Point Cloud Library (PCL) 1.15.0
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cppf.hpp
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40
41#ifndef PCL_FEATURES_IMPL_CPPF_H_
42#define PCL_FEATURES_IMPL_CPPF_H_
43
44#include <pcl/features/cppf.h>
45#include <pcl/search/kdtree.h> // for KdTree
46
47//////////////////////////////////////////////////////////////////////////////////////////////
48template <typename PointInT, typename PointNT, typename PointOutT>
50 : FeatureFromNormals <PointInT, PointNT, PointOutT> ()
51{
52 feature_name_ = "CPPFEstimation";
53 // Slight hack in order to pass the check for the presence of a search method in Feature::initCompute ()
54 Feature<PointInT, PointOutT>::tree_.reset (new pcl::search::KdTree <PointInT> ());
56}
57
58
59//////////////////////////////////////////////////////////////////////////////////////////////
60template <typename PointInT, typename PointNT, typename PointOutT> void
62{
63 // Initialize output container
64 output.points.clear ();
65 output.points.reserve (indices_->size () * input_->size ());
66 output.is_dense = true;
67 // Compute point pair features for every pair of points in the cloud
68 for (const auto& i: *indices_)
69 {
70 for (std::size_t j = 0 ; j < input_->size (); ++j)
71 {
72 PointOutT p;
73 // No need to calculate feature for identity pair (i, j) as they aren't used in future calculations
74 // @TODO: resolve issue with comparison in a better manner
75 if (static_cast<std::size_t>(i) != j)
76 {
77 if (
78 pcl::computeCPPFPairFeature ((*input_)[i].getVector4fMap (),
79 (*normals_)[i].getNormalVector4fMap (),
80 (*input_)[i].getRGBVector4i (),
81 (*input_)[j].getVector4fMap (),
82 (*normals_)[j].getNormalVector4fMap (),
83 (*input_)[j].getRGBVector4i (),
84 p.f1, p.f2, p.f3, p.f4, p.f5, p.f6, p.f7, p.f8, p.f9, p.f10))
85 {
86 // Calculate alpha_m angle
87 Eigen::Vector3f model_reference_point = (*input_)[i].getVector3fMap (),
88 model_reference_normal = (*normals_)[i].getNormalVector3fMap (),
89 model_point = (*input_)[j].getVector3fMap ();
90 Eigen::AngleAxisf rotation_mg (std::acos (model_reference_normal.dot (Eigen::Vector3f::UnitX ())),
91 model_reference_normal.cross (Eigen::Vector3f::UnitX ()).normalized ());
92 Eigen::Affine3f transform_mg = Eigen::Translation3f ( rotation_mg * ((-1) * model_reference_point)) * rotation_mg;
93
94 Eigen::Vector3f model_point_transformed = transform_mg * model_point;
95 float angle = std::atan2 ( -model_point_transformed(2), model_point_transformed(1));
96 if (std::sin (angle) * model_point_transformed(2) < 0.0f)
97 angle *= (-1);
98 p.alpha_m = -angle;
99 }
100 else
101 {
102 PCL_ERROR ("[pcl::%s::computeFeature] Computing pair feature vector between points %lu and %lu went wrong.\n", getClassName ().c_str (), i, j);
103 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 ();
104 output.is_dense = false;
105 }
106 }
107 else
108 {
109 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 ();
110 output.is_dense = false;
111 }
112
113 output.push_back (p);
114 }
115 }
116 // overwrite the sizes done by Feature::initCompute ()
117 output.height = 1;
118 output.width = output.size ();
119}
120
121#define PCL_INSTANTIATE_CPPFEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::CPPFEstimation<T,NT,OutT>;
122
123
124#endif // PCL_FEATURES_IMPL_CPPF_H_
Class that calculates the "surflet" features for each pair in the given pointcloud.
Definition cppf.h:87
CPPFEstimation()
Empty Constructor.
Definition cppf.hpp:49
Feature represents the base feature class.
Definition feature.h:107
std::string feature_name_
The feature name.
Definition feature.h:220
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)