Gestalt.h

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

Copyright (c) 2010--2018,
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:
    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above copyright
      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
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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*/
#pragma once

#include "PointMatcher.h"

template<typename T>
struct GestaltDataPointsFilter: public PointMatcher<T>::DataPointsFilter
{
        typedef PointMatcherSupport::Parametrizable Parametrizable;
        typedef PointMatcherSupport::Parametrizable P;
        typedef Parametrizable::Parameters Parameters;
        typedef Parametrizable::ParameterDoc ParameterDoc;
        typedef Parametrizable::ParametersDoc ParametersDoc;
        typedef Parametrizable::InvalidParameter InvalidParameter;
        
        typedef typename PointMatcher<T>::Vector Vector;
        typedef typename PointMatcher<T>::Matrix Matrix;        
        typedef typename PointMatcher<T>::DataPoints DataPoints;
        typedef typename PointMatcher<T>::DataPoints::InvalidField InvalidField;
        
  inline static const std::string description()
  {
    return "Gestalt descriptors filter.";
  }
  inline static const ParametersDoc availableParameters()
  {
    return {
                {"ratio", "ratio of points to keep with random subsampling. Matrix (normal, density, etc.) will be associated to all points in the same bin.", "0.1", "0.0000001", "0.9999999", &P::Comp<T>},
                {"radius", "is the radius of the gestalt descriptor, will be divided into 4 circular and 8 radial bins = 32 bins", "5", "0.1", "2147483647", &P::Comp<T>},
                {"knn", "determined how many points are used to compute the normals. Direct link with the rapidity of the computation (large = fast). Technically, limit over which a box is splitted in two", "7", "3", "2147483647", &P::Comp<unsigned>},
                {"vSizeX", "Dimension of each voxel cell in x direction", "1.0", "-inf", "inf", &P::Comp<T>},
                {"vSizeY", "Dimension of each voxel cell in y direction", "1.0", "-inf", "inf", &P::Comp<T>},
                {"vSizeZ", "Dimension of each voxel cell in z direction", "1.0", "-inf", "inf", &P::Comp<T>},
                {"keepMeans", "whether the means should be added as descriptors to the resulting cloud", "0"},
                {"maxBoxDim", "maximum length of a box above which the box is discarded", "inf"},
                {"averageExistingDescriptors", "whether the filter keep the existing point descriptors and average them or should it drop them", "1"},
                {"maxTimeWindow", "maximum spread of times in a surfel", "inf"},
                {"keepNormals", "whether the normals should be added as descriptors to the resulting cloud", "1"},
                {"keepEigenValues", "whether the eigen values should be added as descriptors to the resulting cloud", "0"},
                {"keepEigenVectors", "whether the eigen vectors should be added as descriptors to the resulting cloud", "0"},
                {"keepCovariances", "whether the covariances should be added as descriptors to the resulting cloud", "0"},
                {"keepGestaltFeatures", "whether the Gestalt features shall be added to the resulting cloud", "1"}
    };
  }

  const T ratio;
  const T radius;
  const unsigned knn;
  const T vSizeX;
  const T vSizeY;
  const T vSizeZ;
  const T maxBoxDim;
  const T maxTimeWindow;
  const bool keepMeans;
  const bool averageExistingDescriptors;
  const bool keepNormals;
  const bool keepEigenValues;
  const bool keepEigenVectors;
  const bool keepCovariances;
  const bool keepGestaltFeatures;


 public:
  GestaltDataPointsFilter(const Parameters& params = Parameters());
  virtual ~GestaltDataPointsFilter() {}
  virtual DataPoints filter(const DataPoints& input);
  virtual void inPlaceFilter(DataPoints& cloud);
  
  typename PointMatcher<T>::Vector serializeGestaltMatrix(const Matrix& gestaltFeatures) const;
  typename PointMatcher<T>::Vector calculateAngles(const Matrix& points, const Eigen::Matrix<T,3,1>&) const;
  typename PointMatcher<T>::Vector calculateRadii(const Matrix& points, const Eigen::Matrix<T,3,1>&) const;


 protected:
  struct BuildData
  {
    typedef std::vector<int> Indices;
    typedef typename DataPoints::View View;
    typedef typename Eigen::Matrix<std::int64_t, Eigen::Dynamic, Eigen::Dynamic> Int64Matrix;
    typedef typename Eigen::Matrix<std::int64_t, 1, Eigen::Dynamic> Int64Vector;

    Indices indices;
    Indices indicesToKeep;
    Matrix& features;
    Matrix& descriptors;
    Int64Matrix& times;
    boost::optional<View> normals;
    boost::optional<View> means;
    boost::optional<View> eigenValues;
    boost::optional<View> eigenVectors;
    boost::optional<View> covariance;
    boost::optional<View> gestaltMeans;
    boost::optional<View> gestaltVariances;
    boost::optional<View> gestaltShapes;
    boost::optional<View> warpedXYZ;
    int outputInsertionPoint;
    int unfitPointsCount;

    BuildData(Matrix& features, Matrix& descriptors, Int64Matrix& times):
      features(features),
      descriptors(descriptors),
      times(times),
      unfitPointsCount(0)
    {
      const int pointsCount(features.cols());
      indices.reserve(pointsCount);
      for (int i = 0; i < pointsCount; ++i)
        indices.push_back(i);
    }
  };

  struct CompareDim
  {
    const int dim;
    const BuildData& buildData;
    CompareDim(const int dim, const BuildData& buildData):dim(dim),buildData(buildData){}
    bool operator() (const int& p0, const int& p1)
    {
      return buildData.features(dim, p0) <
          buildData.features(dim, p1);
    }
  };

 protected:
  void buildNew(BuildData& data, const int first, const int last, Vector&& minValues, Vector&& maxValues) const;
  void fuseRange(BuildData& data, DataPoints& input, const int first, const int last) const;

};