GMMParameterEstimator.h

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#pragma once

// Global includes
#include <random>
#include <string>
#include <vector>
#include <chrono>

// Package includes
#include <Eigen/Core>
#include <Eigen/Geometry>
#include <Eigen/Eigenvalues>

#include <boost/lexical_cast.hpp>
#include <boost/property_tree/ptree.hpp>

#include <asr_msgs/AsrObject.h>

#include <Pose.h>

#include <opencv2/opencv.hpp>

#include <visualization/gnuplot/GMMGnuplotVisualization.h>

// Local includes.
#include "learner/foreground/ocm/ocm/shape/GaussianMixtureModel.h"

#include "helper/MathHelper.h"

namespace ProbabilisticSceneRecognition {
   
  class GMMParameterEstimator {
  public:

    GMMParameterEstimator(unsigned int pNumberOfDimensions, unsigned int pNumberOfKernelsMin, unsigned int pNumberOfKernelsMax, unsigned int pNumberOfRuns, unsigned int pNumberOfSyntheticSamples, double pIntervalPosition, double pIntervalOrientation, std::string pPathOrientationPlots, unsigned int pAttemptsPerKernel);
    
    ~GMMParameterEstimator();
    
    void addDatum(Eigen::Vector3d pSample);
    
    void addDatum(Eigen::Quaternion<double> pSample);
    
    void learn();
    
    void getModel(GaussianMixtureModel& gmm);
    
    void plotModel();
    
  private:
    
    bool runExpectationMaximization(const std::vector<std::vector<double>> data,
                    unsigned int nc,
                    unsigned int& nparams,
                    double& llk,
                    double& bic,
                    GaussianMixtureModel& model,
                    bool useGenericMatrices = true);

    unsigned int mNumberDimensions;
    
    unsigned int mNumberKernelsMin, mNumberKernelsMax, mNumberKernels;
    
    unsigned int mNumberOfRuns;
    
    unsigned int mNumberOfSyntheticSamples;
    
    double mIntervalPosition, mIntervalOrientation;
    
    std::string mPathOrientationPlots;

    unsigned int mAttemptsPerRun;
    
    std::vector<std::vector<double> > mData;
    
    GaussianMixtureModel mBestGMM;
  };
}