Definition of the gestures and their meanings [UPDATE 31/05]

At this point, we are able to describe the gestures that we considered to form the main block of our system. As Pablo and Sverrir show before, there isn't any protocol or steps that must be follow to configure the final order, due to the back end of the program is able to identify the gesture and classify it depending on the gestures that the user did.

Now, we are using only 8 different gestures, minimum number described in the requirement paper of this project. Furthermore, is important to remember that all the gestures begin in the same position due to the Leap Motion module sometimes fails detecting the real position of the hand and fingers.

The initial position is:

Picture	Gesture Description
	Initial All the gestures begins with the same static gesture.

From this we can achieve this others:

Picture	Gesture Description
	CIRCLE Select pasta as a meal
	PISTOL Drink cola
	PINKY Pay with cash
	ROLL Cancel the last selection

Picture	Gesture Description
	ROCK Select hamburger as a meal
	SCISSORS Drink Cocktail
	COME Pay with card
	STOP Accept the order. Confirmation.

Recording all the samples to the neural network we figured out that there is a problem with the Leap Motion module. That mean, when we introduce the user hand into the range of the module (as you can see in the 'Initial Position' picture) is it possible that the output data could be with not the correct roll value. This is, if the value expected is 0º, we read 180º proximately. Indeed, unless the system detect this problematic initial position, is impossible to continue with the complete gesture; the result will not be the correct one.
Furthermore, recognizing the position of the fingers suppose other point of fault because sometimes the module misunderstand which is the extended finger.

This non-deseable scenarios change all the steps to record the samples because a preprocessing is needed using the visualization and the input data, which the program use to train the neural network.