void ppfmap::CudaPPFMatch<PointT, NormalT>::detect(
const PointCloudPtr cloud,
const NormalsPtr normals,
Eigen::Affine3f& trans,
pcl::Correspondences& correspondences,
int& votes) {
std::vector<Pose> poses;
detect(cloud, normals, poses);
clusterPoses(
poses,
translation_threshold,
rotation_threshold,
trans,
correspondences,
votes);
}
template <typename PointSource, typename PointTarget> void
pcl::PPFRegistration<PointSource, PointTarget>::computeTransformation (PointCloudSource &output, const Eigen::Matrix4f& guess)
{
if (!search_method_)
{
PCL_ERROR("[pcl::PPFRegistration::computeTransformation] Search method not set - skipping computeTransformation!\n");
return;
}
if (guess != Eigen::Matrix4f::Identity ())
{
PCL_ERROR("[pcl::PPFRegistration::computeTransformation] setting initial transform (guess) not implemented!\n");
}
PoseWithVotesList voted_poses;
std::vector <std::vector <unsigned int> > accumulator_array;
accumulator_array.resize (input_->points.size ());
size_t aux_size = static_cast<size_t> (floor (2 * M_PI / search_method_->getAngleDiscretizationStep ()));
for (size_t i = 0; i < input_->points.size (); ++i)
{
std::vector<unsigned int> aux (aux_size);
accumulator_array[i] = aux;
}
PCL_INFO ("Accumulator array size: %u x %u.\n", accumulator_array.size (), accumulator_array.back ().size ());
// Consider every <scene_reference_point_sampling_rate>-th point as the reference point => fix s_r
float f1, f2, f3, f4;
for (size_t scene_reference_index = 0; scene_reference_index < target_->points.size (); scene_reference_index += scene_reference_point_sampling_rate_)
{
Eigen::Vector3f scene_reference_point = target_->points[scene_reference_index].getVector3fMap (),
scene_reference_normal = target_->points[scene_reference_index].getNormalVector3fMap ();
Eigen::AngleAxisf rotation_sg (acosf (scene_reference_normal.dot (Eigen::Vector3f::UnitX ())),
scene_reference_normal.cross (Eigen::Vector3f::UnitX ()). normalized());
Eigen::Affine3f transform_sg (Eigen::Translation3f (rotation_sg * ((-1) * scene_reference_point)) * rotation_sg);
// For every other point in the scene => now have pair (s_r, s_i) fixed
std::vector<int> indices;
std::vector<float> distances;
scene_search_tree_->radiusSearch (target_->points[scene_reference_index],
search_method_->getModelDiameter () /2,
indices,
distances);
for(size_t i = 0; i < indices.size (); ++i)
// for(size_t i = 0; i < target_->points.size (); ++i)
{
//size_t scene_point_index = i;
size_t scene_point_index = indices[i];
if (scene_reference_index != scene_point_index)
{
if (/*pcl::computePPFPairFeature*/pcl::computePairFeatures (target_->points[scene_reference_index].getVector4fMap (),
target_->points[scene_reference_index].getNormalVector4fMap (),
target_->points[scene_point_index].getVector4fMap (),
target_->points[scene_point_index].getNormalVector4fMap (),
f1, f2, f3, f4))
{
std::vector<std::pair<size_t, size_t> > nearest_indices;
search_method_->nearestNeighborSearch (f1, f2, f3, f4, nearest_indices);
// Compute alpha_s angle
Eigen::Vector3f scene_point = target_->points[scene_point_index].getVector3fMap ();
Eigen::AngleAxisf rotation_sg (acosf (scene_reference_normal.dot (Eigen::Vector3f::UnitX ())),
scene_reference_normal.cross (Eigen::Vector3f::UnitX ()).normalized ());
Eigen::Affine3f transform_sg = Eigen::Translation3f ( rotation_sg * ((-1) * scene_reference_point)) * rotation_sg;
// float alpha_s = acos (Eigen::Vector3f::UnitY ().dot ((transform_sg * scene_point).normalized ()));
Eigen::Vector3f scene_point_transformed = transform_sg * scene_point;
float alpha_s = atan2f ( -scene_point_transformed(2), scene_point_transformed(1));
if ( alpha_s != alpha_s)
{
PCL_ERROR ("alpha_s is nan\n");
continue;
}
if (sin (alpha_s) * scene_point_transformed(2) < 0.0f)
alpha_s *= (-1);
alpha_s *= (-1);
// Go through point pairs in the model with the same discretized feature
for (std::vector<std::pair<size_t, size_t> >::iterator v_it = nearest_indices.begin (); v_it != nearest_indices.end (); ++ v_it)
{
size_t model_reference_index = v_it->first,
model_point_index = v_it->second;
// Calculate angle alpha = alpha_m - alpha_s
float alpha = search_method_->alpha_m_[model_reference_index][model_point_index] - alpha_s;
unsigned int alpha_discretized = static_cast<unsigned int> (floor (alpha) + floor (M_PI / search_method_->getAngleDiscretizationStep ()));
accumulator_array[model_reference_index][alpha_discretized] ++;
}
}
else PCL_ERROR ("[pcl::PPFRegistration::computeTransformation] Computing pair feature vector between points %zu and %zu went wrong.\n", scene_reference_index, scene_point_index);
}
}
size_t max_votes_i = 0, max_votes_j = 0;
unsigned int max_votes = 0;
for (size_t i = 0; i < accumulator_array.size (); ++i)
for (size_t j = 0; j < accumulator_array.back ().size (); ++j)
{
if (accumulator_array[i][j] > max_votes)
{
max_votes = accumulator_array[i][j];
max_votes_i = i;
max_votes_j = j;
}
// Reset accumulator_array for the next set of iterations with a new scene reference point
accumulator_array[i][j] = 0;
}
Eigen::Vector3f model_reference_point = input_->points[max_votes_i].getVector3fMap (),
model_reference_normal = input_->points[max_votes_i].getNormalVector3fMap ();
Eigen::AngleAxisf rotation_mg (acosf (model_reference_normal.dot (Eigen::Vector3f::UnitX ())), model_reference_normal.cross (Eigen::Vector3f::UnitX ()).normalized ());
Eigen::Affine3f transform_mg = Eigen::Translation3f ( rotation_mg * ((-1) * model_reference_point)) * rotation_mg;
Eigen::Affine3f max_transform =
transform_sg.inverse () *
Eigen::AngleAxisf ((static_cast<float> (max_votes_j) - floorf (static_cast<float> (M_PI) / search_method_->getAngleDiscretizationStep ())) * search_method_->getAngleDiscretizationStep (), Eigen::Vector3f::UnitX ()) *
transform_mg;
voted_poses.push_back (PoseWithVotes (max_transform, max_votes));
}
PCL_DEBUG ("Done with the Hough Transform ...\n");
// Cluster poses for filtering out outliers and obtaining more precise results
PoseWithVotesList results;
clusterPoses (voted_poses, results);
pcl::transformPointCloud (*input_, output, results.front ().pose);
transformation_ = final_transformation_ = results.front ().pose.matrix ();
converged_ = true;
}