pfhrgb.hpp
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#ifndef PCL_FEATURES_IMPL_PFHRGB_H_
#define PCL_FEATURES_IMPL_PFHRGB_H_
#include <pcl/features/pfhrgb.h>
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT> bool
pcl::PFHRGBEstimation<PointInT, PointNT, PointOutT>::computeRGBPairFeatures (
const pcl::PointCloud<PointInT> &cloud, const pcl::PointCloud<PointNT> &normals,
int p_idx, int q_idx,
float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7)
{
Eigen::Vector4i colors1 (cloud[p_idx].r, cloud[p_idx].g, cloud[p_idx].b, 0),
colors2 (cloud[q_idx].r, cloud[q_idx].g, cloud[q_idx].b, 0);
pcl::computeRGBPairFeatures (cloud[p_idx].getVector4fMap (), normals[p_idx].getNormalVector4fMap (),
colors1,
cloud[q_idx].getVector4fMap (), normals[q_idx].getNormalVector4fMap (),
colors2,
f1, f2, f3, f4, f5, f6, f7);
return (true);
}
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT> void
pcl::PFHRGBEstimation<PointInT, PointNT, PointOutT>::computePointPFHRGBSignature (
const pcl::PointCloud<PointInT> &cloud, const pcl::PointCloud<PointNT> &normals,
const pcl::Indices &indices, int nr_split, Eigen::VectorXf &pfhrgb_histogram)
{
int h_index, h_p;
// Clear the resultant point histogram
pfhrgb_histogram.setZero ();
// Factorization constant
float hist_incr = 100.0f / static_cast<float> (indices.size () * (indices.size () - 1) / 2);
// Iterate over all the points in the neighborhood
for (const auto& index_i: indices)
{
for (const auto& index_j: indices)
{
// Avoid unnecessary returns
if (index_i == index_j)
continue;
// Compute the pair NNi to NNj
if (!computeRGBPairFeatures (cloud, normals, index_i, index_j,
pfhrgb_tuple_[0], pfhrgb_tuple_[1], pfhrgb_tuple_[2], pfhrgb_tuple_[3],
pfhrgb_tuple_[4], pfhrgb_tuple_[5], pfhrgb_tuple_[6]))
continue;
// Normalize the f1, f2, f3, f5, f6, f7 features and push them in the histogram
f_index_[0] = static_cast<int> (std::floor (nr_split * ((pfhrgb_tuple_[0] + M_PI) * d_pi_)));
// @TODO: confirm "not to do for i == 3"
for (int i = 1; i < 3; ++i)
{
const float feature_value = nr_split * ((pfhrgb_tuple_[i] + 1.0) * 0.5);
f_index_[i] = static_cast<int> (std::floor (feature_value));
}
// color ratios are in [-1, 1]
for (int i = 4; i < 7; ++i)
{
const float feature_value = nr_split * ((pfhrgb_tuple_[i] + 1.0) * 0.5);
f_index_[i] = static_cast<int> (std::floor (feature_value));
}
for (auto& feature: f_index_)
{
feature = std::min(nr_split - 1, std::max(0, feature));
}
// Copy into the histogram
h_index = 0;
h_p = 1;
for (int d = 0; d < 3; ++d)
{
h_index += h_p * f_index_[d];
h_p *= nr_split;
}
pfhrgb_histogram[h_index] += hist_incr;
// and the colors
h_index = 125;
h_p = 1;
for (int d = 4; d < 7; ++d)
{
h_index += h_p * f_index_[d];
h_p *= nr_split;
}
pfhrgb_histogram[h_index] += hist_incr;
}
}
}
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointNT, typename PointOutT> void
pcl::PFHRGBEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output)
{
/// nr_subdiv^3 for RGB and nr_subdiv^3 for the angular features
pfhrgb_histogram_.setZero (2 * nr_subdiv_ * nr_subdiv_ * nr_subdiv_);
pfhrgb_tuple_.setZero (7);
// 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_);
// Iterating over the entire index vector
for (std::size_t idx = 0; idx < indices_->size (); ++idx)
{
this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists);
// Estimate the PFH signature at each patch
computePointPFHRGBSignature (*surface_, *normals_, nn_indices, nr_subdiv_, pfhrgb_histogram_);
std::copy_n (pfhrgb_histogram_.data (), pfhrgb_histogram_.size (),
output[idx].histogram);
}
}
#define PCL_INSTANTIATE_PFHRGBEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::PFHRGBEstimation<T,NT,OutT>;
#endif /* PCL_FEATURES_IMPL_PFHRGB_H_ */
pcl::PFHRGBEstimation::computeRGBPairFeatures
bool computeRGBPairFeatures(const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, int p_idx, int q_idx, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7)
Definition: pfhrgb.hpp:47
pcl::PFHRGBEstimation::computeFeature
void computeFeature(PointCloudOut &output) override
Abstract feature estimation method.
Definition: pfhrgb.hpp:135
pcl::PFHRGBEstimation::computePointPFHRGBSignature
void computePointPFHRGBSignature(const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, int nr_split, Eigen::VectorXf &pfhrgb_histogram)
Definition: pfhrgb.hpp:64
pcl::PointCloud< PointInT >
pcl::computeRGBPairFeatures
PCL_EXPORTS bool computeRGBPairFeatures(const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &colors1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &colors2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7)
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
M_PI
#define M_PI
Definition: pcl_macros.h:201