ErrorMinimizer.cpp

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// kate: replace-tabs off; indent-width 4; indent-mode normal
// vim: ts=4:sw=4:noexpandtab
/*

Copyright (c) 2010--2012,
François Pomerleau and Stephane Magnenat, ASL, ETHZ, Switzerland
You can contact the authors at <f dot pomerleau at gmail dot com> and
<stephane at magnenat dot net>

All rights reserved.

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modification, are permitted provided that the following conditions are met:
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      names of its contributors may be used to endorse or promote products
      derived from this software without specific prior written permission.

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*/

#include "PointMatcher.h"
#include "PointMatcherPrivate.h"

// ErrorElements

template<typename T>
PointMatcher<T>::ErrorMinimizer::ErrorElements::ErrorElements():
        reading(DataPoints()),
        reference(DataPoints()),
        weights(OutlierWeights()),
        matches(Matches()),
        nbRejectedMatches(-1),
        nbRejectedPoints(-1),
        pointUsedRatio(-1.0),
        weightedPointUsedRatio(-1.0)
{
}

template<typename T>
PointMatcher<T>::ErrorMinimizer::ErrorElements::ErrorElements(const DataPoints& requestedPts, const DataPoints& sourcePts, const OutlierWeights& outlierWeights, const Matches& matches)
{
        typedef typename Matches::Ids Ids;
        typedef typename Matches::Dists Dists;
        
        assert(matches.ids.rows() > 0);
        assert(matches.ids.cols() > 0);
        assert(matches.ids.cols() == requestedPts.features.cols()); //nbpts
        assert(outlierWeights.rows() == matches.ids.rows());  // knn
        
        const int knn = outlierWeights.rows();
        const int dimFeat = requestedPts.features.rows();
        const int dimReqDesc = requestedPts.descriptors.rows();
        const int dimReqTime = requestedPts.times.rows();

        // Count points with no weights
        const int pointsCount = (outlierWeights.array() != 0.0).count();
        if (pointsCount == 0)
                throw ConvergenceError("ErrorMnimizer: no point to minimize");

        Matrix keptFeat(dimFeat, pointsCount);
        
        Matrix keptDesc;
        if(dimReqDesc > 0)
                keptDesc = Matrix(dimReqDesc, pointsCount);
        
        Int64Matrix keptTime;
        if(dimReqTime > 0)
                keptTime = Int64Matrix(dimReqTime, pointsCount);
        
        Matches keptMatches (Dists(1,pointsCount), Ids(1, pointsCount));
        OutlierWeights keptWeights(1, pointsCount);

        int j = 0;
        int rejectedMatchCount = 0;
        int rejectedPointCount = 0;
        bool matchExist = false;
        this->weightedPointUsedRatio = 0;
        
        for (int i = 0; i < requestedPts.features.cols(); ++i) //nb pts
        {
                matchExist = false;
                for(int k = 0; k < knn; k++) // knn
                {
                        const auto matchDist = matches.dists(k, i);
                        if (matchDist == Matches::InvalidDist){
                                continue;
                        }

                        if (outlierWeights(k,i) != 0.0)
                        {
                                if(dimReqDesc > 0)
                                        keptDesc.col(j) = requestedPts.descriptors.col(i);

                                if(dimReqTime > 0)
                                        keptTime.col(j) = requestedPts.times.col(i);

                                
                                keptFeat.col(j) = requestedPts.features.col(i);
                                keptMatches.ids(0, j) = matches.ids(k, i);
                                keptMatches.dists(0, j) = matchDist;
                                keptWeights(0,j) = outlierWeights(k,i);
                                ++j;
                                this->weightedPointUsedRatio += outlierWeights(k,i);
                                matchExist = true;
                        }
                        else
                        {
                                rejectedMatchCount++;
                        }
                }

                if(matchExist == false)
                {
                        rejectedPointCount++;
                }
        }

        assert(j == pointsCount);

        this->pointUsedRatio = T(j)/T(knn*requestedPts.features.cols());
        this->weightedPointUsedRatio /= T(knn*requestedPts.features.cols());
        
        assert(dimFeat == sourcePts.features.rows());
        const int dimSourDesc = sourcePts.descriptors.rows();
        const int dimSourTime = sourcePts.times.rows();
        
        Matrix associatedFeat(dimFeat, pointsCount);
        
        Matrix associatedDesc;
        if(dimSourDesc > 0)
                associatedDesc = Matrix(dimSourDesc, pointsCount);
        
        Int64Matrix associatedTime;
        if(dimSourTime> 0)
                associatedTime = Int64Matrix(dimSourTime, pointsCount);
        
        // Fetch matched points
        for (int i = 0; i < pointsCount; ++i)
        {
                const int refIndex(keptMatches.ids(i));
                associatedFeat.col(i) = sourcePts.features.block(0, refIndex, dimFeat, 1);
                
                if(dimSourDesc > 0)
                        associatedDesc.col(i) = sourcePts.descriptors.block(0, refIndex, dimSourDesc, 1);

                if(dimSourTime> 0)
                        associatedTime.col(i) = sourcePts.times.block(0, refIndex, dimSourTime, 1);

        }

        // Copy final data to structure
        this->reading = DataPoints(
                keptFeat, 
                requestedPts.featureLabels,
                keptDesc,
                requestedPts.descriptorLabels,
                keptTime,
                requestedPts.timeLabels
        );

        this->reference = DataPoints(
                associatedFeat,
                sourcePts.featureLabels,
                associatedDesc,
                sourcePts.descriptorLabels,
                associatedTime,
                sourcePts.timeLabels
        );

        this->weights = keptWeights;
        this->matches = keptMatches;
        this->nbRejectedMatches = rejectedMatchCount;
        this->nbRejectedPoints = rejectedPointCount;
}


// ErrorMinimizer

template<typename T>
PointMatcher<T>::ErrorMinimizer::ErrorMinimizer()
{}

template<typename T>
PointMatcher<T>::ErrorMinimizer::ErrorMinimizer(const std::string& className, const ParametersDoc paramsDoc, const Parameters& params):
        Parametrizable(className,paramsDoc,params)
{}

template<typename T>
PointMatcher<T>::ErrorMinimizer::~ErrorMinimizer()
{}

template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ErrorMinimizer::compute(const DataPoints& filteredReading, const DataPoints& filteredReference, const OutlierWeights& outlierWeights, const Matches& matches)
{
        
        // generates pairs of matching points
        typename ErrorMinimizer::ErrorElements matchedPoints(filteredReading, filteredReference, outlierWeights, matches);
        
        // calls specific instantiation for a given ErrorMinimizer
        TransformationParameters transform = this->compute(matchedPoints);
        
        // saves paired points for future introspection
        this->lastErrorElements = matchedPoints;
        
        // returns transforme parameters
        return transform;
}

template<typename T>
T PointMatcher<T>::ErrorMinimizer::getPointUsedRatio() const
{
        return lastErrorElements.pointUsedRatio;
}

template<typename T>
typename PointMatcher<T>::ErrorMinimizer::ErrorElements PointMatcher<T>::ErrorMinimizer::getErrorElements() const
{
        //Warning: the use of the variable lastErrorElements is not standardized yet.
        return lastErrorElements;
}

template<typename T>
T PointMatcher<T>::ErrorMinimizer::getWeightedPointUsedRatio() const
{
        return lastErrorElements.weightedPointUsedRatio;
}

template<typename T>
T PointMatcher<T>::ErrorMinimizer::getOverlap() const
{
        LOG_WARNING_STREAM("ErrorMinimizer - warning, no specific method to compute overlap was provided for the ErrorMinimizer used.");
        return lastErrorElements.weightedPointUsedRatio;
}

template<typename T>
typename PointMatcher<T>::Matrix PointMatcher<T>::ErrorMinimizer::getCovariance() const
{
        LOG_WARNING_STREAM("ErrorMinimizer - warning, no specific method to compute covariance was provided for the ErrorMinimizer used.");
        return Matrix::Zero(6,6);
}

template<typename T>
T PointMatcher<T>::ErrorMinimizer::getResidualError(const DataPoints& filteredReading, const DataPoints& filteredReference, const OutlierWeights& outlierWeights, const Matches& matches) const
{
        LOG_WARNING_STREAM("ErrorMinimizer - warning, no specific method to compute residual was provided for the ErrorMinimizer used.");
        return std::numeric_limits<T>::max();
}

template<typename T>
typename PointMatcher<T>::Matrix PointMatcher<T>::ErrorMinimizer::crossProduct(const Matrix& A, const Matrix& B)
{
        //Note: A = [x, y, z, 1] and B = [x, y, z] for convenience

        // Expecting matched points
        assert(A.cols() == B.cols());

        // Expecting homogenous coord X eucl. coord
        assert(A.rows() -1 == B.rows());

        // Expecting homogenous coordinates
        assert(A.rows() == 4 || A.rows() == 3);
        
        const unsigned int x = 0;
        const unsigned int y = 1;
        const unsigned int z = 2;

        Matrix cross;
        if(A.rows() == 4)
        {
                cross = Matrix(B.rows(), B.cols());
                                
                cross.row(x) = A.row(y).array() * B.row(z).array() - A.row(z).array() * B.row(y).array();
                cross.row(y) = A.row(z).array() * B.row(x).array() - A.row(x).array() * B.row(z).array();
                cross.row(z) = A.row(x).array() * B.row(y).array() - A.row(y).array() * B.row(x).array();
        }
        else
        {
                //pseudo-cross product for 2D vectors
                cross = Vector(B.cols());
                cross = A.row(x).array() * B.row(y).array() - A.row(y).array() * B.row(x).array();
        }
        return cross;
}




template struct PointMatcher<float>::ErrorMinimizer;
template struct PointMatcher<double>::ErrorMinimizer;