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Point Cloud Library (PCL)
1.6.0
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SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for generic-purpose SAC-based segmentation. More...
#include <pcl/segmentation/sac_segmentation.h>


Public Types | |
| typedef pcl::PointCloud< PointT > | PointCloud |
| typedef PointCloud::Ptr | PointCloudPtr |
| typedef PointCloud::ConstPtr | PointCloudConstPtr |
| typedef pcl::search::Search < PointT >::Ptr | SearchPtr |
| typedef SampleConsensus < PointT >::Ptr | SampleConsensusPtr |
| typedef SampleConsensusModel < PointT >::Ptr | SampleConsensusModelPtr |
| typedef PointIndices::Ptr | PointIndicesPtr |
| typedef PointIndices::ConstPtr | PointIndicesConstPtr |
Public Member Functions | |
| SACSegmentation () | |
| Empty constructor. More... | |
| virtual | ~SACSegmentation () |
| Empty destructor. More... | |
| void | setModelType (int model) |
| The type of model to use (user given parameter). More... | |
| int | getModelType () const |
| Get the type of SAC model used. More... | |
| SampleConsensusPtr | getMethod () const |
| Get a pointer to the SAC method used. More... | |
| SampleConsensusModelPtr | getModel () const |
| Get a pointer to the SAC model used. More... | |
| void | setMethodType (int method) |
| The type of sample consensus method to use (user given parameter). More... | |
| int | getMethodType () const |
| Get the type of sample consensus method used. More... | |
| void | setDistanceThreshold (double threshold) |
| Distance to the model threshold (user given parameter). More... | |
| double | getDistanceThreshold () const |
| Get the distance to the model threshold. More... | |
| void | setMaxIterations (int max_iterations) |
| Set the maximum number of iterations before giving up. More... | |
| int | getMaxIterations () const |
| Get maximum number of iterations before giving up. More... | |
| void | setProbability (double probability) |
| Set the probability of choosing at least one sample free from outliers. More... | |
| double | getProbability () const |
| Get the probability of choosing at least one sample free from outliers. More... | |
| void | setOptimizeCoefficients (bool optimize) |
| Set to true if a coefficient refinement is required. More... | |
| bool | getOptimizeCoefficients () const |
| Get the coefficient refinement internal flag. More... | |
| void | setRadiusLimits (const double &min_radius, const double &max_radius) |
| Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius) More... | |
| void | getRadiusLimits (double &min_radius, double &max_radius) |
| Get the minimum and maximum allowable radius limits for the model as set by the user. More... | |
| void | setSamplesMaxDist (const double &radius, SearchPtr search) |
| Set the maximum distance allowed when drawing random samples. More... | |
| void | getSamplesMaxDist (double &radius) |
| Get maximum distance allowed when drawing random samples. More... | |
| void | setAxis (const Eigen::Vector3f &ax) |
| Set the axis along which we need to search for a model perpendicular to. More... | |
| Eigen::Vector3f | getAxis () const |
| Get the axis along which we need to search for a model perpendicular to. More... | |
| void | setEpsAngle (double ea) |
| Set the angle epsilon (delta) threshold. More... | |
| double | getEpsAngle () const |
| Get the epsilon (delta) model angle threshold in radians. More... | |
| virtual void | segment (PointIndices &inliers, ModelCoefficients &model_coefficients) |
| Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()> More... | |
| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. More... | |
| PointCloudConstPtr const | getInputCloud () |
| Get a pointer to the input point cloud dataset. More... | |
| void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... | |
| void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... | |
| void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... | |
| void | setIndices (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols) |
| Set the indices for the points laying within an interest region of the point cloud. More... | |
| IndicesPtr const | getIndices () |
| Get a pointer to the vector of indices used. More... | |
| const PointT & | operator[] (size_t pos) |
| Override PointCloud operator[] to shorten code. More... | |
SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for generic-purpose SAC-based segmentation.
Definition at line 65 of file sac_segmentation.h.
| typedef pcl::PointCloud<PointT> pcl::SACSegmentation< PointT >::PointCloud |
Definition at line 74 of file sac_segmentation.h.
| typedef PointCloud::ConstPtr pcl::SACSegmentation< PointT >::PointCloudConstPtr |
Definition at line 76 of file sac_segmentation.h.
| typedef PointCloud::Ptr pcl::SACSegmentation< PointT >::PointCloudPtr |
Definition at line 75 of file sac_segmentation.h.
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inherited |
Definition at line 79 of file pcl_base.h.
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inherited |
Definition at line 78 of file pcl_base.h.
| typedef SampleConsensusModel<PointT>::Ptr pcl::SACSegmentation< PointT >::SampleConsensusModelPtr |
Definition at line 80 of file sac_segmentation.h.
| typedef SampleConsensus<PointT>::Ptr pcl::SACSegmentation< PointT >::SampleConsensusPtr |
Definition at line 79 of file sac_segmentation.h.
| typedef pcl::search::Search<PointT>::Ptr pcl::SACSegmentation< PointT >::SearchPtr |
Definition at line 77 of file sac_segmentation.h.
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inline |
Empty constructor.
Definition at line 83 of file sac_segmentation.h.
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inlinevirtual |
Empty destructor.
Definition at line 92 of file sac_segmentation.h.
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inline |
Get the axis along which we need to search for a model perpendicular to.
Definition at line 213 of file sac_segmentation.h.
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inline |
Get the distance to the model threshold.
Definition at line 130 of file sac_segmentation.h.
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inline |
Get the epsilon (delta) model angle threshold in radians.
Definition at line 223 of file sac_segmentation.h.
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inlineinherited |
Get a pointer to the vector of indices used.
Definition at line 190 of file pcl_base.h.
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inlineinherited |
Get a pointer to the input point cloud dataset.
Definition at line 107 of file pcl_base.h.
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inline |
Get maximum number of iterations before giving up.
Definition at line 140 of file sac_segmentation.h.
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inline |
Get a pointer to the SAC method used.
Definition at line 106 of file sac_segmentation.h.
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inline |
Get the type of sample consensus method used.
Definition at line 120 of file sac_segmentation.h.
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inline |
Get a pointer to the SAC model used.
Definition at line 110 of file sac_segmentation.h.
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inline |
Get the type of SAC model used.
Definition at line 102 of file sac_segmentation.h.
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inline |
Get the coefficient refinement internal flag.
Definition at line 160 of file sac_segmentation.h.
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inline |
Get the probability of choosing at least one sample free from outliers.
Definition at line 150 of file sac_segmentation.h.
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inline |
Get the minimum and maximum allowable radius limits for the model as set by the user.
| [out] | min_radius | the resultant minimum radius model |
| [out] | max_radius | the resultant maximum radius model |
Definition at line 179 of file sac_segmentation.h.
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inline |
Get maximum distance allowed when drawing random samples.
| [out] | radius | the maximum distance (L2 norm) |
Definition at line 200 of file sac_segmentation.h.
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inlineinherited |
Override PointCloud operator[] to shorten code.
| pos | position in indices_ vector |
Definition at line 197 of file pcl_base.h.
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virtual |
Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()>
| [in] | inliers | the resultant point indices that support the model found (inliers) |
| [out] | model_coefficients | the resultant model coefficients |
Definition at line 71 of file sac_segmentation.hpp.
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inline |
Set the axis along which we need to search for a model perpendicular to.
| [in] | ax | the axis along which we need to search for a model perpendicular to |
Definition at line 209 of file sac_segmentation.h.
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inline |
Distance to the model threshold (user given parameter).
| [in] | threshold | the distance threshold to use |
Definition at line 126 of file sac_segmentation.h.
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inline |
Set the angle epsilon (delta) threshold.
| [in] | ea | the maximum allowed difference between the model normal and the given axis in radians. |
Definition at line 219 of file sac_segmentation.h.
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inlineinherited |
Provide a pointer to the vector of indices that represents the input data.
| indices | a pointer to the vector of indices that represents the input data. |
Definition at line 113 of file pcl_base.h.
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inlineinherited |
Provide a pointer to the vector of indices that represents the input data.
| indices | a pointer to the vector of indices that represents the input data. |
Definition at line 124 of file pcl_base.h.
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inlineinherited |
Provide a pointer to the vector of indices that represents the input data.
| indices | a pointer to the vector of indices that represents the input data. |
Definition at line 135 of file pcl_base.h.
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inlineinherited |
Set the indices for the points laying within an interest region of the point cloud.
| row_start | the offset on rows |
| col_start | the offset on columns |
| nb_rows | the number of rows to be considered row_start included |
| nb_cols | the number of columns to be considered col_start included |
Definition at line 151 of file pcl_base.h.
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inlinevirtualinherited |
Provide a pointer to the input dataset.
| cloud | the const boost shared pointer to a PointCloud message |
Reimplemented in pcl::PCA< PointT >.
Definition at line 103 of file pcl_base.h.
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inline |
Set the maximum number of iterations before giving up.
| [in] | max_iterations | the maximum number of iterations the sample consensus method will run |
Definition at line 136 of file sac_segmentation.h.
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inline |
The type of sample consensus method to use (user given parameter).
| [in] | method | the method type (check method_types.h) |
Definition at line 116 of file sac_segmentation.h.
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inline |
The type of model to use (user given parameter).
| [in] | model | the model type (check model_types.h) |
Definition at line 98 of file sac_segmentation.h.
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inline |
Set to true if a coefficient refinement is required.
| [in] | optimize | true for enabling model coefficient refinement, false otherwise |
Definition at line 156 of file sac_segmentation.h.
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inline |
Set the probability of choosing at least one sample free from outliers.
| [in] | probability | the model fitting probability |
Definition at line 146 of file sac_segmentation.h.
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inline |
Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius)
| [in] | min_radius | the minimum radius model |
| [in] | max_radius | the maximum radius model |
Definition at line 168 of file sac_segmentation.h.
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inline |
Set the maximum distance allowed when drawing random samples.
| [in] | radius | the maximum distance (L2 norm) |
Definition at line 189 of file sac_segmentation.h.
1.8.3.1