GestureRecognitionToolkit  Version: 1.0 Revision: 04-03-15
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
GRT Namespace Reference

Classes

class  AdaBoost
 
class  AdaBoostClassModel
 
class  ANBC
 
class  ANBC_Model
 
struct  AngleMagnitude
 
class  BAG
 
class  BernoulliRBM
 
class  Cholesky
 
class  CircularBuffer
 
class  ClassificationData
 
class  ClassificationResult
 
class  ClassificationSample
 
class  Classifier
 
class  ClassLabelAndTimer
 
class  ClassLabelChangeFilter
 
class  ClassLabelFilter
 
class  ClassLabelTimeoutFilter
 
class  ClassTracker
 
class  Clusterer
 
class  ClusterInfo
 
class  ClusterLevel
 
class  ClusterTree
 
class  ClusterTreeNode
 
class  CommandLineParser
 
class  Context
 
class  ContinuousHiddenMarkovModel
 
class  DeadZone
 
class  DebugLog
 
class  DebugLogMessage
 
class  DecisionStump
 
class  DecisionTree
 
class  DecisionTreeClusterNode
 
class  DecisionTreeNode
 
class  DecisionTreeThresholdNode
 
class  DecisionTreeTripleFeatureNode
 
class  Derivative
 
class  DiscreteHiddenMarkovModel
 
class  DoubleMovingAverageFilter
 
class  DTW
 
class  DTWTemplate
 
class  EigenvalueDecomposition
 
class  ErrorLog
 
class  ErrorLogMessage
 
class  EvolutionaryAlgorithm
 
class  Exception
 
class  FastFourierTransform
 
class  FeatureExtraction
 
class  FFT
 
class  FFTFeatures
 
class  FileParser
 
class  FiniteStateMachine
 
class  FIRFilter
 
class  FSMParticle
 
class  FSMParticleFilter
 
class  Gate
 
class  GaussianMixtureModels
 
class  GaussNeuron
 
class  GestureRecognitionPipeline
 
class  GMM
 
class  GRTBase
 
class  GuassModel
 
class  HierarchicalClustering
 
class  HighPassFilter
 
class  HMM
 
class  HMMTrainingObject
 
class  IndexDist
 
class  IndexedDouble
 
class  Individual
 
class  InfoLog
 
class  InfoLogMessage
 
class  KMeans
 
class  KMeansFeatures
 
class  KMeansQuantizer
 
class  KNN
 
class  LDA
 
class  LDAClassModel
 
class  LeakyIntegrator
 
class  LinearLeastSquares
 
class  LinearRegression
 
class  Log
 
class  LogisticRegression
 
class  LowPassFilter
 
class  LUDecomposition
 
class  Matrix
 
class  MatrixDouble
 
class  MeanShift
 
class  MedianFilter
 
class  MinDist
 
class  MinDistModel
 
class  MinMax
 
class  MixtureModel
 
class  MLBase
 
class  MLP
 
class  MovementDetector
 
class  MovementIndex
 
class  MovementTrajectoryFeatures
 
class  MovingAverageFilter
 
class  MultidimensionalRegression
 
class  Neuron
 
class  Node
 
class  Observer
 
class  ObserverManager
 
class  Particle
 
class  ParticleClassifier
 
class  ParticleClassifierGestureTemplate
 
class  ParticleClassifierParticleFilter
 
class  ParticleFilter
 
class  ParticleSwarmOptimization
 
class  PeakDetection
 
struct  PeakInfo
 
class  PostProcessing
 
class  PreProcessing
 
class  PrincipalComponentAnalysis
 
class  PSOParticle
 
class  RadialBasisFunction
 
class  Random
 
class  RandomForests
 
class  RangeTracker
 
class  RBMQuantizer
 
class  RegisterClassifierModule
 
class  RegisterClustererModule
 
class  RegisterContextModule
 
class  RegisterFeatureExtractionModule
 
class  RegisterNode
 
class  RegisterPostProcessingModule
 
class  RegisterPreProcessingModule
 
class  RegisterRegressifierModule
 
class  RegisterWeakClassifierModule
 
class  Regressifier
 
class  RegressionData
 
class  RegressionSample
 
class  RegressionTree
 
class  RegressionTreeNode
 
class  SavitzkyGolayFilter
 
class  SelfOrganizingMap
 
class  Softmax
 
class  SoftmaxModel
 
class  SOMQuantizer
 
class  SVD
 
class  SVM
 
class  SwipeDetector
 
class  TestingLog
 
class  TestingLogMessage
 
class  TestInstanceResult
 
class  TestResult
 
class  TestResultsObserverManager
 
class  ThresholdCrossingDetector
 
class  TimeDomainFeatures
 
class  Timer
 
class  TimeseriesBuffer
 
class  TimeSeriesClassificationData
 
class  TimeSeriesClassificationDataStream
 
class  TimeSeriesClassificationSample
 
class  TimeSeriesClassificationSampleTrimmer
 
class  TimeSeriesPositionTracker
 
class  TimeStamp
 
class  TrainingDataRecordingTimer
 
class  TrainingLog
 
class  TrainingLogMessage
 
class  TrainingResult
 
class  TrainingResultsObserverManager
 
class  Tree
 
class  UnlabelledData
 
class  Util
 
class  WarningLog
 
class  WarningLogMessage
 
class  WeakClassifier
 
class  ZeroCrossingCounter
 

Typedefs

typedef struct AngleMagnitude AngleMagnitude
 
typedef std::vector< double > VectorDouble
 
typedef ClassificationData LabelledClassificationData
 
typedef RegressionData LabelledRegressionData
 
typedef TimeSeriesClassificationData LabelledTimeSeriesClassificationData
 
typedef UnlabelledData UnlabelledClassificationData
 
typedef struct PeakInfo PeakInfo
 

Enumerations

enum  HMMModelTypes { HMM_ERGODIC =0, HMM_LEFTRIGHT }
 
enum  HMMTypes { HMM_DISCRETE =0, HMM_CONTINUOUS }
 

Functions

template<typename T >
WeakClassifiernewWeakClassificationModuleInstance ()
 
template<typename T >
NodegetNewNodeInstance ()
 
template<typename T >
ClassifiergetNewClassificationModuleInstance ()
 
template<typename T >
ClusterergetNewClassificationModuleInstance ()
 
template<typename T >
ContextnewContextModuleInstance ()
 
template<typename T >
FeatureExtractionnewFeatureExtractionModuleInstance ()
 
template<typename T >
PostProcessingnewPostProcessingModuleInstance ()
 
template<typename T >
PreProcessingnewPreProcessingModuleInstance ()
 
template<typename T >
RegressifiernewRegressionModuleInstance ()
 
bool sortIndexDoubleDecendingValue (IndexedDouble i, IndexedDouble j)
 
template<class T >
SQR (const T &a)
 
template<class T >
void SWAP (T &a, T &b)
 
double SIGN (const double &a, const double &b)
 
double antilog (const double &x)
 

Detailed Description

GRT MIT License Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.