GestureRecognitionToolkit  Version: 0.2.5
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
WeakClassifiers Directory Reference

Files

file  DecisionStump.cpp [code]
 
file  DecisionStump.h [code]
 This class implements a DecisionStump, which is a single node of a DecisionTree.
 
file  RadialBasisFunction.cpp [code]
 
file  RadialBasisFunction.h [code]
 This class implements a Radial Basis Function Weak Classifier. The Radial Basis Function (RBF) class fits an RBF to the weighted training data so as to maximize the number of positive training samples that are inside a specific region of the RBF (this region is set by the GRT::RadialBasisFunction::positiveClassificationThreshold parameter). After the RBF has been trained, it will output 1 if the input data is inside the RBF positive classification region, otherwise it will output 0.
 
file  WeakClassifier.cpp [code]
 
file  WeakClassifier.h [code]
 This is the main base class for all GRT WeakClassifiers.