The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library that has been specifically designed for real-time gesture recognition.
The GRT has been designed to:
be easy to use and integrate into your existing c++ projects
be compatible with any type of sensor or data input
be easy to rapidly train with your own gestures
be easy to extend and adapt with your own custom processing or feature extraction algorithms (if needed)
The GRT features a large number of algorithms that can be used to:
recognize static postures (such as if a user has their hands in a specific posture or if a device fitted with an accelerometer is being held in a distinct orientation)
recognize dynamic temporal gestures (such as a swipe or tap gesture)
perform regression (i.e. continually map an input signal to an output signal, such as mapping the angle of a user’s hands to the angle a steering wheel should be turned in a driving game)
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