GestureApp Manual

Training

Before testing of recognition ability you must train the network (or you can load a file image of trained net). You can customize the parameters of training process namely: maximum number of cycles, a momentum value, a learning rate, a minimum value of mean square error (in other words "target error"). The training process will stop after achieving either of the condition: maximum number of cycles or target error. During training process, you can keep an eye on a error's graph, a current gesture (with noise) and 2D network presentation.

Testing

As soon as you have a trained net, you can test it. Select the patterns (or test all of them), a speed value and a noise level. Besides, you can familiarize oneself with ideal presentation of gestures via setting minimal noise and minimal speed.

Recognition

For recognition of mouse gestures you must press right mouse button during moving a mouse. For example for recognition "left" gesture, press right mouse button and move a mouse to the left. If a neural network can recognize the gesture, then you will see the name, probability and ideal presentation of winner. Because of freeware nature of GestureApp the mouse path must have at least 16 points :(. Sorry I didn't implemented a "stretch a path" feature so far.

Attention: the direction is very important.
The network is trained to recognize the gestures but not 2D images. Hence, you can draw the "circle" gesture via thousand different ways, but valid way is: press mouse button and move a mouse to the right and down and so on. Once more: it's gesture but not 2D image.

Mouse gestures


Send your question and comments to konstantin@mail.primorye.ru
The source code of GestureApp can be downloaded from www.codeproject.com or www.codeguru.com
Copyright (c) 2001 Konstantin Boukreev