|| || || || || ||

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KalmanTemplate.h

Go to the documentation of this file.

#ifndef Impala_Core_Tracking_KalmanTemplate_h
#define Impala_Core_Tracking_KalmanTemplate_h

#include "Core/Array/Pattern/PatGenConv2d.h"
#include "Core/Array/Pattern/PatBinaryPixOp.h"

#include "Core/Tracking/ObjectRepresentation.h"
#include "Core/Tracking/SearcherAroundLastPos.h"
#include "Core/Tracking/FunctorKalman.h"

namespace Impala
{
namespace Core
{
namespace Tracking
{

class KalmanTemplate : public ObjectRepresentation
{
public:
    KalmanTemplate()
    {
        mTemplate = new Array::Array2dVec3Real64(0, 0, 0, 0);
        mScratch = new Array::Array2dVec3UInt8(0, 0, 0, 0);
        mTemplatePrediction = Array::ArrayClone<Array::Array2dVec3Real64,
                                                Array::Array2dVec3Real64>(mTemplate);
    }

    virtual ~KalmanTemplate()
    {
        delete mScratch;
        delete mTemplate;
        delete mTemplatePrediction;
    }

    void Update(/*const*/ Array::Array2dVec3Real64& image, const Position& pos)
    {
        Array::Array2dVec3Real64* temp =
            new Array::Array2dVec3Real64(pos.size.x, pos.size.y, 0, 0);
        Array::Pattern::PatSet(temp, &image, pos.translation.x, pos.translation.y,
                               pos.size.x, pos.size.y, 0, 0);
        Array::Pattern::PatBinaryPixOp(mTemplatePrediction, mTemplate,
                                       temp, mKalman);
        delete temp;
        mKalman.UpdateKalman();
        if(!mKalman.mOcclusion)
        {
            Array::Pattern::PatSet(mTemplate, mTemplatePrediction, 0, 0,
                                   mTemplate->CW(), mTemplate->CH(), 0, 0);
        }

        Array::Pattern::PatSet(mScratch,mTemplate,0,0,pos.size.x, pos.size.y,0,0);
    }

    double Score(/*const*/ Array::Array2dVec3Real64& image, const Position& pos)
    {
        Array::Trait::FuncBpoRobustMahalanobis dif;
        for(int i=0 ; i<3 ; i++)
            dif.mSigma[i] = mKalman.mSigmaG[i] + mKalman.mSigmaI[i];
        Array::Pattern::PatBinaryPixOp(mTemplatePrediction, &image, mTemplate, dif);
        return dif.mError;
    }

    void Reset(/*const*/ Array::Array2dVec3Real64& image, const Position& pos)
    {
        ILOG_DEBUG("Reset with size = (" << pos.size.x << "," << pos.size.y << ")");
        delete mTemplate;
        mTemplate = new Array::Array2dVec3Real64(pos.size.x, pos.size.y, 0, 0);
        Array::Pattern::PatSet(mTemplate, &image,
                               pos.translation.x, pos.translation.y,
                               pos.size.x, pos.size.y, 0, 0);
        delete mTemplatePrediction;
        mTemplatePrediction =
            new Array::Array2dVec3Real64(pos.size.x, pos.size.y, 0, 0);
        Array::Pattern::PatSet(mTemplatePrediction, &image,
                               pos.translation.x, pos.translation.y,
                               pos.size.x, pos.size.y, 0, 0);
        mKalman.Reset(pos.size.x, pos.size.y);
        delete mScratch;
        mScratch = new Array::Array2dVec3UInt8(pos.size.x, pos.size.y, 0, 0);
        Array::Pattern::PatSet(mScratch,mTemplate,0,0,pos.size.x, pos.size.y,0,0);
    }

    Array::Array2dVec3Real64* GetImage()
    {
        ILOG_DEBUG("object image requested");
        return mTemplate;
    }

    Array::Array2dVec3Real64* mTemplate;
    Array::Array2dVec3Real64* mTemplatePrediction;
    Array::Trait::FuncKalmanColor mKalman;
    Array::Array2dVec3UInt8* mScratch;
    ILOG_CLASS;
};

ILOG_VAR_INIT(KalmanTemplate, Impala.Core.Tracking);

} // namespace Tracking
} // namespace Core
} // namespace Impala

#endif //Impala_Core_Tracking_KalmanTemplate_h

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