Abstract
Leap Motion is one of the most prominent and widely used hand tracking devices, solutions that make use of this device range from fields like education, health, or videogames, although it is not reported a tool that make easier the integration of the device with the development of applications controlled by hand gesture interfaces. An architecture is proposed alongside a set of gestures ready to be used in the development process of gesture interface applications. To support gesture recognition, skeletal information provided by Leap Motion is used in combination with a machine learning model.
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