41 #ifndef PCL_FEATURES_IMPL_CRH_H_ 42 #define PCL_FEATURES_IMPL_CRH_H_ 44 #include <pcl/features/crh.h> 45 #include <pcl/common/fft/kiss_fftr.h> 47 #include <pcl/common/transforms.h> 50 template<
typename Po
intInT,
typename Po
intNT,
typename Po
intOutT>
57 PCL_ERROR (
"[pcl::%s::computeFeature] No input dataset containing normals was given!\n", getClassName ().c_str ());
58 output.width = output.height = 0;
59 output.points.clear ();
63 if (normals_->points.size () != surface_->points.size ())
65 PCL_ERROR (
"[pcl::%s::computeFeature] The number of points in the input dataset differs from the number of points in the dataset containing the normals!\n", getClassName ().c_str ());
66 output.width = output.height = 0;
67 output.points.clear ();
71 Eigen::Vector3f plane_normal;
72 plane_normal[0] = -centroid_[0];
73 plane_normal[1] = -centroid_[1];
74 plane_normal[2] = -centroid_[2];
75 Eigen::Vector3f z_vector = Eigen::Vector3f::UnitZ ();
76 plane_normal.normalize ();
77 Eigen::Vector3f axis = plane_normal.cross (z_vector);
78 double rotation = -asin (axis.norm ());
82 int bin_angle = 360 / nbins;
84 Eigen::Affine3f transformPC (Eigen::AngleAxisf (static_cast<float> (rotation), axis));
87 grid.
points.resize (indices_->size ());
89 for (
size_t i = 0; i < indices_->size (); i++)
91 grid.
points[i].getVector4fMap () = surface_->points[(*indices_)[i]].getVector4fMap ();
92 grid.
points[i].getNormalVector4fMap () = normals_->points[(*indices_)[i]].getNormalVector4fMap ();
99 kiss_fft_scalar * spatial_data =
new kiss_fft_scalar[nbins]();
102 float sum_w = 0, w = 0;
104 for (
size_t i = 0; i < grid.
points.size (); ++i)
106 bin =
static_cast<int> ((((atan2 (grid.
points[i].normal_y, grid.
points[i].normal_x) + M_PI) * 180 / M_PI) / bin_angle)) % nbins;
107 w = std::sqrt (grid.
points[i].normal_y * grid.
points[i].normal_y + grid.
points[i].normal_x * grid.
points[i].normal_x);
109 spatial_data[bin] += w;
112 for (
int i = 0; i < nbins; ++i)
113 spatial_data[i] /= sum_w;
116 kiss_fftr_cfg mycfg = kiss_fftr_alloc (nbins, 0, NULL, NULL);
117 kiss_fftr (mycfg, spatial_data, freq_data);
119 output.points.resize (1);
120 output.width = output.height = 1;
122 output.points[0].histogram[0] = freq_data[0].
r / freq_data[0].
r;
124 for (
int i = 1; i < (nbins / 2); i++, k += 2)
126 output.points[0].histogram[k] = freq_data[i].
r / freq_data[0].
r;
127 output.points[0].histogram[k + 1] = freq_data[i].
i / freq_data[0].
r;
130 output.points[0].histogram[nbins - 1] = freq_data[nbins / 2].
r / freq_data[0].
r;
132 delete[] spatial_data;
137 #define PCL_INSTANTIATE_CRHEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::CRHEstimation<T,NT,OutT>; 139 #endif // PCL_FEATURES_IMPL_CRH_H_
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
void transformPointCloudWithNormals(const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
Transform a point cloud and rotate its normals using an Eigen transform.
Define standard C methods and C++ classes that are common to all methods.
CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset co...