ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined clustering condition. More...
#include <pcl/segmentation/conditional_euclidean_clustering.h>
Public Member Functions |
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| ConditionalEuclideanClustering (bool extract_removed_clusters=false) | |
| Constructor. More... |
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| void | setSearchMethod (const SearcherPtr &tree) |
| Provide a pointer to the search object. More... |
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| const SearcherPtr & | getSearchMethod () const |
| Get a pointer to the search method used. More... |
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| void | setConditionFunction (bool(*condition_function)(const PointT &, const PointT &, float)) |
| Set the condition that needs to hold for neighboring points to be considered part of the same cluster. More... |
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| void | setConditionFunction (std::function< bool(const PointT &, const PointT &, float)> condition_function) |
| Set the condition that needs to hold for neighboring points to be considered part of the same cluster. More... |
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| void | setClusterTolerance (float cluster_tolerance) |
| Set the spatial tolerance for new cluster candidates. More... |
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| float | getClusterTolerance () |
| Get the spatial tolerance for new cluster candidates. More... |
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| void | setMinClusterSize (int min_cluster_size) |
| Set the minimum number of points that a cluster needs to contain in order to be considered valid. More... |
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| int | getMinClusterSize () |
| Get the minimum number of points that a cluster needs to contain in order to be considered valid. More... |
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| void | setMaxClusterSize (int max_cluster_size) |
| Set the maximum number of points that a cluster needs to contain in order to be considered valid. More... |
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| int | getMaxClusterSize () |
| Get the maximum number of points that a cluster needs to contain in order to be considered valid. More... |
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| void | segment (IndicesClusters &clusters) |
| Segment the input into separate clusters. More... |
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| void | getRemovedClusters (IndicesClustersPtr &small_clusters, IndicesClustersPtr &large_clusters) |
| Get the clusters that are invalidated due to size constraints. More... |
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 Public Member Functions inherited from pcl::PCLBase< PointT > |
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| PCLBase () | |
| Empty constructor. More... |
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| PCLBase (const PCLBase &base) | |
| Copy constructor. More... |
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| virtual | ~PCLBase ()=default |
| Destructor. More... |
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| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. More... |
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| const PointCloudConstPtr | getInputCloud () const |
| Get a pointer to the input point cloud dataset. More... |
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| virtual void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
| Set the indices for the points laying within an interest region of the point cloud. More... |
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| IndicesPtr | getIndices () |
| Get a pointer to the vector of indices used. More... |
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| const IndicesConstPtr | getIndices () const |
| Get a pointer to the vector of indices used. More... |
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| const PointT & | operator[] (std::size_t pos) const |
| Override PointCloud operator[] to shorten code. More... |
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Protected Types |
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| using | SearcherPtr = typename pcl::search::Search< PointT >::Ptr |
Additional Inherited Members |
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| Public Types inherited from pcl::PCLBase< PointT > |
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| using | PointCloud = pcl::PointCloud< PointT > |
| using | PointCloudPtr = typename PointCloud::Ptr |
| using | PointCloudConstPtr = typename PointCloud::ConstPtr |
| using | PointIndicesPtr = PointIndices::Ptr |
| using | PointIndicesConstPtr = PointIndices::ConstPtr |
| Protected Member Functions inherited from pcl::PCLBase< PointT > |
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| bool | initCompute () |
| This method should get called before starting the actual computation. More... |
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| bool | deinitCompute () |
| This method should get called after finishing the actual computation. More... |
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| Protected Attributes inherited from pcl::PCLBase< PointT > |
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| PointCloudConstPtr | input_ |
| The input point cloud dataset. More... |
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| IndicesPtr | indices_ |
| A pointer to the vector of point indices to use. More... |
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| bool | use_indices_ |
| Set to true if point indices are used. More... |
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| bool | fake_indices_ |
| If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More... |
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Detailed Description
template<typename PointT>
class pcl::ConditionalEuclideanClustering< PointT >
ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined clustering condition.
The condition that need to hold is currently passed using a function pointer. For more information check the documentation of setConditionFunction() or the usage example below:
Definition at line 85 of file conditional_euclidean_clustering.h.
Member Typedef Documentation
SearcherPtr
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protected |
Definition at line 88 of file conditional_euclidean_clustering.h.
Constructor & Destructor Documentation
ConditionalEuclideanClustering()
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inline |
Constructor.
- Parameters
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[in] extract_removed_clusters Set to true if you want to be able to extract the clusters that are too large or too small (default = false)
Definition at line 99 of file conditional_euclidean_clustering.h.
Member Function Documentation
getClusterTolerance()
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inline |
Get the spatial tolerance for new cluster candidates.
Definition at line 172 of file conditional_euclidean_clustering.h.
getMaxClusterSize()
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inline |
Get the maximum number of points that a cluster needs to contain in order to be considered valid.
Definition at line 204 of file conditional_euclidean_clustering.h.
getMinClusterSize()
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inline |
Get the minimum number of points that a cluster needs to contain in order to be considered valid.
Definition at line 188 of file conditional_euclidean_clustering.h.
getRemovedClusters()
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inline |
Get the clusters that are invalidated due to size constraints.
- Note
- The constructor of this class needs to be initialized with true, and the segment method needs to have been called prior to using this method.
- Parameters
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[out] small_clusters The resultant clusters that contain less than min_cluster_size points [out] large_clusters The resultant clusters that contain more than max_cluster_size points
Definition at line 227 of file conditional_euclidean_clustering.h.
getSearchMethod()
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inline |
Get a pointer to the search method used.
Definition at line 123 of file conditional_euclidean_clustering.h.
segment()
| void pcl::ConditionalEuclideanClustering< PointT >::segment | ( | pcl::IndicesClusters & | clusters | ) |
Segment the input into separate clusters.
The input can be set using setInputCloud() and setIndices().
The size constraints for the resulting clusters can be set using setMinClusterSize() and setMaxClusterSize().
The region growing parameters can be set using setConditionFunction() and setClusterTolerance().
- Parameters
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[out] clusters The resultant set of indices, indexing the points of the input cloud that correspond to the clusters
Definition at line 45 of file conditional_euclidean_clustering.hpp.
References pcl::PointIndices::header, and pcl::PointIndices::indices.
setClusterTolerance()
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inline |
Set the spatial tolerance for new cluster candidates.
Any two points within this distance from one another will need to evaluate a certain condition in order to be made part of the same cluster. The condition can be set using setConditionFunction().
- Parameters
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[in] cluster_tolerance The distance to scan for cluster candidates (default = 0.0)
Definition at line 165 of file conditional_euclidean_clustering.h.
setConditionFunction() [1/2]
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inline |
Set the condition that needs to hold for neighboring points to be considered part of the same cluster.
Any two points within a certain distance from one another will need to evaluate this condition in order to be made part of the same cluster. The distance can be set using setClusterTolerance().
Note that for a point to be part of a cluster, the condition only needs to hold for at least 1 point pair. To clarify, the following statement is false: Any two points within a cluster always evaluate this condition function to true.
The input arguments of the condition function are:
- PointT The first point of the point pair
- PointT The second point of the point pair
- float The squared distance between the points
The output argument is a boolean, returning true will merge the second point into the cluster of the first point.
- Parameters
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[in] condition_function The condition function that needs to hold for clustering
Definition at line 146 of file conditional_euclidean_clustering.h.
setConditionFunction() [2/2]
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inline |
Set the condition that needs to hold for neighboring points to be considered part of the same cluster.
This is an overloaded function provided for convenience. See the documentation for setConditionFunction().
Definition at line 154 of file conditional_euclidean_clustering.h.
setMaxClusterSize()
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inline |
Set the maximum number of points that a cluster needs to contain in order to be considered valid.
- Parameters
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[in] max_cluster_size The maximum cluster size (default = unlimited)
Definition at line 197 of file conditional_euclidean_clustering.h.
setMinClusterSize()
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inline |
Set the minimum number of points that a cluster needs to contain in order to be considered valid.
- Parameters
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[in] min_cluster_size The minimum cluster size (default = 1)
Definition at line 181 of file conditional_euclidean_clustering.h.
setSearchMethod()
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inline |
Provide a pointer to the search object.
- Parameters
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[in] tree a pointer to the spatial search object.
Definition at line 115 of file conditional_euclidean_clustering.h.
The documentation for this class was generated from the following files:
- pcl/segmentation/conditional_euclidean_clustering.h
- pcl/segmentation/impl/conditional_euclidean_clustering.hpp
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_conditional_euclidean_clustering.html
