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Point Cloud Library (PCL)
1.6.0
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SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
#include <pcl/sample_consensus/sac_model_normal_plane.h>


Public Types | |
| typedef SampleConsensusModel < PointT >::PointCloud | PointCloud |
| typedef SampleConsensusModel < PointT >::PointCloudPtr | PointCloudPtr |
| typedef SampleConsensusModel < PointT >::PointCloudConstPtr | PointCloudConstPtr |
| typedef SampleConsensusModelFromNormals < PointT, PointNT > ::PointCloudNPtr | PointCloudNPtr |
| typedef SampleConsensusModelFromNormals < PointT, PointNT > ::PointCloudNConstPtr | PointCloudNConstPtr |
| typedef boost::shared_ptr < SampleConsensusModelNormalPlane > | Ptr |
| typedef pcl::search::Search < PointT >::Ptr | SearchPtr |
| typedef boost::shared_ptr < const SampleConsensusModel > | ConstPtr |
| typedef boost::shared_ptr < const SampleConsensusModelFromNormals > | ConstPtr |
Public Member Functions | |
| SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud) | |
| Constructor for base SampleConsensusModelNormalPlane. More... | |
| SampleConsensusModelNormalPlane (const PointCloudConstPtr &cloud, const std::vector< int > &indices) | |
| Constructor for base SampleConsensusModelNormalPlane. More... | |
| void | selectWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold, std::vector< int > &inliers) |
| Select all the points which respect the given model coefficients as inliers. More... | |
| virtual int | countWithinDistance (const Eigen::VectorXf &model_coefficients, const double threshold) |
| Count all the points which respect the given model coefficients as inliers. More... | |
| void | getDistancesToModel (const Eigen::VectorXf &model_coefficients, std::vector< double > &distances) |
| Compute all distances from the cloud data to a given plane model. More... | |
| pcl::SacModel | getModelType () const |
| Return an unique id for this model (SACMODEL_NORMAL_PLANE). More... | |
| bool | computeModelCoefficients (const std::vector< int > &samples, Eigen::VectorXf &model_coefficients) |
| Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them internally in model_coefficients_. More... | |
| void | optimizeModelCoefficients (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) |
| Recompute the plane coefficients using the given inlier set and return them to the user. More... | |
| void | projectPoints (const std::vector< int > &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) |
| Create a new point cloud with inliers projected onto the plane model. More... | |
| bool | doSamplesVerifyModel (const std::set< int > &indices, const Eigen::VectorXf &model_coefficients, const double threshold) |
| Verify whether a subset of indices verifies the given plane model coefficients. More... | |
| void | getSamples (int &iterations, std::vector< int > &samples) |
| Get a set of random data samples and return them as point indices. More... | |
| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. More... | |
| PointCloudConstPtr | getInputCloud () const |
| Get a pointer to the input point cloud dataset. More... | |
| void | setIndices (const boost::shared_ptr< std::vector< int > > &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... | |
| void | setIndices (const std::vector< int > &indices) |
| Provide the vector of indices that represents the input data. More... | |
| boost::shared_ptr< std::vector < int > > | getIndices () const |
| Get a pointer to the vector of indices used. More... | |
| unsigned int | getSampleSize () const |
| Return the size of a sample from which a model is computed. 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 | setNormalDistanceWeight (const double w) |
| Set the normal angular distance weight. More... | |
| double | getNormalDistanceWeight () |
| Get the normal angular distance weight. More... | |
| void | setInputNormals (const PointCloudNConstPtr &normals) |
| Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More... | |
| PointCloudNConstPtr | getInputNormals () |
| Get a pointer to the normals of the input XYZ point cloud dataset. More... | |
SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints.
Basically this means that checking for inliers will not only involve a "distance to model" criterion, but also an additional "maximum angular deviation" between the plane's normal and the inlier points normals.
The model coefficients are defined as:
To set the influence of the surface normals in the inlier estimation process, set the normal weight (0.0-1.0), e.g.:
Definition at line 75 of file sac_model_normal_plane.h.
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inherited |
Definition at line 74 of file sac_model.h.
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inherited |
Definition at line 510 of file sac_model.h.
| typedef SampleConsensusModel<PointT>::PointCloud pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloud |
Definition at line 84 of file sac_model_normal_plane.h.
| typedef SampleConsensusModel<PointT>::PointCloudConstPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudConstPtr |
Definition at line 86 of file sac_model_normal_plane.h.
| typedef SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNConstPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudNConstPtr |
Definition at line 89 of file sac_model_normal_plane.h.
| typedef SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudNPtr |
Definition at line 88 of file sac_model_normal_plane.h.
| typedef SampleConsensusModel<PointT>::PointCloudPtr pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::PointCloudPtr |
Definition at line 85 of file sac_model_normal_plane.h.
| typedef boost::shared_ptr<SampleConsensusModelNormalPlane> pcl::SampleConsensusModelNormalPlane< PointT, PointNT >::Ptr |
Definition at line 91 of file sac_model_normal_plane.h.
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inherited |
Definition at line 71 of file sac_model.h.
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inline |
Constructor for base SampleConsensusModelNormalPlane.
| [in] | cloud | the input point cloud dataset |
Definition at line 96 of file sac_model_normal_plane.h.
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inline |
Constructor for base SampleConsensusModelNormalPlane.
| [in] | cloud | the input point cloud dataset |
| [in] | indices | a vector of point indices to be used from cloud |
Definition at line 104 of file sac_model_normal_plane.h.
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virtualinherited |
Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them internally in model_coefficients_.
The plane coefficients are: a, b, c, d (ax+by+cz+d=0)
| [in] | samples | the point indices found as possible good candidates for creating a valid model |
| [out] | model_coefficients | the resultant model coefficients |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 65 of file sac_model_plane.hpp.
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virtual |
Count all the points which respect the given model coefficients as inliers.
| [in] | model_coefficients | the coefficients of a model that we need to compute distances to |
| [in] | threshold | maximum admissible distance threshold for determining the inliers from the outliers |
Reimplemented from pcl::SampleConsensusModelPlane< PointT >.
Definition at line 93 of file sac_model_normal_plane.hpp.
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virtualinherited |
Verify whether a subset of indices verifies the given plane model coefficients.
| [in] | indices | the data indices that need to be tested against the plane model |
| [in] | model_coefficients | the plane model coefficients |
| [in] | threshold | a maximum admissible distance threshold for determining the inliers from the outliers |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 329 of file sac_model_plane.hpp.
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virtual |
Compute all distances from the cloud data to a given plane model.
| [in] | model_coefficients | the coefficients of a plane model that we need to compute distances to |
| [out] | distances | the resultant estimated distances |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 133 of file sac_model_normal_plane.hpp.
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inlineinherited |
Get a pointer to the vector of indices used.
Definition at line 327 of file sac_model.h.
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inlineinherited |
Get a pointer to the input point cloud dataset.
Definition at line 303 of file sac_model.h.
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inlineinherited |
Get a pointer to the normals of the input XYZ point cloud dataset.
Definition at line 546 of file sac_model.h.
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inlinevirtual |
Return an unique id for this model (SACMODEL_NORMAL_PLANE).
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 138 of file sac_model_normal_plane.h.
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inlineinherited |
Get the normal angular distance weight.
Definition at line 531 of file sac_model.h.
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inlineinherited |
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 363 of file sac_model.h.
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inlineinherited |
Get a set of random data samples and return them as point indices.
Pure virtual.
| [out] | iterations | the internal number of iterations used by SAC methods |
| [out] | samples | the resultant model samples |
Definition at line 163 of file sac_model.h.
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inlineinherited |
Return the size of a sample from which a model is computed.
Definition at line 335 of file sac_model.h.
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inlineinherited |
Get maximum distance allowed when drawing random samples.
| [out] | radius | the maximum distance (L2 norm) |
Definition at line 384 of file sac_model.h.
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virtualinherited |
Recompute the plane coefficients using the given inlier set and return them to the user.
| [in] | inliers | the data inliers found as supporting the model |
| [in] | model_coefficients | the initial guess for the model coefficients |
| [out] | optimized_coefficients | the resultant recomputed coefficients after non-linear optimization |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 202 of file sac_model_plane.hpp.
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virtualinherited |
Create a new point cloud with inliers projected onto the plane model.
| [in] | inliers | the data inliers that we want to project on the plane model |
| [in] | model_coefficients | the normalized coefficients of a plane model |
| [out] | projected_points | the resultant projected points |
| [in] | copy_data_fields | set to true if we need to copy the other data fields |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 245 of file sac_model_plane.hpp.
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virtual |
Select all the points which respect the given model coefficients as inliers.
| [in] | model_coefficients | the coefficients of a plane model that we need to compute distances to |
| [in] | threshold | a maximum admissible distance threshold for determining the inliers from the outliers |
| [out] | inliers | the resultant model inliers |
Implements pcl::SampleConsensusModel< PointT >.
Definition at line 45 of file sac_model_normal_plane.hpp.
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inlineinherited |
Provide a pointer to the vector of indices that represents the input data.
| [in] | indices | a pointer to the vector of indices that represents the input data. |
Definition at line 309 of file sac_model.h.
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inlineinherited |
Provide the vector of indices that represents the input data.
| [out] | indices | the vector of indices that represents the input data. |
Definition at line 319 of file sac_model.h.
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inlinevirtualinherited |
Provide a pointer to the input dataset.
| [in] | cloud | the const boost shared pointer to a PointCloud message |
Reimplemented in pcl::SampleConsensusModelRegistration< PointT >.
Definition at line 286 of file sac_model.h.
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inlineinherited |
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
| [in] | normals | the const boost shared pointer to a PointCloud message |
Definition at line 539 of file sac_model.h.
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inlineinherited |
Set the normal angular distance weight.
| [in] | w | the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. (The Euclidean distance will have weight 1-w.) |
Definition at line 524 of file sac_model.h.
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inlineinherited |
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 350 of file sac_model.h.
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inlineinherited |
Set the maximum distance allowed when drawing random samples.
| [in] | radius | the maximum distance (L2 norm) |
Definition at line 373 of file sac_model.h.
1.8.3.1