Gesture Recognition Toolkit
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.
- 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)
- Windows (Tested on Windows XP, Windows 7)
- OS X (Tested on 10.7)
- Linux (Tested on Ubuntu 12)
Some example code demonstrating how to create a new gesture recognition pipeline, add a pre-processing modules, two feature-extraction modules, an ANBC classifier module, and a post-processing module, load some training and test data, and then train and test the pipeline.
GRT Machine Learning Algorithms
The current development build of the GRT contains machine-learning algorithms such as:
- Adaptive Naive Bayes Classifier
- K-Nearest Neighbor Classifier
- Dynamic Time Warping
- Support Vector Machine
- Artificial Neural Network (Multi Layer Perceptron)
GRT Supporting Algorithms
In addition to the machine-learning algorithms, the GRT also contains a large number of pre-processing, post-processing, and feature-extraction algorithms such as:
- Low Pass Filter
- High Pass Filter
- Moving Average Filter
- Derivative
- Zero Crossing
- FFT
- Class Label Filter
- Class Label Timeout Filter
GRT Wiki
The GRT has not yet been officially released but a development version can be downloaded from googlecode: GRT and also on the GRT Wiki.
You can find the main GRT Wiki here, which includes tutorials, code examples, and instuctions on how to download and integrate the GRT in your own c++ projects.
The wiki also features a guide to getting started if you've never used machine learning or gesture recognition before.