Class implementing a 3D correspondence grouping algorithm that can deal with multiple instances of a model template found into a given scene. Each correspondence casts a vote for a reference point in a 3D Hough Space. The remaining 3 DOF are taken into account by associating each correspondence with a local Reference Frame. The suggested PointModelRfT is pcl::ReferenceFrame. More...
#include <hough_3d.h>
Public Types | |
| typedef pcl::PointCloud < PointModelRfT > | ModelRfCloud |
| typedef ModelRfCloud::ConstPtr | ModelRfCloudConstPtr |
| typedef ModelRfCloud::Ptr | ModelRfCloudPtr |
| typedef pcl::PointCloud < PointModelT > | PointCloud |
| typedef PointCloud::ConstPtr | PointCloudConstPtr |
| typedef PointCloud::Ptr | PointCloudPtr |
| typedef pcl::CorrespondenceGrouping < PointModelT, PointSceneT > ::SceneCloudConstPtr | SceneCloudConstPtr |
| typedef pcl::PointCloud < PointSceneRfT > | SceneRfCloud |
| typedef SceneRfCloud::ConstPtr | SceneRfCloudConstPtr |
| typedef SceneRfCloud::Ptr | SceneRfCloudPtr |
Public Member Functions | |
| double | getHoughBinSize () const |
| Gets the size of each bin into the Hough space. | |
| double | getHoughThreshold () const |
| Gets the minimum number of votes in the Hough space needed to infer the presence of a model instance into the scene cloud. | |
| ModelRfCloudConstPtr | getInputRf () const |
| Getter for the input dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the input dataset. | |
| float | getLocalRfNormalsSearchRadius () const |
| If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to compute the normals in order to subsequently compute the RF (if not set a default 15 nearest neighbors search is performed). | |
| float | getLocalRfSearchRadius () const |
| If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to do so. | |
| SceneRfCloudConstPtr | getSceneRf () const |
| Getter for the scene dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the scene dataset. | |
| bool | getUseDistanceWeight () const |
| Gets whether the vote casting procedure uses the correspondence's distance as a score. | |
| bool | getUseInterpolation () const |
| Gets whether the vote casting procedure interpolates the score between neighboring bins of the Hough space or not. | |
| Hough3DGrouping () | |
| Constructor. | |
| bool | recognize (std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &transformations) |
| The main function, recognizes instances of the model into the scene set by the user. | |
| bool | recognize (std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > &transformations, std::vector< pcl::Correspondences > &clustered_corrs) |
| The main function, recognizes instances of the model into the scene set by the user. | |
| void | setHoughBinSize (double bin_size) |
| Sets the size of each bin into the Hough space. | |
| void | setHoughThreshold (double threshold) |
| Sets the minimum number of votes in the Hough space needed to infer the presence of a model instance into the scene cloud. | |
| void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. | |
| void | setInputRf (const ModelRfCloudConstPtr &input_rf) |
| Provide a pointer to the input dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the input dataset. | |
| void | setLocalRfNormalsSearchRadius (float local_rf_normals_search_radius) |
| If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to compute the normals in order to subsequently compute the RF (if not set a default 15 nearest neighbors search is performed). | |
| void | setLocalRfSearchRadius (float local_rf_search_radius) |
| If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to do so. | |
| void | setModelSceneCorrespondences (const CorrespondencesConstPtr &corrs) |
| Provide a pointer to the precomputed correspondences between points in the input dataset and points in the scene dataset. The correspondences are going to be clustered into different model instances by the algorithm. | |
| void | setSceneCloud (const SceneCloudConstPtr &scene) |
| Provide a pointer to the scene dataset (i.e. the cloud in which the algorithm has to search for instances of the input model) | |
| void | setSceneRf (const SceneRfCloudConstPtr &scene_rf) |
| Provide a pointer to the scene dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the scene dataset. | |
| void | setUseDistanceWeight (bool use_distance_weight) |
| Sets whether the vote casting procedure uses the correspondence's distance as a score. | |
| void | setUseInterpolation (bool use_interpolation) |
| Sets whether the vote casting procedure interpolates the score between neighboring bins of the Hough space or not. | |
| bool | train () |
| Call this function after setting the input, the input_rf and the hough_bin_size parameters to perform an off line training of the algorithm. This might be useful if one wants to perform once and for all a pre-computation of votes that only concern the models, increasing the on-line efficiency of the grouping algorithm. The algorithm is automatically trained on the first invocation of the recognize method or the cluster method if this training function has not been manually invoked. | |
Protected Member Functions | |
| void | clusterCorrespondences (std::vector< Correspondences > &model_instances) |
| Cluster the input correspondences in order to distinguish between different instances of the model into the scene. | |
| template<typename PointType , typename PointRfType > | |
| void | computeRf (const boost::shared_ptr< const pcl::PointCloud< PointType > > &input, pcl::PointCloud< PointRfType > &rf) |
| Computes the reference frame for an input cloud. | |
| bool | houghVoting () |
| Finds the transformation matrix between the input and the scene cloud for a set of correspondences using a RANSAC algorithm. | |
Protected Attributes | |
| std::vector< Eigen::Matrix4f, Eigen::aligned_allocator < Eigen::Matrix4f > > | found_transformations_ |
| Transformations found by clusterCorrespondences method. | |
| double | hough_bin_size_ |
| The size of each bin of the hough space. | |
| boost::shared_ptr < pcl::recognition::HoughSpace3D > | hough_space_ |
| The Hough space. | |
| bool | hough_space_initialized_ |
| Whether the Hough space already contains the correct votes for the current input parameters and so the cluster and recognize calls don't need to recompute each value. Reset on the change of any parameter except the hough_threshold. | |
| double | hough_threshold_ |
| The minimum number of votes in the Hough space needed to infer the presence of a model instance into the scene cloud. | |
| ModelRfCloudConstPtr | input_rf_ |
| The input Rf cloud. | |
| float | local_rf_normals_search_radius_ |
| Normals search radius for the potential Rf calculation. | |
| float | local_rf_search_radius_ |
| Search radius for the potential Rf calculation. | |
| std::vector< Eigen::Vector3f > | model_votes_ |
| The result of the training. The vector between each model point and the centroid of the model adjusted by its local reference frame. | |
| bool | needs_training_ |
| If the training of the Hough space is needed; set on change of either the input cloud or the input_rf. | |
| SceneRfCloudConstPtr | scene_rf_ |
| The scene Rf cloud. | |
| bool | use_distance_weight_ |
| Use the weighted correspondence distance when casting votes. | |
| bool | use_interpolation_ |
| Use the interpolation between neighboring Hough bins when casting votes. | |
Detailed Description
template<typename PointModelT, typename PointSceneT, typename PointModelRfT = pcl::ReferenceFrame, typename PointSceneRfT = pcl::ReferenceFrame>
class pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >
Class implementing a 3D correspondence grouping algorithm that can deal with multiple instances of a model template found into a given scene. Each correspondence casts a vote for a reference point in a 3D Hough Space. The remaining 3 DOF are taken into account by associating each correspondence with a local Reference Frame. The suggested PointModelRfT is pcl::ReferenceFrame.
- Note:
- If you use this code in any academic work, please cite the original paper:
- F. Tombari, L. Di Stefano: Object recognition in 3D scenes with occlusions and clutter by Hough voting. 2010, Fourth Pacific-Rim Symposium on Image and Video Technology
Definition at line 144 of file hough_3d.h.
Member Typedef Documentation
| typedef pcl::PointCloud<PointModelRfT> pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::ModelRfCloud |
Definition at line 147 of file hough_3d.h.
| typedef ModelRfCloud::ConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::ModelRfCloudConstPtr |
Definition at line 149 of file hough_3d.h.
| typedef ModelRfCloud::Ptr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::ModelRfCloudPtr |
Definition at line 148 of file hough_3d.h.
| typedef pcl::PointCloud<PointModelT> pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::PointCloud |
Reimplemented from pcl::PCLBase< PointModelT >.
Definition at line 155 of file hough_3d.h.
| typedef PointCloud::ConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::PointCloudConstPtr |
Reimplemented from pcl::PCLBase< PointModelT >.
Definition at line 157 of file hough_3d.h.
| typedef PointCloud::Ptr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::PointCloudPtr |
Reimplemented from pcl::PCLBase< PointModelT >.
Definition at line 156 of file hough_3d.h.
| typedef pcl::CorrespondenceGrouping<PointModelT, PointSceneT>::SceneCloudConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::SceneCloudConstPtr |
Reimplemented from pcl::CorrespondenceGrouping< PointModelT, PointSceneT >.
Definition at line 159 of file hough_3d.h.
| typedef pcl::PointCloud<PointSceneRfT> pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::SceneRfCloud |
Definition at line 151 of file hough_3d.h.
| typedef SceneRfCloud::ConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::SceneRfCloudConstPtr |
Definition at line 153 of file hough_3d.h.
| typedef SceneRfCloud::Ptr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::SceneRfCloudPtr |
Definition at line 152 of file hough_3d.h.
Constructor & Destructor Documentation
| pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::Hough3DGrouping | ( | ) | [inline] |
Constructor.
Definition at line 162 of file hough_3d.h.
Member Function Documentation
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::clusterCorrespondences | ( | std::vector< Correspondences > & | model_instances | ) | [protected, virtual] |
Cluster the input correspondences in order to distinguish between different instances of the model into the scene.
- Parameters:
-
[out] model_instances a vector containing the clustered correspondences for each model found on the scene.
- Returns:
- true if the clustering had been successful or false if errors have occurred.
Implements pcl::CorrespondenceGrouping< PointModelT, PointSceneT >.
Definition at line 258 of file hough_3d.hpp.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::computeRf | ( | const boost::shared_ptr< const pcl::PointCloud< PointType > > & | input, |
| pcl::PointCloud< PointRfType > & | rf | ||
| ) | [protected] |
Computes the reference frame for an input cloud.
- Parameters:
-
[in] input the input cloud. [out] rf the resulting reference frame.
Definition at line 54 of file hough_3d.hpp.
| double pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getHoughBinSize | ( | ) | const [inline] |
Gets the size of each bin into the Hough space.
- Returns:
- the size of each Hough space's bin.
Definition at line 305 of file hough_3d.h.
| double pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getHoughThreshold | ( | ) | const [inline] |
Gets the minimum number of votes in the Hough space needed to infer the presence of a model instance into the scene cloud.
- Returns:
- the threshold for the Hough space voting.
Definition at line 284 of file hough_3d.h.
| ModelRfCloudConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getInputRf | ( | ) | const [inline] |
Getter for the input dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the input dataset.
- Returns:
- the pointer to the input cloud's reference frames.
Definition at line 211 of file hough_3d.h.
| float pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getLocalRfNormalsSearchRadius | ( | ) | const [inline] |
If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to compute the normals in order to subsequently compute the RF (if not set a default 15 nearest neighbors search is performed).
- Returns:
- the normals search radius for the local reference frame calculation.
Definition at line 375 of file hough_3d.h.
| float pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getLocalRfSearchRadius | ( | ) | const [inline] |
If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to do so.
- Attention:
- This parameter NEEDS to be set if the reference frames are not precomputed externally, otherwise the recognition results won't be correct.
- Returns:
- the search radius for the local reference frame calculation.
Definition at line 403 of file hough_3d.h.
| SceneRfCloudConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getSceneRf | ( | ) | const [inline] |
Getter for the scene dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the scene dataset.
- Returns:
- the pointer to the scene cloud's reference frames.
Definition at line 248 of file hough_3d.h.
| bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getUseDistanceWeight | ( | ) | const [inline] |
Gets whether the vote casting procedure uses the correspondence's distance as a score.
- Returns:
- if the algorithm should use the weighted distance when calculating the Hough voting score.
Definition at line 349 of file hough_3d.h.
| bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::getUseInterpolation | ( | ) | const [inline] |
Gets whether the vote casting procedure interpolates the score between neighboring bins of the Hough space or not.
- Returns:
- if the algorithm should interpolate the vote score between neighboring bins.
Definition at line 328 of file hough_3d.h.
| bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::houghVoting | ( | ) | [protected] |
Finds the transformation matrix between the input and the scene cloud for a set of correspondences using a RANSAC algorithm.
- Parameters:
-
[in] the scene cloud in which the PointSceneT has been converted to PointModelT. [in] corrs a set of correspondences. [out] transform the transformation matrix between the input cloud and the scene cloud that aligns the found correspondences.
- Returns:
- true if the recognition had been successful or false if errors have occurred.The Hough space voting procedure.
- true if the voting had been successful or false if errors have occurred.
Definition at line 137 of file hough_3d.hpp.
| bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::recognize | ( | std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > & | transformations | ) |
The main function, recognizes instances of the model into the scene set by the user.
- Parameters:
-
[out] transformations a vector containing one transformation matrix for each instance of the model recognized into the scene.
- Returns:
- true if the recognition had been successful or false if errors have occurred.
Definition at line 333 of file hough_3d.hpp.
| bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::recognize | ( | std::vector< Eigen::Matrix4f, Eigen::aligned_allocator< Eigen::Matrix4f > > & | transformations, |
| std::vector< pcl::Correspondences > & | clustered_corrs | ||
| ) |
The main function, recognizes instances of the model into the scene set by the user.
- Parameters:
-
[out] transformations a vector containing one transformation matrix for each instance of the model recognized into the scene. [out] clustered_corrs a vector containing the correspondences for each instance of the model found within the input data (the same output of clusterCorrespondences).
- Returns:
- true if the recognition had been successful or false if errors have occurred.
Definition at line 342 of file hough_3d.hpp.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setHoughBinSize | ( | double | bin_size | ) | [inline] |
Sets the size of each bin into the Hough space.
- Parameters:
-
[in] bin_size the size of each Hough space's bin.
Definition at line 294 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setHoughThreshold | ( | double | threshold | ) | [inline] |
Sets the minimum number of votes in the Hough space needed to infer the presence of a model instance into the scene cloud.
- Parameters:
-
[in] threshold the threshold for the Hough space voting, if set between -1 and 0 the maximum vote in the entire space is automatically calculated and -threshold the maximum value is used as a threshold. This means that a value between -1 and 0 should be used only if at least one instance of the model is always present in the scene, or if this false positive can be filtered later.
Definition at line 274 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setInputCloud | ( | const PointCloudConstPtr & | cloud | ) | [inline, virtual] |
Provide a pointer to the input dataset.
- Parameters:
-
[in] cloud the const boost shared pointer to a PointCloud message.
Reimplemented from pcl::PCLBase< PointModelT >.
Definition at line 182 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setInputRf | ( | const ModelRfCloudConstPtr & | input_rf | ) | [inline] |
Provide a pointer to the input dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the input dataset.
- Parameters:
-
[in] input_rf the pointer to the input cloud's reference frames.
Definition at line 197 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setLocalRfNormalsSearchRadius | ( | float | local_rf_normals_search_radius | ) | [inline] |
If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to compute the normals in order to subsequently compute the RF (if not set a default 15 nearest neighbors search is performed).
- Parameters:
-
[in] local_rf_normals_search_radius the normals search radius for the local reference frame calculation.
Definition at line 361 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setLocalRfSearchRadius | ( | float | local_rf_search_radius | ) | [inline] |
If the Local reference frame has not been set for either the model cloud or the scene cloud, this algorithm makes the computation itself but needs a suitable search radius to do so.
- Attention:
- This parameter NEEDS to be set if the reference frames are not precomputed externally, otherwise the recognition results won't be correct.
- Parameters:
-
[in] local_rf_search_radius the search radius for the local reference frame calculation.
Definition at line 388 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setModelSceneCorrespondences | ( | const CorrespondencesConstPtr & | corrs | ) | [inline, virtual] |
Provide a pointer to the precomputed correspondences between points in the input dataset and points in the scene dataset. The correspondences are going to be clustered into different model instances by the algorithm.
- Parameters:
-
[in] corrs the correspondences between the model and the scene.
Reimplemented from pcl::CorrespondenceGrouping< PointModelT, PointSceneT >.
Definition at line 260 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setSceneCloud | ( | const SceneCloudConstPtr & | scene | ) | [inline, virtual] |
Provide a pointer to the scene dataset (i.e. the cloud in which the algorithm has to search for instances of the input model)
- Parameters:
-
[in] scene the const boost shared pointer to a PointCloud message.
Reimplemented from pcl::CorrespondenceGrouping< PointModelT, PointSceneT >.
Definition at line 221 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setSceneRf | ( | const SceneRfCloudConstPtr & | scene_rf | ) | [inline] |
Provide a pointer to the scene dataset's reference frames. Each point in the reference frame cloud should be the reference frame of the correspondent point in the scene dataset.
- Parameters:
-
[in] scene_rf the pointer to the scene cloud's reference frames.
Definition at line 235 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setUseDistanceWeight | ( | bool | use_distance_weight | ) | [inline] |
Sets whether the vote casting procedure uses the correspondence's distance as a score.
- Parameters:
-
[in] use_distance_weight the algorithm should use the weighted distance when calculating the Hough voting score.
Definition at line 338 of file hough_3d.h.
| void pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::setUseInterpolation | ( | bool | use_interpolation | ) | [inline] |
Sets whether the vote casting procedure interpolates the score between neighboring bins of the Hough space or not.
- Parameters:
-
[in] use_interpolation the algorithm should interpolate the vote score between neighboring bins.
Definition at line 316 of file hough_3d.h.
| bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::train | ( | ) |
Call this function after setting the input, the input_rf and the hough_bin_size parameters to perform an off line training of the algorithm. This might be useful if one wants to perform once and for all a pre-computation of votes that only concern the models, increasing the on-line efficiency of the grouping algorithm. The algorithm is automatically trained on the first invocation of the recognize method or the cluster method if this training function has not been manually invoked.
- Returns:
- true if the training had been successful or false if errors have occurred.
Definition at line 84 of file hough_3d.hpp.
Member Data Documentation
std::vector<Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::found_transformations_ [protected] |
Transformations found by clusterCorrespondences method.
Definition at line 474 of file hough_3d.h.
double pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::hough_bin_size_ [protected] |
The size of each bin of the hough space.
Definition at line 456 of file hough_3d.h.
boost::shared_ptr<pcl::recognition::HoughSpace3D> pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::hough_space_ [protected] |
The Hough space.
Definition at line 471 of file hough_3d.h.
bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::hough_space_initialized_ [protected] |
Whether the Hough space already contains the correct votes for the current input parameters and so the cluster and recognize calls don't need to recompute each value. Reset on the change of any parameter except the hough_threshold.
Definition at line 479 of file hough_3d.h.
double pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::hough_threshold_ [protected] |
The minimum number of votes in the Hough space needed to infer the presence of a model instance into the scene cloud.
Definition at line 453 of file hough_3d.h.
ModelRfCloudConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::input_rf_ [protected] |
The input Rf cloud.
Definition at line 441 of file hough_3d.h.
float pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::local_rf_normals_search_radius_ [protected] |
Normals search radius for the potential Rf calculation.
Definition at line 465 of file hough_3d.h.
float pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::local_rf_search_radius_ [protected] |
Search radius for the potential Rf calculation.
Definition at line 468 of file hough_3d.h.
std::vector<Eigen::Vector3f> pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::model_votes_ [protected] |
The result of the training. The vector between each model point and the centroid of the model adjusted by its local reference frame.
Definition at line 450 of file hough_3d.h.
bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::needs_training_ [protected] |
If the training of the Hough space is needed; set on change of either the input cloud or the input_rf.
Definition at line 447 of file hough_3d.h.
SceneRfCloudConstPtr pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::scene_rf_ [protected] |
The scene Rf cloud.
Definition at line 444 of file hough_3d.h.
bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::use_distance_weight_ [protected] |
Use the weighted correspondence distance when casting votes.
Definition at line 462 of file hough_3d.h.
bool pcl::Hough3DGrouping< PointModelT, PointSceneT, PointModelRfT, PointSceneRfT >::use_interpolation_ [protected] |
Use the interpolation between neighboring Hough bins when casting votes.
Definition at line 459 of file hough_3d.h.
The documentation for this class was generated from the following files: