fingers on a person's hand or expression on his or her face has applications in recognizing gestures such as sign language, as well as user inputs that are normally done with a mouse or a button on a controller. Tracking individual fingers or the subtleties of facial expressions poses many challenges, including the resolution of the depth camera, the possibility for fingers to occlude each other, or be occluded by the hand and performing these functions within the power and performance limitations of traditional coded architectures. This unique codeless, trainable hardware method can recognize finger gestures robustly and deal with these limitations. By recognizing facial expressions, additional information like approval, disapproval, surprise, commands and other useful inputs can be incorporated.
METHOD AND APPARATUS FOR DOING HAND AND FACE GESTURE RECOGNITION USING 3D SENSORS AND HARDWARE NON-LINEAR CLASSIFIERS