GestureRecognitionToolkit  Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Static Protected Member Functions | Protected Attributes | List of all members
FeatureExtraction Class Reference

#include <FeatureExtraction.h>

Inheritance diagram for FeatureExtraction:
MLBase GRTBase Observer< TrainingResult > Observer< TestInstanceResult > EnvelopeExtractor FFT FFTFeatures KMeansFeatures KMeansQuantizer MovementIndex MovementTrajectoryFeatures RBMQuantizer RegisterFeatureExtractionModule< T > RegisterFeatureExtractionModule< EnvelopeExtractor > RegisterFeatureExtractionModule< FFT > RegisterFeatureExtractionModule< FFTFeatures > RegisterFeatureExtractionModule< KMeansFeatures > RegisterFeatureExtractionModule< KMeansQuantizer > RegisterFeatureExtractionModule< MovementIndex > RegisterFeatureExtractionModule< MovementTrajectoryFeatures > RegisterFeatureExtractionModule< RBMQuantizer > RegisterFeatureExtractionModule< SOMQuantizer > RegisterFeatureExtractionModule< TimeDomainFeatures > RegisterFeatureExtractionModule< TimeseriesBuffer > RegisterFeatureExtractionModule< ZeroCrossingCounter > SOMQuantizer TimeDomainFeatures TimeseriesBuffer ZeroCrossingCounter

Public Types

typedef std::map< std::string, FeatureExtraction *(*)() > StringFeatureExtractionMap
 
- Public Types inherited from MLBase
enum  BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER }
 

Public Member Functions

 FeatureExtraction ()
 
virtual ~FeatureExtraction ()
 
virtual bool deepCopyFrom (const FeatureExtraction *rhs)
 
bool copyBaseVariables (const FeatureExtraction *featureExtractionModule)
 
virtual bool computeFeatures (const VectorFloat &inputVector)
 
virtual bool computeFeatures (const MatrixFloat &inputMatrix)
 
virtual bool reset ()
 
virtual bool clear ()
 
virtual bool saveModelToFile (std::fstream &file) const
 
virtual bool loadModelFromFile (std::fstream &file)
 
std::string getFeatureExtractionType () const
 
UINT getNumInputDimensions () const
 
UINT getNumOutputDimensions () const
 
bool getInitialized () const
 
bool getFeatureDataReady () const
 
const VectorFloat & getFeatureVector () const
 
const MatrixFloat & getFeatureMatrix () const
 
FeatureExtraction * createNewInstance () const
 
- Public Member Functions inherited from MLBase
 MLBase (void)
 
virtual ~MLBase (void)
 
bool copyMLBaseVariables (const MLBase *mlBase)
 
virtual bool train (ClassificationData trainingData)
 
virtual bool train_ (ClassificationData &trainingData)
 
virtual bool train (RegressionData trainingData)
 
virtual bool train_ (RegressionData &trainingData)
 
virtual bool train (TimeSeriesClassificationData trainingData)
 
virtual bool train_ (TimeSeriesClassificationData &trainingData)
 
virtual bool train (ClassificationDataStream trainingData)
 
virtual bool train_ (ClassificationDataStream &trainingData)
 
virtual bool train (UnlabelledData trainingData)
 
virtual bool train_ (UnlabelledData &trainingData)
 
virtual bool train (MatrixFloat data)
 
virtual bool train_ (MatrixFloat &data)
 
virtual bool predict (VectorFloat inputVector)
 
virtual bool predict_ (VectorFloat &inputVector)
 
virtual bool predict (MatrixFloat inputMatrix)
 
virtual bool predict_ (MatrixFloat &inputMatrix)
 
virtual bool map (VectorFloat inputVector)
 
virtual bool map_ (VectorFloat &inputVector)
 
virtual bool print () const
 
virtual bool save (const std::string filename) const
 
virtual bool load (const std::string filename)
 
virtual bool save (std::fstream &file) const
 
virtual bool load (std::fstream &file)
 
 GRT_DEPRECATED_MSG ("saveModelToFile(std::string filename) is deprecated, use save(std::string filename) instead", virtual bool saveModelToFile(std::string filename) const )
 
 GRT_DEPRECATED_MSG ("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )
 
 GRT_DEPRECATED_MSG ("loadModelFromFile(std::string filename) is deprecated, use load(std::string filename) instead", virtual bool loadModelFromFile(std::string filename))
 
 GRT_DEPRECATED_MSG ("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))
 
virtual bool getModel (std::ostream &stream) const
 
Float scale (const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)
 
virtual std::string getModelAsString () const
 
DataType getInputType () const
 
DataType getOutputType () const
 
UINT getBaseType () const
 
UINT getNumInputFeatures () const
 
UINT getNumInputDimensions () const
 
UINT getNumOutputDimensions () const
 
UINT getMinNumEpochs () const
 
UINT getMaxNumEpochs () const
 
UINT getValidationSetSize () const
 
UINT getNumTrainingIterationsToConverge () const
 
Float getMinChange () const
 
Float getLearningRate () const
 
Float getRootMeanSquaredTrainingError () const
 
Float getTotalSquaredTrainingError () const
 
Float getValidationSetAccuracy () const
 
VectorFloat getValidationSetPrecision () const
 
VectorFloat getValidationSetRecall () const
 
bool getUseValidationSet () const
 
bool getRandomiseTrainingOrder () const
 
bool getTrained () const
 
bool getModelTrained () const
 
bool getScalingEnabled () const
 
bool getIsBaseTypeClassifier () const
 
bool getIsBaseTypeRegressifier () const
 
bool getIsBaseTypeClusterer () const
 
bool enableScaling (const bool useScaling)
 
bool setMaxNumEpochs (const UINT maxNumEpochs)
 
bool setMinNumEpochs (const UINT minNumEpochs)
 
bool setMinChange (const Float minChange)
 
bool setLearningRate (const Float learningRate)
 
bool setUseValidationSet (const bool useValidationSet)
 
bool setValidationSetSize (const UINT validationSetSize)
 
bool setRandomiseTrainingOrder (const bool randomiseTrainingOrder)
 
bool setTrainingLoggingEnabled (const bool loggingEnabled)
 
bool registerTrainingResultsObserver (Observer< TrainingResult > &observer)
 
bool registerTestResultsObserver (Observer< TestInstanceResult > &observer)
 
bool removeTrainingResultsObserver (const Observer< TrainingResult > &observer)
 
bool removeTestResultsObserver (const Observer< TestInstanceResult > &observer)
 
bool removeAllTrainingObservers ()
 
bool removeAllTestObservers ()
 
bool notifyTrainingResultsObservers (const TrainingResult &data)
 
bool notifyTestResultsObservers (const TestInstanceResult &data)
 
MLBase * getMLBasePointer ()
 
const MLBase * getMLBasePointer () const
 
Vector< TrainingResult > getTrainingResults () const
 
- Public Member Functions inherited from GRTBase
 GRTBase (void)
 
virtual ~GRTBase (void)
 
bool copyGRTBaseVariables (const GRTBase *GRTBase)
 
std::string getClassType () const
 
std::string getLastWarningMessage () const
 
std::string getLastErrorMessage () const
 
std::string getLastInfoMessage () const
 
bool setInfoLoggingEnabled (const bool loggingEnabled)
 
bool setWarningLoggingEnabled (const bool loggingEnabled)
 
bool setErrorLoggingEnabled (const bool loggingEnabled)
 
GRTBase * getGRTBasePointer ()
 
const GRTBase * getGRTBasePointer () const
 
- Public Member Functions inherited from Observer< TrainingResult >
virtual void notify (const TrainingResult &data)
 
- Public Member Functions inherited from Observer< TestInstanceResult >
virtual void notify (const TestInstanceResult &data)
 

Static Public Member Functions

static FeatureExtraction * createInstanceFromString (const std::string &featureExtractionType)
 
- Static Public Member Functions inherited from GRTBase
static std::string getGRTVersion (bool returnRevision=true)
 
static std::string getGRTRevison ()
 

Protected Member Functions

bool init ()
 
bool saveFeatureExtractionSettingsToFile (std::fstream &file) const
 
bool loadFeatureExtractionSettingsFromFile (std::fstream &file)
 
- Protected Member Functions inherited from MLBase
bool saveBaseSettingsToFile (std::fstream &file) const
 
bool loadBaseSettingsFromFile (std::fstream &file)
 
- Protected Member Functions inherited from GRTBase
Float SQR (const Float &x) const
 

Static Protected Member Functions

static StringFeatureExtractionMap * getMap ()
 

Protected Attributes

std::string featureExtractionType
 
bool initialized
 
bool featureDataReady
 
VectorFloat featureVector
 
MatrixFloat featureMatrix
 
- Protected Attributes inherited from MLBase
bool trained
 
bool useScaling
 
DataType inputType
 
DataType outputType
 
UINT baseType
 
UINT numInputDimensions
 
UINT numOutputDimensions
 
UINT numTrainingIterationsToConverge
 
UINT minNumEpochs
 
UINT maxNumEpochs
 
UINT validationSetSize
 
Float learningRate
 
Float minChange
 
Float rootMeanSquaredTrainingError
 
Float totalSquaredTrainingError
 
Float validationSetAccuracy
 
bool useValidationSet
 
bool randomiseTrainingOrder
 
VectorFloat validationSetPrecision
 
VectorFloat validationSetRecall
 
Random random
 
std::vector< TrainingResult > trainingResults
 
TrainingResultsObserverManager trainingResultsObserverManager
 
TestResultsObserverManager testResultsObserverManager
 
- Protected Attributes inherited from GRTBase
std::string classType
 
DebugLog debugLog
 
ErrorLog errorLog
 
InfoLog infoLog
 
TrainingLog trainingLog
 
TestingLog testingLog
 
WarningLog warningLog
 

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.

Definition at line 38 of file FeatureExtraction.h.

Member Typedef Documentation

typedef std::map< std::string, FeatureExtraction*(*)() > FeatureExtraction::StringFeatureExtractionMap

Defines a map between a string (which will contain the name of the featureExtraction module, such as FFT) and a function returns a new instance of that featureExtraction

Definition at line 170 of file FeatureExtraction.h.

Constructor & Destructor Documentation

FeatureExtraction::FeatureExtraction ( )

Default FeatureExtraction Constructor

Definition at line 42 of file FeatureExtraction.cpp.

FeatureExtraction::~FeatureExtraction ( )
virtual

Default FeatureExtraction Destructor

Definition at line 56 of file FeatureExtraction.cpp.

Member Function Documentation

bool FeatureExtraction::clear ( )
virtual

This function clears any previous setup.

Returns
returns true if the module was cleared, false otherwise

Reimplemented from MLBase.

Reimplemented in FFT, RBMQuantizer, KMeansQuantizer, and SOMQuantizer.

Definition at line 108 of file FeatureExtraction.cpp.

virtual bool FeatureExtraction::computeFeatures ( const VectorFloat &  inputVector)
inlinevirtual

This function is called by the GestureRecognitionPipeline when any new input data needs to be processed (during the prediction phase for example). This function should be overwritten by the derived class.

Parameters
inputVectorthe inputVector that should be processed
Returns
returns true if the data was processed, false otherwise (the base class always returns false)

Reimplemented in FFT, ZeroCrossingCounter, RBMQuantizer, KMeansQuantizer, SOMQuantizer, TimeDomainFeatures, MovementTrajectoryFeatures, FFTFeatures, KMeansFeatures, MovementIndex, EnvelopeExtractor, and TimeseriesBuffer.

Definition at line 74 of file FeatureExtraction.h.

virtual bool FeatureExtraction::computeFeatures ( const MatrixFloat &  inputMatrix)
inlinevirtual

This function is called by the GestureRecognitionPipeline when any new input data needs to be processed (during the prediction phase for example). This function should be overwritten by the derived class.

Parameters
inputMatrixthe inputVector that should be processed
Returns
returns true if the data was processed, false otherwise (the base class always returns false)

Reimplemented in FFT.

Definition at line 83 of file FeatureExtraction.h.

bool FeatureExtraction::copyBaseVariables ( const FeatureExtraction *  featureExtractionModule)

This copies the FeatureExtraction variables from featureExtractionModule to the instance that calls the function.

Parameters
featureExtractionModulea pointer to a feature extraction module from which the values will be copied
Returns
returns true if the copy was successfull, false otherwise

Definition at line 63 of file FeatureExtraction.cpp.

FeatureExtraction * FeatureExtraction::createNewInstance ( ) const

Creates a new feature extraction instance based on the current featureExtractionType string value.

Returns
FeatureExtraction*: a pointer to the new instance of the feature extraction

Definition at line 38 of file FeatureExtraction.cpp.

virtual bool FeatureExtraction::deepCopyFrom ( const FeatureExtraction *  rhs)
inlinevirtual

This is the base deepCopyFrom function for the FeatureExtraction modules. This function should be overwritten by the derived class.

Parameters
featureExtractiona pointer to the FeatureExtraction base class, this should be pointing to another instance of a matching derived class
Returns
returns true if the deep copy was successfull, false otherwise (the FeatureExtraction base class will always return flase)

Reimplemented in FFT, ZeroCrossingCounter, KMeansQuantizer, RBMQuantizer, SOMQuantizer, TimeDomainFeatures, FFTFeatures, MovementTrajectoryFeatures, KMeansFeatures, MovementIndex, EnvelopeExtractor, and TimeseriesBuffer.

Definition at line 57 of file FeatureExtraction.h.

bool FeatureExtraction::getFeatureDataReady ( ) const

Returns true if the feature extraction module has just processed the last input vector and a new output feature vector is ready.

Returns
returns true if the feature extraction module has just processed the last input vector and a new output feature vector is ready, false otherwise

Definition at line 181 of file FeatureExtraction.cpp.

std::string FeatureExtraction::getFeatureExtractionType ( ) const

Returns the feature extraction type as a string.

Returns
returns the feature extraction type as a string

Definition at line 165 of file FeatureExtraction.cpp.

const MatrixFloat & FeatureExtraction::getFeatureMatrix ( ) const

Returns the current feature matrix.

Returns
returns the current feature matrix, this matrix will be empty if the module has not been initialized

Definition at line 189 of file FeatureExtraction.cpp.

const VectorFloat & FeatureExtraction::getFeatureVector ( ) const

Returns the current feature vector.

Returns
returns the current feature vector, this vector will be empty if the module has not been initialized

Definition at line 185 of file FeatureExtraction.cpp.

bool FeatureExtraction::getInitialized ( ) const

Returns true if the feature extraction module has been initialized correctly.

Returns
returns true if the feature extraction module has been initialized succesfully, false otherwise

Definition at line 177 of file FeatureExtraction.cpp.

UINT FeatureExtraction::getNumInputDimensions ( ) const

Returns the size of the input vector expected by the feature extraction module.

Returns
returns the size of the input vector expected by the feature extraction module

Definition at line 169 of file FeatureExtraction.cpp.

UINT FeatureExtraction::getNumOutputDimensions ( ) const

Returns the size of the feature vector that will be computed by the feature extraction module.

Returns
returns the size of the feature vector that will be computed by the feature extraction module

Definition at line 173 of file FeatureExtraction.cpp.

bool FeatureExtraction::init ( )
protected

Initializes the base feature extraction module, this will resize the feature vector and get the instance ready for processing new data.

Returns
returns true if the module was initialized, false otherwise

Definition at line 88 of file FeatureExtraction.cpp.

bool FeatureExtraction::loadFeatureExtractionSettingsFromFile ( std::fstream &  file)
protected

Loads the core base settings from a file.

Returns
returns true if the base settings were loaded, false otherwise

Definition at line 134 of file FeatureExtraction.cpp.

virtual bool FeatureExtraction::loadModelFromFile ( std::fstream &  file)
inlinevirtual

This loads the feature extraction settings from a file. This function should be overwritten by the derived class.

Parameters
filea reference to the file to load the settings from
Returns
returns true if the settings were loaded successfully, false otherwise (the base class always returns false)

Reimplemented in FFT, ZeroCrossingCounter, SOMQuantizer, TimeDomainFeatures, MovementTrajectoryFeatures, FFTFeatures, KMeansFeatures, EnvelopeExtractor, MovementIndex, KMeansQuantizer, and TimeseriesBuffer.

Definition at line 116 of file FeatureExtraction.h.

virtual bool FeatureExtraction::reset ( )
inlinevirtual

This function is called by the GestureRecognitionPipeline's reset function. This function should be overwritten by the derived class.

Returns
returns true if the module was reset, false otherwise (the base class always returns true)

Reimplemented from MLBase.

Reimplemented in FFT, ZeroCrossingCounter, RBMQuantizer, KMeansQuantizer, SOMQuantizer, TimeDomainFeatures, MovementTrajectoryFeatures, FFTFeatures, KMeansFeatures, MovementIndex, EnvelopeExtractor, and TimeseriesBuffer.

Definition at line 91 of file FeatureExtraction.h.

bool FeatureExtraction::saveFeatureExtractionSettingsToFile ( std::fstream &  file) const
protected

Saves the core base settings to a file.

Returns
returns true if the base settings were saved, false otherwise

Definition at line 120 of file FeatureExtraction.cpp.

virtual bool FeatureExtraction::saveModelToFile ( std::fstream &  file) const
inlinevirtual

This saves the feature extraction settings to a file. This function should be overwritten by the derived class.

Parameters
filea reference to the file to save the settings to
Returns
returns true if the settings were saved successfully, false otherwise (the base class always returns false)

Reimplemented in FFT, ZeroCrossingCounter, SOMQuantizer, TimeDomainFeatures, MovementTrajectoryFeatures, FFTFeatures, KMeansFeatures, EnvelopeExtractor, MovementIndex, KMeansQuantizer, and TimeseriesBuffer.

Definition at line 107 of file FeatureExtraction.h.

The documentation for this class was generated from the following files: