bipedarticulatedmodel.h

#ifndef BIPEDARTICULATEDMODEL_H
#define BIPEDARTICULATEDMODEL_H

#include <QDomNode>
#include <QImage>
#include "reliabilitysinglemodelinterface.h"
#include "src/fivelink2dbodymodel.h"

/*
 * Autor: Cristobal Barrientos Low  - mail: cbarrientoslow@gmail.com
 * Interfaz de que implementa el Modelo de objeto articulado Bípedo con 5 articulaciones.
 * Fuente: Detection and Tracking of Humans in Single View Sequences Using 2D Articulated Model.
 * Autores: Filip Korc and Vaclav Hlavac
*/

//Estructura que define las variables para representar el ROI de un objeto persona
typedef struct personROI personROI;
struct personROI
{
        cv::Rect ROI;
        cv::Point center;
        double valueCorrelation;
};

class BipedArticulatedModel : public ReliabilitySingleModelInterface
{
public:
    BipedArticulatedModel(int buffer_size);

    //IMPLEMENT!!
    virtual ~BipedArticulatedModel();

    //IMPLEMENT!! Initializes the model attributes for the interface.
    //The function is called by the interface constructor
    virtual void initInstanceAttributes();

    //IMPLEMENT!! Initializes the dynamics model attributes for the interface.
    //The function is called by the interface constructor
    virtual void initDynamicsAttributes();

    //IMPLEMENT!! Copy function for specific data from the instance (general_copy calls it after copying base info)
    virtual void copy(SpReliabilitySingleModelInterface);

    //IMPLEMENT!! Copy general structures and parameters of specific model, without considering instance specific data
    virtual void copy_structure(SpReliabilitySingleModelInterface);

    //IMPLEMENT!! sets parameters from xml file
    virtual void setParameters(QDomNode &i_parameters);

    //IMPLEMENT!! sets activation criteria for each model: reliability on input (distance, bad data),
    //   needs (occlusion, priority),
    //sets priority of models (hierarchy).
    //Checked before update phase
    virtual void activate(BoundingBox &bb);

    //IMPLEMENT!! initializes every activated model, according to their own input (region-blob-segments schema)
    //Executed only once at the begginning of single model creation (after 'copy_structure' and 'copy' methods
    //are used to copy the information).
    virtual void init();

    //IMPLEMENT!! updates activated model instance attributes for current frame, and returns the set of detected/enriched objects.
    //            It notifies if roi (bounding box, or segmentation) changes compared to the input, for reprocessing.
    virtual bool updateInstance(BoundingBox &, std::set<SpRMMHypothesis, hypothesesOrderedByBestProbabilityOperator> &);

    //IMPLEMENT!! updates activated model instance attributes for current frame and object, and returns the detected/enriched object.
    //            It notifies if roi (bounding box, or segmentation) changes compared to the input, for reprocessing.
    //            This function does NOT generate mobiles or hypotheses. It processes attributes for the current object.
    //            This function could be used by updateInstance to generate mobile information.
    virtual void updateSingleInstance(BoundingBox &);


    //IMPLEMENT!! updates model dynamics, based on instances information
    virtual void updateModelDynamics();

    //IMPLEMENT!! sets global probability for the model (how good is the model)
    virtual void setProbabilityAndReliability();

    //IMPLEMENT!! sets blob enclosing the model in forward process (update)
    virtual void setForwardInterface();

    //OPTIONAL
    virtual bool draw(QPainter &painter);

    virtual bool draw(QPainter &painter, int r, int g, int b);

    virtual BoundingBox getEstimator(double &R);



private:

    /*
     * Entrega la zona de interes (ROI's) donde se puede encontrar el jugador, verifica que la
     * altura del jugador sea acorde a la posición del blob en la imagen
    */
    cv::Rect humanCandidatesDetection(BoundingBox &bb);

    //Junto con el Modelo extendido y el ROI se verifica que el área de interes cumpla la apariencia de un humano
    double modelValidation(cv::Rect ROI, cv::Mat im);

    //Mean Shift Algorithm
    void meanShift_STEP1_TORSO(const cv::Rect &roi);
    void meanShift_STEP2_TORSO(const cv::Rect &roi);
    void meanShift_STEP2_THIGHS();
    void meanShift_STEP3_CALVES();
    void meanShift_STEP4_HEAD();

    //Test Parameters of Biped Model when Drawing and generating mask
    void getSilhouetteMask(cv::Rect roi, cv::Mat &image2);

    void setParamModel();

    std::vector< cv::Rect > roi_evaluados;
    FiveLink2DBodyModel bipedModel;

    //Razón para calcular el modelo de Altura
    double hwRatio;

    //Threshold Detección de Candidatos Humanos
    double detectThreshold;

    //Paŕametros evaluación del modelo
    bool externalPar;
    double costThreshold; //Threshold para la función de costo
    double par_Mm; //Paŕametro para mediciones faltantes (a en paper)
    double par_Ou; //Paŕametro para observaciones sin explicación (b en el paper)
    int iterMeanShift;

    //MeanSHift
    int n_samples; //Número de muestras en la vecindad utilizadas para MeanShift

    double ratio_Torso_height;
    double ratio_Torso_width;
    double ratio_Limbs_height;
    double ratio_Limbs_width;
    double ratio_Head_height;
    double ratio_Head_width;

    //Razón de distancia entre los muslos y el centro del modelo (Depende de la vista actual)
    double relativePos_LimbsTorso;

    //Razón de distancia entre partes del cuerpo
    double beta;
    double gama;
    double alpha;

    //Ángulos iniciales del Modelo
    double init_angleHead;
    double init_angleTorso;
    double init_angleLimbsTopLeft;
    double init_angleLimbsTopRight;
    double init_angleLimbsBottomLeft;
    double init_angleLimbsBottomRight;

    //Parámetros que definen la vecindad donde se generarán los valores aleatorios para Meanshift
    double neighboring_X_axis;
    double neighboring_Y_axis;
    double neighboring_Torso_angle;
    double neighboring_Thigs_angle;
    double neighboring_Calves_angle;
    double neighboring_Head_angle;

    //Umbral basado en distancia entre modelos para definir cuando Meanshift converge
    double diffDistModel_Threshold;

    bool drawFlag;

    cv::Point2f *getRectModelPoints(int part);
    double calculateStdDesv(QString attName);
};

#endif // BIPEDARTICULATEDMODEL_H