Class that registers two point clouds based on their sets of PPFSignatures. Please refer to the following publication for more details: B. Drost, M. Ulrich, N. Navab, S. Ilic Model Globally, Match Locally: Efficient and Robust 3D Object Recognition 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 13-18 June 2010, San Francisco, CA. More...
#include <ppf_registration.h>
Classes | |
| struct | PoseWithVotes |
| Structure for storing a pose (represented as an Eigen::Affine3f) and an integer for counting votes. More... | |
Public Types | |
| typedef pcl::PointCloud < PointSource > | PointCloudSource |
| typedef PointCloudSource::ConstPtr | PointCloudSourceConstPtr |
| typedef PointCloudSource::Ptr | PointCloudSourcePtr |
| typedef pcl::PointCloud < PointTarget > | PointCloudTarget |
| typedef PointCloudTarget::ConstPtr | PointCloudTargetConstPtr |
| typedef PointCloudTarget::Ptr | PointCloudTargetPtr |
| typedef std::vector < PoseWithVotes, Eigen::aligned_allocator < PoseWithVotes > > | PoseWithVotesList |
Public Member Functions | |
| float | getPositionClusteringThreshold () |
| Returns the parameter defining the position difference clustering parameter - distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm) | |
| float | getRotationClusteringThreshold () |
| Returns the parameter defining the rotation clustering threshold. | |
| unsigned int | getSceneReferencePointSamplingRate () |
| Returns the parameter for the scene reference point sampling rate of the algorithm. | |
| PPFHashMapSearch::Ptr | getSearchMethod () |
| Getter function for the search method of the class. | |
| PPFRegistration () | |
| Empty constructor that initializes all the parameters of the algorithm with default values. | |
| void | setInputTarget (const PointCloudTargetConstPtr &cloud) |
| Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to) | |
| void | setPositionClusteringThreshold (float clustering_position_diff_threshold) |
| Method for setting the position difference clustering parameter. | |
| void | setRotationClusteringThreshold (float clustering_rotation_diff_threshold) |
| Method for setting the rotation clustering parameter. | |
| void | setSceneReferencePointSamplingRate (unsigned int scene_reference_point_sampling_rate) |
| Method for setting the scene reference point sampling rate. | |
| void | setSearchMethod (PPFHashMapSearch::Ptr search_method) |
| Function that sets the search method for the algorithm. | |
Private Member Functions | |
| void | clusterPoses (PoseWithVotesList &poses, PoseWithVotesList &result) |
| Method that clusters a set of given poses by using the clustering thresholds and their corresponding number of votes (see publication for more details) | |
| void | computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess) |
| Method that calculates the transformation between the input_ and target_ point clouds, based on the PPF features. | |
| bool | posesWithinErrorBounds (Eigen::Affine3f &pose1, Eigen::Affine3f &pose2) |
| Method that checks whether two poses are close together - based on the clustering threshold parameters of the class. | |
Static Private Member Functions | |
| static bool | clusterVotesCompareFunction (const std::pair< size_t, unsigned int > &a, const std::pair< size_t, unsigned int > &b) |
| static method used for the std::sort function to order two pairs <index, votes> by the number of votes (unsigned integer value) | |
| static bool | poseWithVotesCompareFunction (const PoseWithVotes &a, const PoseWithVotes &b) |
| static method used for the std::sort function to order two PoseWithVotes instances by their number of votes | |
Private Attributes | |
| float | clustering_position_diff_threshold_ |
| position and rotation difference thresholds below which two poses are considered to be in the same cluster (for the clustering phase of the algorithm) | |
| float | clustering_rotation_diff_threshold_ |
| unsigned int | scene_reference_point_sampling_rate_ |
| parameter for the sampling rate of the scene reference points | |
| pcl::KdTreeFLANN< PointTarget > ::Ptr | scene_search_tree_ |
| use a kd-tree with range searches of range max_dist to skip an O(N) pass through the point cloud | |
| PPFHashMapSearch::Ptr | search_method_ |
| the search method that is going to be used to find matching feature pairs | |
Detailed Description
template<typename PointSource, typename PointTarget>
class pcl::PPFRegistration< PointSource, PointTarget >
Class that registers two point clouds based on their sets of PPFSignatures. Please refer to the following publication for more details: B. Drost, M. Ulrich, N. Navab, S. Ilic Model Globally, Match Locally: Efficient and Robust 3D Object Recognition 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 13-18 June 2010, San Francisco, CA.
- Note:
- This class works in tandem with the PPFEstimation class
Definition at line 144 of file ppf_registration.h.
Member Typedef Documentation
| typedef pcl::PointCloud<PointSource> pcl::PPFRegistration< PointSource, PointTarget >::PointCloudSource |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 171 of file ppf_registration.h.
| typedef PointCloudSource::ConstPtr pcl::PPFRegistration< PointSource, PointTarget >::PointCloudSourceConstPtr |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 173 of file ppf_registration.h.
| typedef PointCloudSource::Ptr pcl::PPFRegistration< PointSource, PointTarget >::PointCloudSourcePtr |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 172 of file ppf_registration.h.
| typedef pcl::PointCloud<PointTarget> pcl::PPFRegistration< PointSource, PointTarget >::PointCloudTarget |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 175 of file ppf_registration.h.
| typedef PointCloudTarget::ConstPtr pcl::PPFRegistration< PointSource, PointTarget >::PointCloudTargetConstPtr |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 177 of file ppf_registration.h.
| typedef PointCloudTarget::Ptr pcl::PPFRegistration< PointSource, PointTarget >::PointCloudTargetPtr |
Reimplemented from pcl::Registration< PointSource, PointTarget >.
Definition at line 176 of file ppf_registration.h.
| typedef std::vector<PoseWithVotes, Eigen::aligned_allocator<PoseWithVotes> > pcl::PPFRegistration< PointSource, PointTarget >::PoseWithVotesList |
Definition at line 161 of file ppf_registration.h.
Constructor & Destructor Documentation
| pcl::PPFRegistration< PointSource, PointTarget >::PPFRegistration | ( | ) | [inline] |
Empty constructor that initializes all the parameters of the algorithm with default values.
Definition at line 181 of file ppf_registration.h.
Member Function Documentation
| void pcl::PPFRegistration< PointSource, PointTarget >::clusterPoses | ( | PoseWithVotesList & | poses, |
| PoseWithVotesList & | result | ||
| ) | [private] |
Method that clusters a set of given poses by using the clustering thresholds and their corresponding number of votes (see publication for more details)
- Todo:
- some kind of threshold for determining whether a cluster has enough votes or not... now just taking the first three clusters
averaging rotations by just averaging the quaternions in 4D space - reference "On Averaging Rotations" by CLAUS GRAMKOW
Definition at line 254 of file ppf_registration.hpp.
| bool pcl::PPFRegistration< PointSource, PointTarget >::clusterVotesCompareFunction | ( | const std::pair< size_t, unsigned int > & | a, |
| const std::pair< size_t, unsigned int > & | b | ||
| ) | [static, private] |
static method used for the std::sort function to order two pairs <index, votes> by the number of votes (unsigned integer value)
Definition at line 345 of file ppf_registration.hpp.
| void pcl::PPFRegistration< PointSource, PointTarget >::computeTransformation | ( | PointCloudSource & | output, |
| const Eigen::Matrix4f & | guess | ||
| ) | [private] |
Method that calculates the transformation between the input_ and target_ point clouds, based on the PPF features.
Definition at line 120 of file ppf_registration.hpp.
| float pcl::PPFRegistration< PointSource, PointTarget >::getPositionClusteringThreshold | ( | ) | [inline] |
Returns the parameter defining the position difference clustering parameter - distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm)
Definition at line 201 of file ppf_registration.h.
| float pcl::PPFRegistration< PointSource, PointTarget >::getRotationClusteringThreshold | ( | ) | [inline] |
Returns the parameter defining the rotation clustering threshold.
Definition at line 213 of file ppf_registration.h.
| unsigned int pcl::PPFRegistration< PointSource, PointTarget >::getSceneReferencePointSamplingRate | ( | ) | [inline] |
Returns the parameter for the scene reference point sampling rate of the algorithm.
Definition at line 223 of file ppf_registration.h.
| PPFHashMapSearch::Ptr pcl::PPFRegistration< PointSource, PointTarget >::getSearchMethod | ( | ) | [inline] |
Getter function for the search method of the class.
Definition at line 235 of file ppf_registration.h.
| bool pcl::PPFRegistration< PointSource, PointTarget >::posesWithinErrorBounds | ( | Eigen::Affine3f & | pose1, |
| Eigen::Affine3f & | pose2 | ||
| ) | [private] |
Method that checks whether two poses are close together - based on the clustering threshold parameters of the class.
Definition at line 320 of file ppf_registration.hpp.
| bool pcl::PPFRegistration< PointSource, PointTarget >::poseWithVotesCompareFunction | ( | const PoseWithVotes & | a, |
| const PoseWithVotes & | b | ||
| ) | [static, private] |
static method used for the std::sort function to order two PoseWithVotes instances by their number of votes
Definition at line 336 of file ppf_registration.hpp.
| void pcl::PPFRegistration< PointSource, PointTarget >::setInputTarget | ( | const PointCloudTargetConstPtr & | cloud | ) |
Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to)
- Parameters:
-
cloud the input point cloud target
Definition at line 109 of file ppf_registration.hpp.
| void pcl::PPFRegistration< PointSource, PointTarget >::setPositionClusteringThreshold | ( | float | clustering_position_diff_threshold | ) | [inline] |
Method for setting the position difference clustering parameter.
- Parameters:
-
clustering_position_diff_threshold distance threshold below which two poses are considered close enough to be in the same cluster (for the clustering phase of the algorithm)
Definition at line 194 of file ppf_registration.h.
| void pcl::PPFRegistration< PointSource, PointTarget >::setRotationClusteringThreshold | ( | float | clustering_rotation_diff_threshold | ) | [inline] |
Method for setting the rotation clustering parameter.
- Parameters:
-
clustering_rotation_diff_threshold rotation difference threshold below which two poses are considered to be in the same cluster (for the clustering phase of the algorithm)
Definition at line 208 of file ppf_registration.h.
| void pcl::PPFRegistration< PointSource, PointTarget >::setSceneReferencePointSamplingRate | ( | unsigned int | scene_reference_point_sampling_rate | ) | [inline] |
Method for setting the scene reference point sampling rate.
- Parameters:
-
scene_reference_point_sampling_rate sampling rate for the scene reference point
Definition at line 219 of file ppf_registration.h.
| void pcl::PPFRegistration< PointSource, PointTarget >::setSearchMethod | ( | PPFHashMapSearch::Ptr | search_method | ) | [inline] |
Function that sets the search method for the algorithm.
- Note:
- Right now, the only available method is the one initially proposed by the authors - by using a hash map with discretized feature vectors
- Parameters:
-
search_method smart pointer to the search method to be set
Definition at line 231 of file ppf_registration.h.
Member Data Documentation
float pcl::PPFRegistration< PointSource, PointTarget >::clustering_position_diff_threshold_ [private] |
position and rotation difference thresholds below which two poses are considered to be in the same cluster (for the clustering phase of the algorithm)
Definition at line 258 of file ppf_registration.h.
float pcl::PPFRegistration< PointSource, PointTarget >::clustering_rotation_diff_threshold_ [private] |
Definition at line 258 of file ppf_registration.h.
unsigned int pcl::PPFRegistration< PointSource, PointTarget >::scene_reference_point_sampling_rate_ [private] |
parameter for the sampling rate of the scene reference points
Definition at line 254 of file ppf_registration.h.
pcl::KdTreeFLANN<PointTarget>::Ptr pcl::PPFRegistration< PointSource, PointTarget >::scene_search_tree_ [private] |
use a kd-tree with range searches of range max_dist to skip an O(N) pass through the point cloud
Definition at line 261 of file ppf_registration.h.
PPFHashMapSearch::Ptr pcl::PPFRegistration< PointSource, PointTarget >::search_method_ [private] |
the search method that is going to be used to find matching feature pairs
Definition at line 251 of file ppf_registration.h.
The documentation for this class was generated from the following files: