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.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
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      notice, this list of conditions and the following disclaimer.
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      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
    * Neither the name of the <organization> nor the
      names of its contributors may be used to endorse or promote products
      derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL ETH-ASL BE LIABLE FOR ANY
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*/

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

template<typename T>
PointMatcher<T>::ErrorMinimizer::ErrorMinimizer():
        pointUsedRatio(-1.),
        weightedPointUsedRatio(-1.)
{}

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>
PointMatcher<T>::ErrorMinimizer::ErrorElements::ErrorElements(const DataPoints& reading, const DataPoints reference, const OutlierWeights weights, const Matches matches):
        reading(reading),
        reference(reference),
        weights(weights),
        matches(matches)
{
        assert(reading.features.cols() == reference.features.cols());
        assert(reading.features.cols() == weights.cols());
        assert(reading.features.cols() == matches.dists.cols());
        // May have no descriptors... size 0
}

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

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

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

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

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).cwise() * B.row(z) - A.row(z).cwise() * B.row(y);
                cross.row(y) = A.row(z).cwise() * B.row(x) - A.row(x).cwise() * B.row(z);
                cross.row(z) = A.row(x).cwise() * B.row(y) - A.row(y).cwise() * B.row(x);
        }
        else
        {
                //pseudo-cross product for 2D vectors
                cross = Vector(B.cols());
                cross = A.row(x).cwise() * B.row(y) - A.row(y).cwise() * B.row(x);
        }

        return cross;
}


template<typename T>
typename PointMatcher<T>::ErrorMinimizer::ErrorElements& PointMatcher<T>::ErrorMinimizer::getMatchedPoints(
                const DataPoints& requestedPts,
                const DataPoints& sourcePts,
                const Matches& matches, 
                const OutlierWeights& outlierWeights)
{
        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();

        // Count points with no weights
        const int pointsCount = (outlierWeights.cwise() != 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);

        Matches keptMatches (Dists(1,pointsCount), Ids(1, pointsCount));
        OutlierWeights keptWeights(1, pointsCount);

        int j = 0;
        weightedPointUsedRatio = 0;
        for(int k = 0; k < knn; k++) // knn
        {
                for (int i = 0; i < requestedPts.features.cols(); ++i) //nb pts
                {
                        if (outlierWeights(k,i) != 0.0)
                        {
                                if(dimReqDesc > 0)
                                        keptDesc.col(j) = requestedPts.descriptors.col(i);
                                
                                keptFeat.col(j) = requestedPts.features.col(i);
                                keptMatches.ids(0, j) = matches.ids(k, i);
                                keptMatches.dists(0, j) = matches.dists(k, i);
                                keptWeights(0,j) = outlierWeights(k,i);
                                ++j;
                                weightedPointUsedRatio += outlierWeights(k,i);
                        }
                }
        }

        assert(j == pointsCount);

        this->pointUsedRatio = double(j)/double(knn*requestedPts.features.cols());
        this->weightedPointUsedRatio /= double(knn*requestedPts.features.cols());
        
        assert(dimFeat == sourcePts.features.rows());
        const int dimSourDesc = sourcePts.descriptors.rows();
        
        Matrix associatedFeat(dimFeat, pointsCount);
        Matrix associatedDesc;
        if(dimSourDesc > 0)
                associatedDesc = Matrix(dimSourDesc, 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);
        }

        lastErrorElements.reading = DataPoints(
                keptFeat, 
                requestedPts.featureLabels,
                keptDesc,
                requestedPts.descriptorLabels
        );
        lastErrorElements.reference = DataPoints(
                associatedFeat,
                sourcePts.featureLabels,
                associatedDesc,
                sourcePts.descriptorLabels
        );
        lastErrorElements.weights = keptWeights;
        lastErrorElements.matches = keptMatches;
        return lastErrorElements;
}

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