shot.hpp

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#ifndef PCL_FEATURES_IMPL_SHOT_H_
#define PCL_FEATURES_IMPL_SHOT_H_
 
#include <pcl/features/shot.h>
#include <pcl/features/shot_lrf.h>
 
#include <pcl/common/colors.h>  // for RGB2sRGB_LUT, XYZ2LAB_LUT
 
// Useful constants.
#define PST_PI 3.1415926535897932384626433832795
#define PST_RAD_45 0.78539816339744830961566084581988
#define PST_RAD_90 1.5707963267948966192313216916398
#define PST_RAD_135 2.3561944901923449288469825374596
#define PST_RAD_180 PST_PI
#define PST_RAD_360 6.283185307179586476925286766558
#define PST_RAD_PI_7_8 2.7488935718910690836548129603691
 
const double zeroDoubleEps15 = 1E-15;
const float zeroFloatEps8 = 1E-8f;
 
//////////////////////////////////////////////////////////////////////////////////////////////
/** \brief Check if val1 and val2 are equals.
  *
  * \param[in] val1 first number to check.
  * \param[in] val2 second number to check.
  * \param[in] zeroDoubleEps epsilon
  * \return true if val1 is equal to val2, false otherwise.
  */
inline bool
areEquals (double val1, double val2, double zeroDoubleEps = zeroDoubleEps15)
{
  return (std::abs (val1 - val2)<zeroDoubleEps);
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
/** \brief Check if val1 and val2 are equals.
  *
  * \param[in] val1 first number to check.
  * \param[in] val2 second number to check.
  * \param[in] zeroFloatEps epsilon
  * \return true if val1 is equal to val2, false otherwise.
  */
inline bool
areEquals (float val1, float val2, float zeroFloatEps = zeroFloatEps8)
{
  return (std::fabs (val1 - val2)<zeroFloatEps);
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT>
std::array<float, 256>
    pcl::SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT>::sRGB_LUT = pcl::RGB2sRGB_LUT<float, 8>();
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT>
std::array<float, 4000>
    pcl::SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT>::sXYZ_LUT = pcl::XYZ2LAB_LUT<float, 4000>();
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT>::RGB2CIELAB (unsigned char R, unsigned char G,
                                                                              unsigned char B, float &L, float &A,
                                                                              float &B2)
{
  float fr = sRGB_LUT[R];
  float fg = sRGB_LUT[G];
  float fb = sRGB_LUT[B];
 
  // Use white = D65
  const float x = fr * 0.412453f + fg * 0.357580f + fb * 0.180423f;
  const float y = fr * 0.212671f + fg * 0.715160f + fb * 0.072169f;
  const float z = fr * 0.019334f + fg * 0.119193f + fb * 0.950227f;
 
  float vx = x / 0.95047f;
  float vy = y;
  float vz = z / 1.08883f;
 
  vx = sXYZ_LUT[static_cast<int>(vx*4000)];
  vy = sXYZ_LUT[static_cast<int>(vy*4000)];
  vz = sXYZ_LUT[static_cast<int>(vz*4000)];
 
  L = 116.0f * vy - 16.0f;
  if (L > 100)
    L = 100.0f;
 
  A = 500.0f * (vx - vy);
  if (A > 120)
    A = 120.0f;
  else if (A <- 120)
    A = -120.0f;
 
  B2 = 200.0f * (vy - vz);
  if (B2 > 120)
    B2 = 120.0f;
  else if (B2<- 120)
    B2 = -120.0f;
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> bool
pcl::SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::initCompute ()
{
  if (!FeatureFromNormals<PointInT, PointNT, PointOutT>::initCompute ())
  {
    PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
    return (false);
  }
 
  // SHOT cannot work with k-search
  if (this->getKSearch () != 0)
  {
    PCL_ERROR(
      "[pcl::%s::initCompute] Error! Search method set to k-neighborhood. Call setKSearch(0) and setRadiusSearch( radius ) to use this class.\n",
      getClassName().c_str ());
    return (false);
  }
 
  // Default LRF estimation alg: SHOTLocalReferenceFrameEstimation
  typename SHOTLocalReferenceFrameEstimation<PointInT, PointRFT>::Ptr lrf_estimator(new SHOTLocalReferenceFrameEstimation<PointInT, PointRFT>());
  lrf_estimator->setRadiusSearch ((lrf_radius_ > 0 ? lrf_radius_ : search_radius_));
  lrf_estimator->setInputCloud (input_);
  lrf_estimator->setIndices (indices_);
  if (!fake_surface_)
    lrf_estimator->setSearchSurface(surface_);
 
  if (!FeatureWithLocalReferenceFrames<PointInT, PointRFT>::initLocalReferenceFrames (indices_->size (), lrf_estimator))
  {
    PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
    return (false);
  }
 
  return (true);
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::createBinDistanceShape (
    int index,
    const pcl::Indices &indices,
    std::vector<double> &bin_distance_shape)
{
  bin_distance_shape.resize (indices.size ());
 
  const PointRFT& current_frame = (*frames_)[index];
  //if (!std::isfinite (current_frame.rf[0]) || !std::isfinite (current_frame.rf[4]) || !std::isfinite (current_frame.rf[11]))
    //return;
 
  Eigen::Vector4f current_frame_z (current_frame.z_axis[0], current_frame.z_axis[1], current_frame.z_axis[2], 0);
 
  unsigned nan_counter = 0;
  for (std::size_t i_idx = 0; i_idx < indices.size (); ++i_idx)
  {
    // check NaN normal
    const Eigen::Vector4f& normal_vec = (*normals_)[indices[i_idx]].getNormalVector4fMap ();
    if (!std::isfinite (normal_vec[0]) ||
        !std::isfinite (normal_vec[1]) ||
        !std::isfinite (normal_vec[2]))
    {
      bin_distance_shape[i_idx] = std::numeric_limits<double>::quiet_NaN ();
      ++nan_counter;
    } else
    {
      //double cosineDesc = feat[i].rf[6]*normal[0] + feat[i].rf[7]*normal[1] + feat[i].rf[8]*normal[2];
      double cosineDesc = normal_vec.dot (current_frame_z);
 
      if (cosineDesc > 1.0)
        cosineDesc = 1.0;
      if (cosineDesc < - 1.0)
        cosineDesc = - 1.0;
 
      bin_distance_shape[i_idx] = ((1.0 + cosineDesc) * nr_shape_bins_) / 2;
    }
  }
  if (nan_counter > 0)
    PCL_WARN ("[pcl::%s::createBinDistanceShape] Point %d has %d (%f%%) NaN normals in its neighbourhood\n",
      getClassName ().c_str (), index, nan_counter, (static_cast<float>(nan_counter)*100.f/static_cast<float>(indices.size ())));
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::normalizeHistogram (
    Eigen::VectorXf &shot, int desc_length)
{
  // Normalization is performed by considering the L2 norm
  // and not the sum of bins, as reported in the ECCV paper.
  // This is due to additional experiments performed by the authors after its pubblication,
  // where L2 normalization turned out better at handling point density variations.
  double acc_norm = 0;
  for (int j = 0; j < desc_length; j++)
    acc_norm += shot[j] * shot[j];
  acc_norm = sqrt (acc_norm);
  for (int j = 0; j < desc_length; j++)
    shot[j] /= static_cast<float> (acc_norm);
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTEstimationBase<PointInT, PointNT, PointOutT, PointRFT>::interpolateSingleChannel (
    const pcl::Indices &indices,
    const std::vector<float> &sqr_dists,
    const int index,
    std::vector<double> &binDistance,
    const int nr_bins,
    Eigen::VectorXf &shot)
{
  const Eigen::Vector4f& central_point = (*input_)[(*indices_)[index]].getVector4fMap ();
  const PointRFT& current_frame = (*frames_)[index];
 
  Eigen::Vector4f current_frame_x (current_frame.x_axis[0], current_frame.x_axis[1], current_frame.x_axis[2], 0);
  Eigen::Vector4f current_frame_y (current_frame.y_axis[0], current_frame.y_axis[1], current_frame.y_axis[2], 0);
  Eigen::Vector4f current_frame_z (current_frame.z_axis[0], current_frame.z_axis[1], current_frame.z_axis[2], 0);
 
  for (std::size_t i_idx = 0; i_idx < indices.size (); ++i_idx)
  {
    if (!std::isfinite(binDistance[i_idx]))
      continue;
 
    Eigen::Vector4f delta = (*surface_)[indices[i_idx]].getVector4fMap () - central_point;
    delta[3] = 0;
 
    // Compute the Euclidean norm
   double distance = sqrt (sqr_dists[i_idx]);
 
    if (areEquals (distance, 0.0))
      continue;
 
    double xInFeatRef = delta.dot (current_frame_x);
    double yInFeatRef = delta.dot (current_frame_y);
    double zInFeatRef = delta.dot (current_frame_z);
 
    // To avoid numerical problems afterwards
    if (std::abs (yInFeatRef) < 1E-30)
      yInFeatRef  = 0;
    if (std::abs (xInFeatRef) < 1E-30)
      xInFeatRef  = 0;
    if (std::abs (zInFeatRef) < 1E-30)
      zInFeatRef  = 0;
 
 
    unsigned char bit4 = ((yInFeatRef > 0) || ((yInFeatRef == 0.0) && (xInFeatRef < 0))) ? 1 : 0;
    auto bit3 = static_cast<unsigned char> (((xInFeatRef > 0) || ((xInFeatRef == 0.0) && (yInFeatRef > 0))) ? !bit4 : bit4);
 
    assert (bit3 == 0 || bit3 == 1);
 
    int desc_index = (bit4<<3) + (bit3<<2);
 
    desc_index = desc_index << 1;
 
    if ((xInFeatRef * yInFeatRef > 0) || (xInFeatRef == 0.0))
      desc_index += (std::abs (xInFeatRef) >= std::abs (yInFeatRef)) ? 0 : 4;
    else
      desc_index += (std::abs (xInFeatRef) > std::abs (yInFeatRef)) ? 4 : 0;
 
    desc_index += zInFeatRef > 0 ? 1 : 0;
 
    // 2 RADII
    desc_index += (distance > radius1_2_) ? 2 : 0;
 
    int step_index = static_cast<int>(std::floor (binDistance[i_idx] +0.5));
    int volume_index = desc_index * (nr_bins+1);
 
    //Interpolation on the cosine (adjacent bins in the histogram)
    binDistance[i_idx] -= step_index;
    double intWeight = (1- std::abs (binDistance[i_idx]));
 
    if (binDistance[i_idx] > 0)
      shot[volume_index + ((step_index+1) % nr_bins)] += static_cast<float> (binDistance[i_idx]);
    else
      shot[volume_index + ((step_index - 1 + nr_bins) % nr_bins)] += - static_cast<float> (binDistance[i_idx]);
 
    //Interpolation on the distance (adjacent husks)
 
    if (distance > radius1_2_)   //external sphere
    {
      double radiusDistance = (distance - radius3_4_) / radius1_2_;
 
      if (distance > radius3_4_) //most external sector, votes only for itself
        intWeight += 1 - radiusDistance;  //peso=1-d
      else  //3/4 of radius, votes also for the internal sphere
      {
        intWeight += 1 + radiusDistance;
        shot[(desc_index - 2) * (nr_bins+1) + step_index] -= static_cast<float> (radiusDistance);
      }
    }
    else    //internal sphere
    {
      double radiusDistance = (distance - radius1_4_) / radius1_2_;
 
      if (distance < radius1_4_) //most internal sector, votes only for itself
        intWeight += 1 + radiusDistance;  //weight=1-d
      else  //3/4 of radius, votes also for the external sphere
      {
        intWeight += 1 - radiusDistance;
        shot[(desc_index + 2) * (nr_bins+1) + step_index] += static_cast<float> (radiusDistance);
      }
    }
 
    //Interpolation on the inclination (adjacent vertical volumes)
    double inclinationCos = zInFeatRef / distance;
    if (inclinationCos < - 1.0)
      inclinationCos = - 1.0;
    if (inclinationCos > 1.0)
      inclinationCos = 1.0;
 
    double inclination = std::acos (inclinationCos);
 
    assert (inclination >= 0.0 && inclination <= PST_RAD_180);
 
    if (inclination > PST_RAD_90 || (std::abs (inclination - PST_RAD_90) < 1e-30 && zInFeatRef <= 0))
    {
      double inclinationDistance = (inclination - PST_RAD_135) / PST_RAD_90;
      if (inclination > PST_RAD_135)
        intWeight += 1 - inclinationDistance;
      else
      {
        intWeight += 1 + inclinationDistance;
        assert ((desc_index + 1) * (nr_bins+1) + step_index >= 0 && (desc_index + 1) * (nr_bins+1) + step_index < descLength_);
        shot[(desc_index + 1) * (nr_bins+1) + step_index] -= static_cast<float> (inclinationDistance);
      }
    }
    else
    {
      double inclinationDistance = (inclination - PST_RAD_45) / PST_RAD_90;
      if (inclination < PST_RAD_45)
        intWeight += 1 + inclinationDistance;
      else
      {
        intWeight += 1 - inclinationDistance;
        assert ((desc_index - 1) * (nr_bins+1) + step_index >= 0 && (desc_index - 1) * (nr_bins+1) + step_index < descLength_);
        shot[(desc_index - 1) * (nr_bins+1) + step_index] += static_cast<float> (inclinationDistance);
      }
    }
 
    if (yInFeatRef != 0.0 || xInFeatRef != 0.0)
    {
      //Interpolation on the azimuth (adjacent horizontal volumes)
      double azimuth = std::atan2 (yInFeatRef, xInFeatRef);
 
      int sel = desc_index >> 2;
      double angularSectorSpan = PST_RAD_45;
      double angularSectorStart = - PST_RAD_PI_7_8;
 
      double azimuthDistance = (azimuth - (angularSectorStart + angularSectorSpan*sel)) / angularSectorSpan;
 
      assert ((azimuthDistance < 0.5 || areEquals (azimuthDistance, 0.5)) && (azimuthDistance > - 0.5 || areEquals (azimuthDistance, - 0.5)));
 
      azimuthDistance = (std::max)(- 0.5, std::min (azimuthDistance, 0.5));
 
      if (azimuthDistance > 0)
      {
        intWeight += 1 - azimuthDistance;
        int interp_index = (desc_index + 4) % maxAngularSectors_;
        assert (interp_index * (nr_bins+1) + step_index >= 0 && interp_index * (nr_bins+1) + step_index < descLength_);
        shot[interp_index * (nr_bins+1) + step_index] += static_cast<float> (azimuthDistance);
      }
      else
      {
        int interp_index = (desc_index - 4 + maxAngularSectors_) % maxAngularSectors_;
        assert (interp_index * (nr_bins+1) + step_index >= 0 && interp_index * (nr_bins+1) + step_index < descLength_);
        intWeight += 1 + azimuthDistance;
        shot[interp_index * (nr_bins+1) + step_index] -= static_cast<float> (azimuthDistance);
      }
 
    }
 
    assert (volume_index + step_index >= 0 &&  volume_index + step_index < descLength_);
    shot[volume_index + step_index] += static_cast<float> (intWeight);
  }
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT>::interpolateDoubleChannel (
  const pcl::Indices &indices,
  const std::vector<float> &sqr_dists,
  const int index,
  std::vector<double> &binDistanceShape,
  std::vector<double> &binDistanceColor,
  const int nr_bins_shape,
  const int nr_bins_color,
  Eigen::VectorXf &shot)
{
  const Eigen::Vector4f &central_point = (*input_)[(*indices_)[index]].getVector4fMap ();
  const PointRFT& current_frame = (*frames_)[index];
 
  int shapeToColorStride = nr_grid_sector_*(nr_bins_shape+1);
 
  Eigen::Vector4f current_frame_x (current_frame.x_axis[0], current_frame.x_axis[1], current_frame.x_axis[2], 0);
  Eigen::Vector4f current_frame_y (current_frame.y_axis[0], current_frame.y_axis[1], current_frame.y_axis[2], 0);
  Eigen::Vector4f current_frame_z (current_frame.z_axis[0], current_frame.z_axis[1], current_frame.z_axis[2], 0);
 
  for (std::size_t i_idx = 0; i_idx < indices.size (); ++i_idx)
  {
    if (!std::isfinite(binDistanceShape[i_idx]))
      continue;
 
    Eigen::Vector4f delta = (*surface_)[indices[i_idx]].getVector4fMap () - central_point;
    delta[3] = 0;
 
    // Compute the Euclidean norm
    double distance = sqrt (sqr_dists[i_idx]);
 
    if (areEquals (distance, 0.0))
      continue;
 
    double xInFeatRef = delta.dot (current_frame_x);
    double yInFeatRef = delta.dot (current_frame_y);
    double zInFeatRef = delta.dot (current_frame_z);
 
    // To avoid numerical problems afterwards
    if (std::abs (yInFeatRef) < 1E-30)
      yInFeatRef  = 0;
    if (std::abs (xInFeatRef) < 1E-30)
      xInFeatRef  = 0;
    if (std::abs (zInFeatRef) < 1E-30)
      zInFeatRef  = 0;
 
    unsigned char bit4 = ((yInFeatRef > 0) || ((yInFeatRef == 0.0) && (xInFeatRef < 0))) ? 1 : 0;
    auto bit3 = static_cast<unsigned char> (((xInFeatRef > 0) || ((xInFeatRef == 0.0) && (yInFeatRef > 0))) ? !bit4 : bit4);
 
    assert (bit3 == 0 || bit3 == 1);
 
    int desc_index = (bit4<<3) + (bit3<<2);
 
    desc_index = desc_index << 1;
 
    if ((xInFeatRef * yInFeatRef > 0) || (xInFeatRef == 0.0))
      desc_index += (std::abs (xInFeatRef) >= std::abs (yInFeatRef)) ? 0 : 4;
    else
      desc_index += (std::abs (xInFeatRef) > std::abs (yInFeatRef)) ? 4 : 0;
 
    desc_index += zInFeatRef > 0 ? 1 : 0;
 
    // 2 RADII
    desc_index += (distance > radius1_2_) ? 2 : 0;
 
    int step_index_shape = static_cast<int>(std::floor (binDistanceShape[i_idx] +0.5));
    int step_index_color = static_cast<int>(std::floor (binDistanceColor[i_idx] +0.5));
 
    int volume_index_shape = desc_index * (nr_bins_shape+1);
    int volume_index_color = shapeToColorStride + desc_index * (nr_bins_color+1);
 
    //Interpolation on the cosine (adjacent bins in the histrogram)
    binDistanceShape[i_idx] -= step_index_shape;
    binDistanceColor[i_idx] -= step_index_color;
 
    double intWeightShape = (1- std::abs (binDistanceShape[i_idx]));
    double intWeightColor = (1- std::abs (binDistanceColor[i_idx]));
 
    if (binDistanceShape[i_idx] > 0)
      shot[volume_index_shape + ((step_index_shape + 1) % nr_bins_shape)] += static_cast<float> (binDistanceShape[i_idx]);
    else
      shot[volume_index_shape + ((step_index_shape - 1 + nr_bins_shape) % nr_bins_shape)] -= static_cast<float> (binDistanceShape[i_idx]);
 
    if (binDistanceColor[i_idx] > 0)
      shot[volume_index_color + ((step_index_color+1) % nr_bins_color)] += static_cast<float> (binDistanceColor[i_idx]);
    else
      shot[volume_index_color + ((step_index_color - 1 + nr_bins_color) % nr_bins_color)] -= static_cast<float> (binDistanceColor[i_idx]);
 
    //Interpolation on the distance (adjacent husks)
 
    if (distance > radius1_2_)   //external sphere
    {
      double radiusDistance = (distance - radius3_4_) / radius1_2_;
 
      if (distance > radius3_4_) //most external sector, votes only for itself
      {
        intWeightShape += 1 - radiusDistance; //weight=1-d
        intWeightColor += 1 - radiusDistance; //weight=1-d
      }
      else  //3/4 of radius, votes also for the internal sphere
      {
        intWeightShape += 1 + radiusDistance;
        intWeightColor += 1 + radiusDistance;
        shot[(desc_index - 2) * (nr_bins_shape+1) + step_index_shape] -= static_cast<float> (radiusDistance);
        shot[shapeToColorStride + (desc_index - 2) * (nr_bins_color+1) + step_index_color] -= static_cast<float> (radiusDistance);
      }
    }
    else    //internal sphere
    {
      double radiusDistance = (distance - radius1_4_) / radius1_2_;
 
      if (distance < radius1_4_) //most internal sector, votes only for itself
      {
        intWeightShape += 1 + radiusDistance;
        intWeightColor += 1 + radiusDistance; //weight=1-d
      }
      else  //3/4 of radius, votes also for the external sphere
      {
        intWeightShape += 1 - radiusDistance; //weight=1-d
        intWeightColor += 1 - radiusDistance; //weight=1-d
        shot[(desc_index + 2) * (nr_bins_shape+1) + step_index_shape] += static_cast<float> (radiusDistance);
        shot[shapeToColorStride + (desc_index + 2) * (nr_bins_color+1) + step_index_color] += static_cast<float> (radiusDistance);
      }
    }
 
    //Interpolation on the inclination (adjacent vertical volumes)
    double inclinationCos = zInFeatRef / distance;
    if (inclinationCos < - 1.0)
      inclinationCos = - 1.0;
    if (inclinationCos > 1.0)
      inclinationCos = 1.0;
 
    double inclination = std::acos (inclinationCos);
 
    assert (inclination >= 0.0 && inclination <= PST_RAD_180);
 
    if (inclination > PST_RAD_90 || (std::abs (inclination - PST_RAD_90) < 1e-30 && zInFeatRef <= 0))
    {
      double inclinationDistance = (inclination - PST_RAD_135) / PST_RAD_90;
      if (inclination > PST_RAD_135)
      {
        intWeightShape += 1 - inclinationDistance;
        intWeightColor += 1 - inclinationDistance;
      }
      else
      {
        intWeightShape += 1 + inclinationDistance;
        intWeightColor += 1 + inclinationDistance;
        assert ((desc_index + 1) * (nr_bins_shape+1) + step_index_shape >= 0 && (desc_index + 1) * (nr_bins_shape+1) + step_index_shape < descLength_);
        assert (shapeToColorStride + (desc_index + 1) * (nr_bins_color+ 1) + step_index_color >= 0 && shapeToColorStride + (desc_index + 1) * (nr_bins_color+1) + step_index_color < descLength_);
        shot[(desc_index + 1) * (nr_bins_shape+1) + step_index_shape] -= static_cast<float> (inclinationDistance);
        shot[shapeToColorStride + (desc_index + 1) * (nr_bins_color+1) + step_index_color] -= static_cast<float> (inclinationDistance);
      }
    }
    else
    {
      double inclinationDistance = (inclination - PST_RAD_45) / PST_RAD_90;
      if (inclination < PST_RAD_45)
      {
        intWeightShape += 1 + inclinationDistance;
        intWeightColor += 1 + inclinationDistance;
      }
      else
      {
        intWeightShape += 1 - inclinationDistance;
        intWeightColor += 1 - inclinationDistance;
        assert ((desc_index - 1) * (nr_bins_shape+1) + step_index_shape >= 0 && (desc_index - 1) * (nr_bins_shape+1) + step_index_shape < descLength_);
        assert (shapeToColorStride + (desc_index - 1) * (nr_bins_color+ 1) + step_index_color >= 0 && shapeToColorStride + (desc_index - 1) * (nr_bins_color+1) + step_index_color < descLength_);
        shot[(desc_index - 1) * (nr_bins_shape+1) + step_index_shape] += static_cast<float> (inclinationDistance);
        shot[shapeToColorStride + (desc_index - 1) * (nr_bins_color+1) + step_index_color] += static_cast<float> (inclinationDistance);
      }
    }
 
    if (yInFeatRef != 0.0 || xInFeatRef != 0.0)
    {
      //Interpolation on the azimuth (adjacent horizontal volumes)
      double azimuth = std::atan2 (yInFeatRef, xInFeatRef);
 
      int sel = desc_index >> 2;
      double angularSectorSpan = PST_RAD_45;
      double angularSectorStart = - PST_RAD_PI_7_8;
 
      double azimuthDistance = (azimuth - (angularSectorStart + angularSectorSpan*sel)) / angularSectorSpan;
      assert ((azimuthDistance < 0.5 || areEquals (azimuthDistance, 0.5)) && (azimuthDistance > - 0.5 || areEquals (azimuthDistance, - 0.5)));
      azimuthDistance = (std::max)(- 0.5, std::min (azimuthDistance, 0.5));
 
      if (azimuthDistance > 0)
      {
        intWeightShape += 1 - azimuthDistance;
        intWeightColor += 1 - azimuthDistance;
        int interp_index = (desc_index + 4) % maxAngularSectors_;
        assert (interp_index * (nr_bins_shape+1) + step_index_shape >= 0 && interp_index * (nr_bins_shape+1) + step_index_shape < descLength_);
        assert (shapeToColorStride + interp_index * (nr_bins_color+1) + step_index_color >= 0 && shapeToColorStride + interp_index * (nr_bins_color+1) + step_index_color < descLength_);
        shot[interp_index * (nr_bins_shape+1) + step_index_shape] += static_cast<float> (azimuthDistance);
        shot[shapeToColorStride + interp_index * (nr_bins_color+1) + step_index_color] += static_cast<float> (azimuthDistance);
      }
      else
      {
        int interp_index = (desc_index - 4 + maxAngularSectors_) % maxAngularSectors_;
        intWeightShape += 1 + azimuthDistance;
        intWeightColor += 1 + azimuthDistance;
        assert (interp_index * (nr_bins_shape+1) + step_index_shape >= 0 && interp_index * (nr_bins_shape+1) + step_index_shape < descLength_);
        assert (shapeToColorStride + interp_index * (nr_bins_color+1) + step_index_color >= 0 && shapeToColorStride + interp_index * (nr_bins_color+1) + step_index_color < descLength_);
        shot[interp_index * (nr_bins_shape+1) + step_index_shape] -= static_cast<float> (azimuthDistance);
        shot[shapeToColorStride + interp_index * (nr_bins_color+1) + step_index_color] -= static_cast<float> (azimuthDistance);
      }
    }
 
    assert (volume_index_shape + step_index_shape >= 0 &&  volume_index_shape + step_index_shape < descLength_);
    assert (volume_index_color + step_index_color >= 0 &&  volume_index_color + step_index_color < descLength_);
    shot[volume_index_shape + step_index_shape] += static_cast<float> (intWeightShape);
    shot[volume_index_color + step_index_color] += static_cast<float> (intWeightColor);
  }
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT>::computePointSHOT (
  const int index, const pcl::Indices &indices, const std::vector<float> &sqr_dists, Eigen::VectorXf &shot)
{
  // Clear the resultant shot
  shot.setZero ();
  const auto nNeighbors = indices.size ();
  //Skip the current feature if the number of its neighbors is not sufficient for its description
  if (nNeighbors < 5)
  {
    PCL_WARN ("[pcl::%s::computePointSHOT] Warning! Neighborhood has less than 5 vertexes. Aborting description of point with index %d\n",
                  getClassName ().c_str (), (*indices_)[index]);
 
    shot.setConstant(descLength_, 1, std::numeric_limits<float>::quiet_NaN () );
 
    return;
  }
 
  //If shape description is enabled, compute the bins activated by each neighbor of the current feature in the shape histogram
  std::vector<double> binDistanceShape;
  if (b_describe_shape_)
  {
    this->createBinDistanceShape (index, indices, binDistanceShape);
  }
 
  //If color description is enabled, compute the bins activated by each neighbor of the current feature in the color histogram
  std::vector<double> binDistanceColor;
  if (b_describe_color_)
  {
    binDistanceColor.reserve (nNeighbors);
 
    //unsigned char redRef = (*input_)[(*indices_)[index]].rgba >> 16 & 0xFF;
    //unsigned char greenRef = (*input_)[(*indices_)[index]].rgba >> 8& 0xFF;
    //unsigned char blueRef = (*input_)[(*indices_)[index]].rgba & 0xFF;
    unsigned char redRef = (*input_)[(*indices_)[index]].r;
    unsigned char greenRef = (*input_)[(*indices_)[index]].g;
    unsigned char blueRef = (*input_)[(*indices_)[index]].b;
 
    float LRef, aRef, bRef;
 
    RGB2CIELAB (redRef, greenRef, blueRef, LRef, aRef, bRef);
    LRef /= 100.0f;
    aRef /= 120.0f;
    bRef /= 120.0f;    //normalized LAB components (0<L<1, -1<a<1, -1<b<1)
 
    for (const auto& idx: indices)
    {
      unsigned char red = (*surface_)[idx].r;
      unsigned char green = (*surface_)[idx].g;
      unsigned char blue = (*surface_)[idx].b;
 
      float L, a, b;
 
      RGB2CIELAB (red, green, blue, L, a, b);
      L /= 100.0f;
      a /= 120.0f;
      b /= 120.0f;   //normalized LAB components (0<L<1, -1<a<1, -1<b<1)
 
      double colorDistance = (std::fabs (LRef - L) + ((std::fabs (aRef - a) + std::fabs (bRef - b)) / 2)) /3;
 
      if (colorDistance > 1.0)
        colorDistance = 1.0;
      if (colorDistance < 0.0)
        colorDistance = 0.0;
 
      binDistanceColor.push_back (colorDistance * nr_color_bins_);
    }
  }
 
  //Apply quadrilinear interpolation on the activated bins in the shape and/or color histogram(s)
 
  if (b_describe_shape_ && b_describe_color_)
    interpolateDoubleChannel (indices, sqr_dists, index, binDistanceShape, binDistanceColor,
                              nr_shape_bins_, nr_color_bins_,
                              shot);
  else if (b_describe_color_)
    interpolateSingleChannel (indices, sqr_dists, index, binDistanceColor, nr_color_bins_, shot);
  else
    interpolateSingleChannel (indices, sqr_dists, index, binDistanceShape, nr_shape_bins_, shot);
 
  // Normalize the final histogram
  this->normalizeHistogram (shot, descLength_);
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTEstimation<PointInT, PointNT, PointOutT, PointRFT>::computePointSHOT (
  const int index, const pcl::Indices &indices, const std::vector<float> &sqr_dists, Eigen::VectorXf &shot)
{
  //Skip the current feature if the number of its neighbors is not sufficient for its description
  if (indices.size () < 5)
  {
    PCL_WARN ("[pcl::%s::computePointSHOT] Warning! Neighborhood has less than 5 vertexes. Aborting description of point with index %d\n",
                  getClassName ().c_str (), (*indices_)[index]);
 
    shot.setConstant(descLength_, 1, std::numeric_limits<float>::quiet_NaN () );
 
    return;
  }
 
   // Clear the resultant shot
  std::vector<double> binDistanceShape;
  this->createBinDistanceShape (index, indices, binDistanceShape);
 
  // Interpolate
  shot.setZero ();
  interpolateSingleChannel (indices, sqr_dists, index, binDistanceShape, nr_shape_bins_, shot);
 
  // Normalize the final histogram
  this->normalizeHistogram (shot, descLength_);
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTEstimation<PointInT, PointNT, PointOutT, PointRFT>::computeFeature (pcl::PointCloud<PointOutT> &output)
{
  descLength_ = nr_grid_sector_ * (nr_shape_bins_+1);
 
  sqradius_ = search_radius_ * search_radius_;
  radius3_4_ = (search_radius_*3) / 4;
  radius1_4_ = search_radius_ / 4;
  radius1_2_ = search_radius_ / 2;
 
  assert(descLength_ == 352);
 
  Eigen::VectorXf shot;
  shot.setZero (descLength_);
 
  // Allocate enough space to hold the results
  // \note This resize is irrelevant for a radiusSearch ().
  pcl::Indices nn_indices (k_);
  std::vector<float> nn_dists (k_);
 
  output.is_dense = true;
  // Iterating over the entire index vector
  for (std::size_t idx = 0; idx < indices_->size (); ++idx)
  {
    bool lrf_is_nan = false;
    const PointRFT& current_frame = (*frames_)[idx];
    if (!std::isfinite (current_frame.x_axis[0]) ||
        !std::isfinite (current_frame.y_axis[0]) ||
        !std::isfinite (current_frame.z_axis[0]))
    {
      PCL_WARN ("[pcl::%s::computeFeature] The local reference frame is not valid! Aborting description of point with index %d\n",
        getClassName ().c_str (), (*indices_)[idx]);
      lrf_is_nan = true;
    }
 
    if (!isFinite ((*input_)[(*indices_)[idx]]) ||
        lrf_is_nan ||
        this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0)
    {
      // Copy into the resultant cloud
      for (int d = 0; d < descLength_; ++d)
        output[idx].descriptor[d] = std::numeric_limits<float>::quiet_NaN ();
      for (int d = 0; d < 9; ++d)
        output[idx].rf[d] = std::numeric_limits<float>::quiet_NaN ();
 
      output.is_dense = false;
      continue;
    }
 
    // Estimate the SHOT descriptor at each patch
    computePointSHOT (static_cast<int> (idx), nn_indices, nn_dists, shot);
 
    // Copy into the resultant cloud
    for (int d = 0; d < descLength_; ++d)
      output[idx].descriptor[d] = shot[d];
    for (int d = 0; d < 3; ++d)
    {
      output[idx].rf[d + 0] = (*frames_)[idx].x_axis[d];
      output[idx].rf[d + 3] = (*frames_)[idx].y_axis[d];
      output[idx].rf[d + 6] = (*frames_)[idx].z_axis[d];
    }
  }
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
pcl::SHOTColorEstimation<PointInT, PointNT, PointOutT, PointRFT>::computeFeature (pcl::PointCloud<PointOutT> &output)
{
  // Compute the current length of the descriptor
  descLength_ = (b_describe_shape_) ? nr_grid_sector_*(nr_shape_bins_+1) : 0;
  descLength_ +=   (b_describe_color_) ? nr_grid_sector_*(nr_color_bins_+1) : 0;
 
  assert( (!b_describe_color_ && b_describe_shape_ && descLength_ == 352) ||
          (b_describe_color_ && !b_describe_shape_ && descLength_ == 992) ||
          (b_describe_color_ && b_describe_shape_ && descLength_ == 1344)
        );
 
  // Useful values
  sqradius_ = search_radius_*search_radius_;
  radius3_4_ = (search_radius_*3) / 4;
  radius1_4_ = search_radius_ / 4;
  radius1_2_ = search_radius_ / 2;
 
  Eigen::VectorXf shot;
  shot.setZero (descLength_);
 
  // Allocate enough space to hold the results
  // \note This resize is irrelevant for a radiusSearch ().
  pcl::Indices nn_indices (k_);
  std::vector<float> nn_dists (k_);
 
  output.is_dense = true;
  // Iterating over the entire index vector
  for (std::size_t idx = 0; idx < indices_->size (); ++idx)
  {
    bool lrf_is_nan = false;
    const PointRFT& current_frame = (*frames_)[idx];
    if (!std::isfinite (current_frame.x_axis[0]) ||
        !std::isfinite (current_frame.y_axis[0]) ||
        !std::isfinite (current_frame.z_axis[0]))
    {
      PCL_WARN ("[pcl::%s::computeFeature] The local reference frame is not valid! Aborting description of point with index %d\n",
        getClassName ().c_str (), (*indices_)[idx]);
      lrf_is_nan = true;
    }
 
    if (!isFinite ((*input_)[(*indices_)[idx]]) ||
        lrf_is_nan ||
        this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0)
    {
      // Copy into the resultant cloud
      for (int d = 0; d < descLength_; ++d)
        output[idx].descriptor[d] = std::numeric_limits<float>::quiet_NaN ();
      for (int d = 0; d < 9; ++d)
        output[idx].rf[d] = std::numeric_limits<float>::quiet_NaN ();
 
      output.is_dense = false;
      continue;
    }
 
    // Compute the SHOT descriptor for the current 3D feature
    computePointSHOT (static_cast<int> (idx), nn_indices, nn_dists, shot);
 
    // Copy into the resultant cloud
    for (int d = 0; d < descLength_; ++d)
      output[idx].descriptor[d] = shot[d];
    for (int d = 0; d < 3; ++d)
    {
      output[idx].rf[d + 0] = (*frames_)[idx].x_axis[d];
      output[idx].rf[d + 3] = (*frames_)[idx].y_axis[d];
      output[idx].rf[d + 6] = (*frames_)[idx].z_axis[d];
    }
  }
}
 
#define PCL_INSTANTIATE_SHOTEstimationBase(T,NT,OutT,RFT) template class PCL_EXPORTS pcl::SHOTEstimationBase<T,NT,OutT,RFT>;
#define PCL_INSTANTIATE_SHOTEstimation(T,NT,OutT,RFT) template class PCL_EXPORTS pcl::SHOTEstimation<T,NT,OutT,RFT>;
#define PCL_INSTANTIATE_SHOTColorEstimation(T,NT,OutT,RFT) template class PCL_EXPORTS pcl::SHOTColorEstimation<T,NT,OutT,RFT>;
 
#endif    // PCL_FEATURES_IMPL_SHOT_H_