Point Cloud Library (PCL)
1.9.1
|
41 #ifndef PCL_REGISTRATION_CORRESPONDENCE_ESTIMATION_NORMAL_SHOOTING_H_
42 #define PCL_REGISTRATION_CORRESPONDENCE_ESTIMATION_NORMAL_SHOOTING_H_
44 #include <pcl/registration/correspondence_types.h>
45 #include <pcl/registration/correspondence_estimation.h>
49 namespace registration
77 template <
typename Po
intSource,
typename Po
intTarget,
typename NormalT,
typename Scalar =
float>
81 typedef boost::shared_ptr<CorrespondenceEstimationNormalShooting<PointSource, PointTarget, NormalT, Scalar> >
Ptr;
82 typedef boost::shared_ptr<const CorrespondenceEstimationNormalShooting<PointSource, PointTarget, NormalT, Scalar> >
ConstPtr;
116 , source_normals_transformed_ ()
119 corr_name_ =
"CorrespondenceEstimationNormalShooting";
158 double max_distance = std::numeric_limits<double>::max ());
169 double max_distance = std::numeric_limits<double>::max ());
187 virtual boost::shared_ptr< CorrespondenceEstimationBase<PointSource, PointTarget, Scalar> >
219 #include <pcl/registration/impl/correspondence_estimation_normal_shooting.hpp>
PointCloudSource::Ptr PointCloudSourcePtr
This file defines compatibility wrappers for low level I/O functions.
boost::shared_ptr< PointCloud< PointSource > > Ptr
CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which h...
pcl::search::KdTree< PointTarget >::Ptr KdTreePtr
virtual void determineReciprocalCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max())
Determine the reciprocal correspondences between input and target cloud.
unsigned int getKSearch() const
Get the number of nearest neighbours considered in the target point cloud for computing correspondenc...
virtual ~CorrespondenceEstimationNormalShooting()
Empty destructor.
void setSourceNormals(const NormalsConstPtr &normals)
Set the normals computed on the source point cloud.
pcl::PointCloud< NormalT > PointCloudNormals
CorrespondenceEstimationNormalShooting()
Empty constructor.
void setSourceNormals(pcl::PCLPointCloud2::ConstPtr cloud2)
Blob method for setting the source normals.
Abstract CorrespondenceEstimationBase class.
virtual boost::shared_ptr< CorrespondenceEstimationBase< PointSource, PointTarget, Scalar > > clone() const
Clone and cast to CorrespondenceEstimationBase.
pcl::search::KdTree< PointTarget > KdTree
boost::shared_ptr< KdTree< PointT, Tree > > Ptr
PointCloudNormals::ConstPtr NormalsConstPtr
bool initCompute()
Internal computation initialization.
void setKSearch(unsigned int k)
Set the number of nearest neighbours to be considered in the target point cloud.
bool requiresSourceNormals() const
See if this rejector requires source normals.
PointCloudTarget::ConstPtr PointCloudTargetConstPtr
boost::shared_ptr< const CorrespondenceEstimationNormalShooting< PointSource, PointTarget, NormalT, Scalar > > ConstPtr
PointCloudTarget::Ptr PointCloudTargetPtr
std::string corr_name_
The correspondence estimation method name.
PointCloudSource::ConstPtr PointCloudSourceConstPtr
boost::shared_ptr< CorrespondenceEstimationNormalShooting< PointSource, PointTarget, NormalT, Scalar > > Ptr
void determineCorrespondences(pcl::Correspondences &correspondences, double max_distance=std::numeric_limits< double >::max())
Determine the correspondences between input and target cloud.
std::vector< pcl::Correspondence, Eigen::aligned_allocator< pcl::Correspondence > > Correspondences
pcl::PointCloud< PointTarget > PointCloudTarget
boost::shared_ptr< const PointCloud< PointSource > > ConstPtr
pcl::PointCloud< PointSource > PointCloudSource
boost::shared_ptr< ::pcl::PCLPointCloud2 const > ConstPtr
NormalsConstPtr getSourceNormals() const
Get the normals of the source point cloud.
PointCloudNormals::Ptr NormalsPtr
void fromPCLPointCloud2(const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.