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cppf.hpp
/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2011, Alexandru-Eugen Ichim
* Copyright (c) 2012-, Open Perception, Inc.
* Copyright (c) 2013, Martin Szarski
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#ifndef PCL_FEATURES_IMPL_CPPF_H_
#define PCL_FEATURES_IMPL_CPPF_H_
#include <pcl/features/cppf.h>
#include <pcl/search/kdtree.h> // for KdTree
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT>
pcl::CPPFEstimation<PointInT, PointNT, PointOutT>::CPPFEstimation ()
: FeatureFromNormals <PointInT, PointNT, PointOutT> ()
{
feature_name_ = "CPPFEstimation";
// Slight hack in order to pass the check for the presence of a search method in Feature::initCompute ()
Feature<PointInT, PointOutT>::tree_.reset (new pcl::search::KdTree <PointInT> ());
Feature<PointInT, PointOutT>::search_radius_ = 1.0f;
}
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT> void
pcl::CPPFEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output)
{
// Initialize output container
output.points.clear ();
output.points.reserve (indices_->size () * input_->size ());
output.is_dense = true;
// Compute point pair features for every pair of points in the cloud
for (const auto& i: *indices_)
{
for (std::size_t j = 0 ; j < input_->size (); ++j)
{
PointOutT p;
// No need to calculate feature for identity pair (i, j) as they aren't used in future calculations
// @TODO: resolve issue with comparison in a better manner
if (static_cast<std::size_t>(i) != j)
{
if (
pcl::computeCPPFPairFeature ((*input_)[i].getVector4fMap (),
(*normals_)[i].getNormalVector4fMap (),
(*input_)[i].getRGBVector4i (),
(*input_)[j].getVector4fMap (),
(*normals_)[j].getNormalVector4fMap (),
(*input_)[j].getRGBVector4i (),
p.f1, p.f2, p.f3, p.f4, p.f5, p.f6, p.f7, p.f8, p.f9, p.f10))
{
// Calculate alpha_m angle
Eigen::Vector3f model_reference_point = (*input_)[i].getVector3fMap (),
model_reference_normal = (*normals_)[i].getNormalVector3fMap (),
model_point = (*input_)[j].getVector3fMap ();
Eigen::AngleAxisf rotation_mg (std::acos (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::Vector3f model_point_transformed = transform_mg * model_point;
float angle = std::atan2 ( -model_point_transformed(2), model_point_transformed(1));
if (std::sin (angle) * model_point_transformed(2) < 0.0f)
angle *= (-1);
p.alpha_m = -angle;
}
else
{
PCL_ERROR ("[pcl::%s::computeFeature] Computing pair feature vector between points %lu and %lu went wrong.\n", getClassName ().c_str (), i, j);
p.f1 = p.f2 = p.f3 = p.f4 = p.f5 = p.f6 = p.f7 = p.f8 = p.f9 = p.f10 = p.alpha_m = std::numeric_limits<float>::quiet_NaN ();
output.is_dense = false;
}
}
else
{
p.f1 = p.f2 = p.f3 = p.f4 = p.f5 = p.f6 = p.f7 = p.f8 = p.f9 = p.f10 = p.alpha_m = std::numeric_limits<float>::quiet_NaN ();
output.is_dense = false;
}
output.push_back (p);
}
}
// overwrite the sizes done by Feature::initCompute ()
output.height = 1;
output.width = output.size ();
}
#define PCL_INSTANTIATE_CPPFEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::CPPFEstimation<T,NT,OutT>;
#endif // PCL_FEATURES_IMPL_CPPF_H_
pcl::CPPFEstimation::CPPFEstimation
CPPFEstimation()
Empty Constructor.
Definition cppf.hpp:49
pcl::FeatureFromNormals::FeatureFromNormals
FeatureFromNormals()
Empty constructor.
Definition feature.h:329
pcl::Feature::search_radius_
double search_radius_
The nearest neighbors search radius for each point.
Definition feature.h:237
pcl::Feature::feature_name_
std::string feature_name_
The feature name.
Definition feature.h:220
pcl::Feature::tree_
KdTreePtr tree_
A pointer to the spatial search object.
Definition feature.h:231
pcl::PointCloudOut
pcl::computeCPPFPairFeature
PCL_EXPORTS bool computeCPPFPairFeature(const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &c1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &c2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7, float &f8, float &f9, float &f10)