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.
SwipeDetector Class Reference

#include <SwipeDetector.h>

Inheritance diagram for SwipeDetector:
Classifier MLBase GRTBase Observer< TrainingResult > Observer< TestInstanceResult >

Public Types

enum  SwipeDirections { POSITIVE_SWIPE =0, NEGATIVE_SWIPE }
 
- Public Types inherited from Classifier
enum  ClassifierModes { STANDARD_CLASSIFIER_MODE =0, TIMESERIES_CLASSIFIER_MODE }
 
typedef std::map< std::string, Classifier *(*)() > StringClassifierMap
 
- Public Types inherited from MLBase
enum  BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER }
 

Public Member Functions

 SwipeDetector (const unsigned int swipeIndex=0, const unsigned int swipeThreshold=100, const unsigned int hysteresisThreshold=0, const unsigned int swipeDirection=POSITIVE_SWIPE, bool useScaling=false)
 
 SwipeDetector (const SwipeDetector &rhs)
 
virtual ~SwipeDetector (void)
 
SwipeDetectoroperator= (const SwipeDetector &rhs)
 
virtual bool deepCopyFrom (const Classifier *classifier)
 
bool init (const unsigned int numInputDimensions)
 
virtual bool train_ (ClassificationData &trainingData)
 
virtual bool predict_ (VectorDouble &inputVector)
 
virtual bool clear ()
 
virtual bool reset ()
 
virtual bool save (std::fstream &file) const
 
virtual bool load (std::fstream &file)
 
bool getSwipeDetected () const
 
Float getSwipeValue () const
 
Float getSwipeThreshold () const
 
Float getHysteresisThreshold () const
 
Float getMovementVelocity () const
 
Float getMovementThreshold () const
 
Float getContextValue () const
 
Float getSwipeIntegrationCoeff () const
 
bool setContext (const bool context)
 
bool setSwipeIndex (const unsigned int swipeIndex)
 
bool setSwipeDirection (const unsigned int swipeDirection)
 
bool setSwipeThreshold (const Float swipeThreshold)
 
bool setHysteresisThreshold (const Float hysteresisThreshold)
 
bool setMovementThreshold (const Float movementThreshold)
 
bool setSwipeIntegrationCoeff (const Float swipeIntegrationCoeff)
 
- Public Member Functions inherited from Classifier
 Classifier (void)
 
virtual ~Classifier (void)
 
bool copyBaseVariables (const Classifier *classifier)
 
std::string getClassifierType () const
 
bool getSupportsNullRejection () const
 
bool getNullRejectionEnabled () const
 
Float getNullRejectionCoeff () const
 
Float getMaximumLikelihood () const
 
Float getBestDistance () const
 
Float getPhase () const
 
virtual UINT getNumClasses () const
 
UINT getClassLabelIndexValue (UINT classLabel) const
 
UINT getPredictedClassLabel () const
 
VectorFloat getClassLikelihoods () const
 
VectorFloat getClassDistances () const
 
VectorFloat getNullRejectionThresholds () const
 
Vector< UINT > getClassLabels () const
 
Vector< MinMaxgetRanges () const
 
bool enableNullRejection (bool useNullRejection)
 
virtual bool setNullRejectionCoeff (Float nullRejectionCoeff)
 
virtual bool setNullRejectionThresholds (VectorFloat newRejectionThresholds)
 
virtual bool recomputeNullRejectionThresholds ()
 
bool getTimeseriesCompatible () const
 
ClassifiercreateNewInstance () const
 
ClassifierdeepCopy () const
 
const ClassifiergetClassifierPointer () const
 
const ClassifiergetBaseClassifier () 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 (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 (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)
 
 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)
 
MLBasegetMLBasePointer ()
 
const MLBasegetMLBasePointer () 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)
 
GRTBasegetGRTBasePointer ()
 
const GRTBasegetGRTBasePointer () 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)
 

Protected Attributes

bool firstSample
 
bool swipeDetected
 
bool contextInput
 
unsigned int swipeIndex
 
unsigned int swipeDirection
 
unsigned int contextFilterSize
 
Float swipeIntegrationCoeff
 
Float movementIntegrationCoeff
 
Float swipeThreshold
 
Float hysteresisThreshold
 
Float swipeVelocity
 
Float movementVelocity
 
Float movementThreshold
 
Float contextFilteredValue
 
VectorFloat lastX
 
GRT::ThresholdCrossingDetector thresholdDetector
 
GRT::MedianFilter contextFilter
 
- Protected Attributes inherited from Classifier
std::string classifierType
 
bool supportsNullRejection
 
bool useNullRejection
 
UINT numClasses
 
UINT predictedClassLabel
 
UINT classifierMode
 
Float nullRejectionCoeff
 
Float maxLikelihood
 
Float bestDistance
 
Float phase
 
VectorFloat classLikelihoods
 
VectorFloat classDistances
 
VectorFloat nullRejectionThresholds
 
Vector< UINT > classLabels
 
Vector< MinMaxranges
 
- 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
 

Static Protected Attributes

static RegisterClassifierModule< SwipeDetectorregisterModule
 

Additional Inherited Members

- Static Public Member Functions inherited from Classifier
static ClassifiercreateInstanceFromString (std::string const &classifierType)
 
static Vector< std::string > getRegisteredClassifiers ()
 
- Static Public Member Functions inherited from GRTBase
static std::string getGRTVersion (bool returnRevision=true)
 
static std::string getGRTRevison ()
 
- Protected Member Functions inherited from Classifier
bool saveBaseSettingsToFile (std::fstream &file) const
 
bool loadBaseSettingsFromFile (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 inherited from Classifier
static StringClassifierMapgetMap ()
 

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 40 of file SwipeDetector.h.

Constructor & Destructor Documentation

SwipeDetector::SwipeDetector ( const unsigned int  swipeIndex = 0,
const unsigned int  swipeThreshold = 100,
const unsigned int  hysteresisThreshold = 0,
const unsigned int  swipeDirection = POSITIVE_SWIPE,
bool  useScaling = false 
)

Default Constructor

Parameters
useScalingsets if the training and prediction data should be scaled to a specific range. Default value is useScaling = false

Definition at line 29 of file SwipeDetector.cpp.

SwipeDetector::SwipeDetector ( const SwipeDetector rhs)

Defines the copy constructor.

Parameters
rhsthe instance from which all the data will be copied into this instance

Definition at line 56 of file SwipeDetector.cpp.

SwipeDetector::~SwipeDetector ( void  )
virtual

Default Destructor

Definition at line 74 of file SwipeDetector.cpp.

Member Function Documentation

bool SwipeDetector::clear ( )
virtual

This overrides the clear function in the Classifier base class. It will completely clear the ML module, removing any trained model and setting all the base variables to their default values.

Returns
returns true if the module was cleared succesfully, false otherwise

Reimplemented from Classifier.

Definition at line 248 of file SwipeDetector.cpp.

bool SwipeDetector::deepCopyFrom ( const Classifier classifier)
virtual

This is required for the Gesture Recognition Pipeline for when the pipeline.setClassifier(...) method is called. It clones the data from the Base Class Classifier pointer (which should be pointing to an SwipeDetector instance) into this instance

Parameters
classifiera pointer to the Classifier Base Class, this should be pointing to another SwipeDetector instance
Returns
returns true if the clone was successfull, false otherwise

Reimplemented from Classifier.

Definition at line 105 of file SwipeDetector.cpp.

Float SwipeDetector::getContextValue ( ) const
Returns
returns the context value, this is the latest output of the context filter

Definition at line 446 of file SwipeDetector.cpp.

Float SwipeDetector::getHysteresisThreshold ( ) const
Returns
returns the hysteresis threshold, this is the value that the swipe analysis value must cross (after a valid swipe detection), before the next swipe will be detected

Definition at line 434 of file SwipeDetector.cpp.

Float SwipeDetector::getMovementThreshold ( ) const
Returns
returns the movement threshold, the movement velocity must be below this value for a valid swipe to be detected

Definition at line 442 of file SwipeDetector.cpp.

Float SwipeDetector::getMovementVelocity ( ) const

This function returns the movement velocity. This is the integrated difference between each of the additional inputs (that are not the swipe index) that is used to detected a valid swipe. The movement velocity must be below the movement threshold for a valid swipe to be detected.

Returns
returns the movement velocity

Definition at line 438 of file SwipeDetector.cpp.

bool SwipeDetector::getSwipeDetected ( ) const
Returns
returns true if a swipe was detected, false otherwise

Definition at line 422 of file SwipeDetector.cpp.

Float SwipeDetector::getSwipeIntegrationCoeff ( ) const
Returns
returns the swipe integration coeff

Definition at line 450 of file SwipeDetector.cpp.

Float SwipeDetector::getSwipeThreshold ( ) const
Returns
returns the swipe threshold, this is the value that the swipe analysis value must cross for a swipe to be trigger

Definition at line 430 of file SwipeDetector.cpp.

Float SwipeDetector::getSwipeValue ( ) const
Returns
returns the swipe analysis value, this is the value that the swipe threshold is matched against

Definition at line 426 of file SwipeDetector.cpp.

bool SwipeDetector::load ( std::fstream &  file)
virtual

This loads a trained SwipeDetector model from a file. This overrides the load function in the Classifier base class.

Parameters
filea reference to the file the SwipeDetector model will be loaded from
Returns
returns true if the model was loaded successfully, false otherwise

Reimplemented from MLBase.

Definition at line 322 of file SwipeDetector.cpp.

SwipeDetector & SwipeDetector::operator= ( const SwipeDetector rhs)

Defines how the data from the rhs SwipeDetector should be copied to this SwipeDetector

Parameters
rhsanother instance of a SwipeDetector
Returns
returns a pointer to this instance of the SwipeDetector

Definition at line 78 of file SwipeDetector.cpp.

bool SwipeDetector::predict_ ( VectorDouble inputVector)
virtual

This predicts the class of the inputVector. This overrides the predict function in the Classifier base class.

Parameters
inputVectorthe input vector to classify
Returns
returns true if the prediction was performed, false otherwise

Reimplemented from MLBase.

Definition at line 190 of file SwipeDetector.cpp.

bool SwipeDetector::reset ( )
virtual

This overrides the reset function in the Classifier base class.

Returns
returns true if the module was reset succesfully, false otherwise

Reimplemented from Classifier.

Definition at line 258 of file SwipeDetector.cpp.

bool SwipeDetector::save ( std::fstream &  file) const
virtual

This saves the trained SwipeDetector model to a file. This overrides the save function in the Classifier base class.

Parameters
filea reference to the file the SwipeDetector model will be saved to
Returns
returns true if the model was saved successfully, false otherwise

Reimplemented from MLBase.

Definition at line 285 of file SwipeDetector.cpp.

bool SwipeDetector::setContext ( const bool  context)

This function lets you set the current context input. This should be called before you call the predict function.

Returns
returns true if the context value was updated, false otherwise

Definition at line 454 of file SwipeDetector.cpp.

bool SwipeDetector::setHysteresisThreshold ( const Float  hysteresisThreshold)

This function lets you set the swipe hysteresisThreshold, this is the threshold that the swipe analysis value must pass after a valid swipe before a new swipe can be detected.

Parameters
hysteresisThresholdthe new hysteresis threshold
Returns
returns true if the parameter was updated, false otherwise

Definition at line 484 of file SwipeDetector.cpp.

bool SwipeDetector::setMovementThreshold ( const Float  movementThreshold)

This function lets you set the swipe movementThreshold. The movement index must be below the movementThreshold for a valid swipe to be detected.

Parameters
movementThresholdthe new movement threshold
Returns
returns true if the parameter was updated, false otherwise

Definition at line 490 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeDirection ( const unsigned int  swipeDirection)

This function lets you set the swipe direction, this should be one of the SwipeDirections enums.

Parameters
swipeDirectionthe direction you want to search for a swipe in
Returns
returns true if the parameter was updated, false otherwise

Definition at line 465 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeIndex ( const unsigned int  swipeIndex)

This function lets you set the swipe index, this is the index in the input vector that contains the main axis you want to use for the swipe detection. The other elements in the input vector will be combined to compute the movement index. The swipeIndex should be a valid index in your input vector.

Parameters
swipeIndexthe index in the input vector you want to use for the swipe detection
Returns
returns true if the parameter was updated, false otherwise

Definition at line 459 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeIntegrationCoeff ( const Float  swipeIntegrationCoeff)

This function lets you set the swipe integration coeff. This controls how much 'memory' is used to when integrating the input data.

Parameters
swipeIntegrationCoeffthe new integration coefficient
Returns
returns true if the parameter was updated, false otherwise

Definition at line 496 of file SwipeDetector.cpp.

bool SwipeDetector::setSwipeThreshold ( const Float  swipeThreshold)

This function lets you set the swipe threshold, this is the threshold that the swipe analysis value must pass for a swipe to be detected.

Parameters
swipeThresholdthe new swipe threshold
Returns
returns true if the parameter was updated, false otherwise

Definition at line 478 of file SwipeDetector.cpp.

bool SwipeDetector::train_ ( ClassificationData trainingData)
virtual

This trains the SwipeDetector model, using the labelled classification data. This overrides the train function in the Classifier base class.

Parameters
trainingDataa reference to the training data
Returns
returns true if the SwipeDetector model was trained, false otherwise

Reimplemented from MLBase.

Definition at line 156 of file SwipeDetector.cpp.


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