sac_model_plane.hpp

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 * $Id: sac_model_plane.hpp 6144 2012-07-04 22:06:28Z rusu $
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#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_PLANE_H_
#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_PLANE_H_

#include <pcl/sample_consensus/sac_model_plane.h>
#include <pcl/common/centroid.h>
#include <pcl/common/eigen.h>
#include <pcl/common/concatenate.h>

template <typename PointT> bool
pcl::SampleConsensusModelPlane<PointT>::isSampleGood (const std::vector<int> &samples) const
{
  // Need an extra check in case the sample selection is empty
  if (samples.empty ())
    return (false);
  // Get the values at the two points
  pcl::Array4fMapConst p0 = input_->points[samples[0]].getArray4fMap ();
  pcl::Array4fMapConst p1 = input_->points[samples[1]].getArray4fMap ();
  pcl::Array4fMapConst p2 = input_->points[samples[2]].getArray4fMap ();

  Eigen::Array4f dy1dy2 = (p1-p0) / (p2-p0);

  return ( (dy1dy2[0] != dy1dy2[1]) || (dy1dy2[2] != dy1dy2[1]) );
}

template <typename PointT> bool
pcl::SampleConsensusModelPlane<PointT>::computeModelCoefficients (
      const std::vector<int> &samples, Eigen::VectorXf &model_coefficients)
{
  // Need 3 samples
  if (samples.size () != 3)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::computeModelCoefficients] Invalid set of samples given (%zu)!\n", samples.size ());
    return (false);
  }

  pcl::Array4fMapConst p0 = input_->points[samples[0]].getArray4fMap ();
  pcl::Array4fMapConst p1 = input_->points[samples[1]].getArray4fMap ();
  pcl::Array4fMapConst p2 = input_->points[samples[2]].getArray4fMap ();

  // Compute the segment values (in 3d) between p1 and p0
  Eigen::Array4f p1p0 = p1 - p0;
  // Compute the segment values (in 3d) between p2 and p0
  Eigen::Array4f p2p0 = p2 - p0;

  // Avoid some crashes by checking for collinearity here
  Eigen::Array4f dy1dy2 = p1p0 / p2p0;
  if ( (dy1dy2[0] == dy1dy2[1]) && (dy1dy2[2] == dy1dy2[1]) )          // Check for collinearity
    return (false);

  // Compute the plane coefficients from the 3 given points in a straightforward manner
  // calculate the plane normal n = (p2-p1) x (p3-p1) = cross (p2-p1, p3-p1)
  model_coefficients.resize (4);
  model_coefficients[0] = p1p0[1] * p2p0[2] - p1p0[2] * p2p0[1];
  model_coefficients[1] = p1p0[2] * p2p0[0] - p1p0[0] * p2p0[2];
  model_coefficients[2] = p1p0[0] * p2p0[1] - p1p0[1] * p2p0[0];
  model_coefficients[3] = 0;

  // Normalize
  model_coefficients.normalize ();

  // ... + d = 0
  model_coefficients[3] = -1 * (model_coefficients.template head<4>().dot (p0.matrix ()));

  return (true);
}

template <typename PointT> void
pcl::SampleConsensusModelPlane<PointT>::getDistancesToModel (
      const Eigen::VectorXf &model_coefficients, std::vector<double> &distances)
{
  // Needs a valid set of model coefficients
  if (model_coefficients.size () != 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::getDistancesToModel] Invalid number of model coefficients given (%zu)!\n", model_coefficients.size ());
    return;
  }

  distances.resize (indices_->size ());

  // Iterate through the 3d points and calculate the distances from them to the plane
  for (size_t i = 0; i < indices_->size (); ++i)
  {
    // Calculate the distance from the point to the plane normal as the dot product
    // D = (P-A).N/|N|
    /*distances[i] = fabs (model_coefficients[0] * input_->points[(*indices_)[i]].x +
                         model_coefficients[1] * input_->points[(*indices_)[i]].y +
                         model_coefficients[2] * input_->points[(*indices_)[i]].z +
                         model_coefficients[3]);*/
    Eigen::Vector4f pt (input_->points[(*indices_)[i]].x,
                        input_->points[(*indices_)[i]].y,
                        input_->points[(*indices_)[i]].z,
                        1);
    distances[i] = fabs (model_coefficients.dot (pt));
  }
}

template <typename PointT> void
pcl::SampleConsensusModelPlane<PointT>::selectWithinDistance (
      const Eigen::VectorXf &model_coefficients, const double threshold, std::vector<int> &inliers)
{
  // Needs a valid set of model coefficients
  if (model_coefficients.size () != 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::selectWithinDistance] Invalid number of model coefficients given (%zu)!\n", model_coefficients.size ());
    return;
  }

  int nr_p = 0;
  inliers.resize (indices_->size ());

  // Iterate through the 3d points and calculate the distances from them to the plane
  for (size_t i = 0; i < indices_->size (); ++i)
  {
    // Calculate the distance from the point to the plane normal as the dot product
    // D = (P-A).N/|N|
    Eigen::Vector4f pt (input_->points[(*indices_)[i]].x,
                        input_->points[(*indices_)[i]].y,
                        input_->points[(*indices_)[i]].z,
                        1);
    if (fabs (model_coefficients.dot (pt)) < threshold)
    {
      // Returns the indices of the points whose distances are smaller than the threshold
      inliers[nr_p] = (*indices_)[i];
      nr_p++;
    }
  }
  inliers.resize (nr_p);
}

template <typename PointT> int
pcl::SampleConsensusModelPlane<PointT>::countWithinDistance (
      const Eigen::VectorXf &model_coefficients, const double threshold)
{
  // Needs a valid set of model coefficients
  if (model_coefficients.size () != 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::countWithinDistance] Invalid number of model coefficients given (%zu)!\n", model_coefficients.size ());
    return (0);
  }

  int nr_p = 0;

  // Iterate through the 3d points and calculate the distances from them to the plane
  for (size_t i = 0; i < indices_->size (); ++i)
  {
    // Calculate the distance from the point to the plane normal as the dot product
    // D = (P-A).N/|N|
    Eigen::Vector4f pt (input_->points[(*indices_)[i]].x,
                        input_->points[(*indices_)[i]].y,
                        input_->points[(*indices_)[i]].z,
                        1);
    if (fabs (model_coefficients.dot (pt)) < threshold)
      nr_p++;
  }
  return (nr_p);
}

template <typename PointT> void
pcl::SampleConsensusModelPlane<PointT>::optimizeModelCoefficients (
      const std::vector<int> &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients)
{
  // Needs a valid set of model coefficients
  if (model_coefficients.size () != 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::optimizeModelCoefficients] Invalid number of model coefficients given (%zu)!\n", model_coefficients.size ());
    optimized_coefficients = model_coefficients;
    return;
  }

  // Need at least 3 points to estimate a plane
  if (inliers.size () < 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::optimizeModelCoefficients] Not enough inliers found to support a model (%zu)! Returning the same coefficients.\n", inliers.size ());
    optimized_coefficients = model_coefficients;
    return;
  }

  Eigen::Vector4f plane_parameters;

  // Use Least-Squares to fit the plane through all the given sample points and find out its coefficients
  EIGEN_ALIGN16 Eigen::Matrix3f covariance_matrix;
  Eigen::Vector4f xyz_centroid;

  computeMeanAndCovarianceMatrix (*input_, inliers, covariance_matrix, xyz_centroid);

  // Compute the model coefficients
  EIGEN_ALIGN16 Eigen::Vector3f::Scalar eigen_value;
  EIGEN_ALIGN16 Eigen::Vector3f eigen_vector;
  pcl::eigen33 (covariance_matrix, eigen_value, eigen_vector);

  // Hessian form (D = nc . p_plane (centroid here) + p)
  optimized_coefficients.resize (4);
  optimized_coefficients[0] = eigen_vector [0];
  optimized_coefficients[1] = eigen_vector [1];
  optimized_coefficients[2] = eigen_vector [2];
  optimized_coefficients[3] = 0;
  optimized_coefficients[3] = -1 * optimized_coefficients.dot (xyz_centroid);
}

template <typename PointT> void
pcl::SampleConsensusModelPlane<PointT>::projectPoints (
      const std::vector<int> &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields)
{
  // Needs a valid set of model coefficients
  if (model_coefficients.size () != 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::projectPoints] Invalid number of model coefficients given (%zu)!\n", model_coefficients.size ());
    return;
  }

  projected_points.header = input_->header;
  projected_points.is_dense = input_->is_dense;

  Eigen::Vector4f mc (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);

  // normalize the vector perpendicular to the plane...
  mc.normalize ();
  // ... and store the resulting normal as a local copy of the model coefficients
  Eigen::Vector4f tmp_mc = model_coefficients;
  tmp_mc[0] = mc[0];
  tmp_mc[1] = mc[1];
  tmp_mc[2] = mc[2];

  // Copy all the data fields from the input cloud to the projected one?
  if (copy_data_fields)
  {
    // Allocate enough space and copy the basics
    projected_points.points.resize (input_->points.size ());
    projected_points.width    = input_->width;
    projected_points.height   = input_->height;

    typedef typename pcl::traits::fieldList<PointT>::type FieldList;
    // Iterate over each point
    for (size_t i = 0; i < input_->points.size (); ++i)
      // Iterate over each dimension
      pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> (input_->points[i], projected_points.points[i]));

    // Iterate through the 3d points and calculate the distances from them to the plane
    for (size_t i = 0; i < inliers.size (); ++i)
    {
      // Calculate the distance from the point to the plane
      Eigen::Vector4f p (input_->points[inliers[i]].x,
                         input_->points[inliers[i]].y,
                         input_->points[inliers[i]].z,
                         1);
      // use normalized coefficients to calculate the scalar projection
      float distance_to_plane = tmp_mc.dot (p);

      pcl::Vector4fMap pp = projected_points.points[inliers[i]].getVector4fMap ();
      pp = p - mc * distance_to_plane;        // mc[3] = 0, therefore the 3rd coordinate is safe
    }
  }
  else
  {
    // Allocate enough space and copy the basics
    projected_points.points.resize (inliers.size ());
    projected_points.width    = static_cast<uint32_t> (inliers.size ());
    projected_points.height   = 1;

    typedef typename pcl::traits::fieldList<PointT>::type FieldList;
    // Iterate over each point
    for (size_t i = 0; i < inliers.size (); ++i)
      // Iterate over each dimension
      pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> (input_->points[inliers[i]], projected_points.points[i]));

    // Iterate through the 3d points and calculate the distances from them to the plane
    for (size_t i = 0; i < inliers.size (); ++i)
    {
      // Calculate the distance from the point to the plane
      Eigen::Vector4f p (input_->points[inliers[i]].x,
                         input_->points[inliers[i]].y,
                         input_->points[inliers[i]].z,
                         1);
      // use normalized coefficients to calculate the scalar projection
      float distance_to_plane = tmp_mc.dot (p);

      pcl::Vector4fMap pp = projected_points.points[i].getVector4fMap ();
      pp = p - mc * distance_to_plane;        // mc[3] = 0, therefore the 3rd coordinate is safe
    }
  }
}

template <typename PointT> bool
pcl::SampleConsensusModelPlane<PointT>::doSamplesVerifyModel (
      const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold)
{
  // Needs a valid set of model coefficients
  if (model_coefficients.size () != 4)
  {
    PCL_ERROR ("[pcl::SampleConsensusModelPlane::doSamplesVerifyModel] Invalid number of model coefficients given (%zu)!\n", model_coefficients.size ());
    return (false);
  }

  for (std::set<int>::const_iterator it = indices.begin (); it != indices.end (); ++it)
  {
    Eigen::Vector4f pt (input_->points[*it].x,
                        input_->points[*it].y,
                        input_->points[*it].z,
                        1);
    if (fabs (model_coefficients.dot (pt)) > threshold)
      return (false);
  }

  return (true);
}

#define PCL_INSTANTIATE_SampleConsensusModelPlane(T) template class PCL_EXPORTS pcl::SampleConsensusModelPlane<T>;

#endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_PLANE_H_