40 #ifndef PCL_FEATURES_IMPL_PPF_H_ 41 #define PCL_FEATURES_IMPL_PPF_H_ 43 #include <pcl/features/ppf.h> 44 #include <pcl/features/pfh.h> 47 template <
typename Po
intInT,
typename Po
intNT,
typename Po
intOutT>
59 template <
typename Po
intInT,
typename Po
intNT,
typename Po
intOutT>
void 65 output.
width =
static_cast<uint32_t
> (output.
points.size ());
69 for (
size_t index_i = 0; index_i <
indices_->size (); ++index_i)
71 size_t i = (*indices_)[index_i];
72 for (
size_t j = 0 ; j <
input_->points.size (); ++j)
79 normals_->points[i].getNormalVector4fMap (),
80 input_->points[j].getVector4fMap (),
81 normals_->points[j].getNormalVector4fMap (),
82 p.f1, p.f2, p.f3, p.f4))
85 Eigen::Vector3f model_reference_point =
input_->points[i].getVector3fMap (),
86 model_reference_normal =
normals_->points[i].getNormalVector3fMap (),
87 model_point =
input_->points[j].getVector3fMap ();
88 float rotation_angle = acosf (model_reference_normal.dot (Eigen::Vector3f::UnitX ()));
89 bool parallel_to_x = (model_reference_normal.y() == 0.0f && model_reference_normal.z() == 0.0f);
90 Eigen::Vector3f rotation_axis = (parallel_to_x)?(Eigen::Vector3f::UnitY ()):(model_reference_normal.cross (Eigen::Vector3f::UnitX ()). normalized());
91 Eigen::AngleAxisf rotation_mg (rotation_angle, rotation_axis);
92 Eigen::Affine3f transform_mg (Eigen::Translation3f ( rotation_mg * ((-1) * model_reference_point)) * rotation_mg);
94 Eigen::Vector3f model_point_transformed = transform_mg * model_point;
95 float angle = atan2f ( -model_point_transformed(2), model_point_transformed(1));
96 if (sin (angle) * model_point_transformed(2) < 0.0f)
102 PCL_ERROR (
"[pcl::%s::computeFeature] Computing pair feature vector between points %u and %u went wrong.\n",
getClassName ().c_str (), i, j);
103 p.f1 = p.f2 = p.f3 = p.f4 = p.alpha_m = std::numeric_limits<float>::quiet_NaN ();
111 p.f1 = p.f2 = p.f3 = p.f4 = p.alpha_m = std::numeric_limits<float>::quiet_NaN ();
120 #define PCL_INSTANTIATE_PPFEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::PPFEstimation<T,NT,OutT>; 123 #endif // PCL_FEATURES_IMPL_PPF_H_ search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...
Class that calculates the "surflet" features for each pair in the given pointcloud.
std::vector< PointT, Eigen::aligned_allocator< PointT > > points
The point data.
std::string feature_name_
The feature name.
IndicesPtr indices_
A pointer to the vector of point indices to use.
const std::string & getClassName() const
Get a string representation of the name of this class.
uint32_t height
The point cloud height (if organized as an image-structure).
uint32_t width
The point cloud width (if organized as an image-structure).
PointCloud represents the base class in PCL for storing collections of 3D points. ...
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values).
PointCloudConstPtr input_
The input point cloud dataset.
Feature represents the base feature class.
PPFEstimation()
Empty Constructor.
PCL_EXPORTS bool computePairFeatures(const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4)
Compute the 4-tuple representation containing the three angles and one distance between two points re...