40 #ifndef PCL_SEGMENTATION_SAC_SEGMENTATION_H_
41 #define PCL_SEGMENTATION_SAC_SEGMENTATION_H_
43 #include <pcl/pcl_base.h>
44 #include <pcl/PointIndices.h>
45 #include <pcl/ModelCoefficients.h>
48 #include <pcl/sample_consensus/method_types.h>
49 #include <pcl/sample_consensus/sac.h>
51 #include <pcl/sample_consensus/model_types.h>
52 #include <pcl/sample_consensus/sac_model.h>
54 #include <pcl/search/search.h>
64 template <
typename Po
intT>
92 ,
radius_min_ (-std::numeric_limits<double>::max ())
97 ,
axis_ (Eigen::Vector3f::Zero ())
226 inline Eigen::Vector3f
257 initSAC (
const int method_type);
310 template <
typename Po
intT,
typename Po
intNT>
429 #ifdef PCL_NO_PRECOMPILE
430 #include <pcl/segmentation/impl/sac_segmentation.hpp>
433 #endif //#ifndef PCL_SEGMENTATION_SAC_SEGMENTATION_H_
double getDistanceThreshold() const
Get the distance to the model threshold.
void setOptimizeCoefficients(bool optimize)
Set to true if a coefficient refinement is required.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
double min_angle_
The minimum and maximum allowed opening angle of valid cone model.
double getEpsAngle() const
Get the epsilon (delta) model angle threshold in radians.
int max_iterations_
Maximum number of iterations before giving up (user given parameter).
virtual std::string getClassName() const
Class get name method.
virtual std::string getClassName() const
Class get name method.
bool random_
Set to true if we need a random seed.
SampleConsensusModelPtr getModel() const
Get a pointer to the SAC model used.
void setSamplesMaxDist(const double &radius, SearchPtr search)
Set the maximum distance allowed when drawing random samples.
boost::shared_ptr< PointCloud< PointT > > Ptr
void setEpsAngle(double ea)
Set the angle epsilon (delta) threshold.
SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models...
void setInputNormals(const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset...
PointCloud::ConstPtr PointCloudConstPtr
double probability_
Desired probability of choosing at least one sample free from outliers (user given parameter)...
void setMethodType(int method)
The type of sample consensus method to use (user given parameter).
int getMaxIterations() const
Get maximum number of iterations before giving up.
SampleConsensus< PointT >::Ptr SampleConsensusPtr
int getMethodType() const
Get the type of sample consensus method used.
SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
void setProbability(double probability)
Set the probability of choosing at least one sample free from outliers.
pcl::PointCloud< PointT > PointCloud
double samples_radius_
The maximum distance of subsequent samples from the first (radius search)
virtual bool initSACModel(const int model_type)
Initialize the Sample Consensus model and set its parameters.
double threshold_
Distance to the model threshold (user given parameter).
PointCloudN::ConstPtr PointCloudNConstPtr
double radius_min_
The minimum and maximum radius limits for the model.
double distance_from_origin_
The distance from the template plane to the origin.
void getSamplesMaxDist(double &radius)
Get maximum distance allowed when drawing random samples.
pcl::search::Search< PointT >::Ptr SearchPtr
void getMinMaxOpeningAngle(double &min_angle, double &max_angle)
Get the opening angle which we need minumum to validate a cone model.
PointCloud::Ptr PointCloudPtr
int model_type_
The type of model to use (user given parameter).
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
PointCloudNConstPtr getInputNormals() const
Get a pointer to the normals of the input XYZ point cloud dataset.
int getModelType() const
Get the type of SAC model used.
pcl::PointCloud< PointNT > PointCloudN
SampleConsensusModelPtr model_
The model that needs to be segmented.
double eps_angle_
The maximum allowed difference between the model normal and the given axis.
SACSegmentationFromNormals(bool random=false)
Empty constructor.
double distance_weight_
The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point norma...
SearchPtr samples_radius_search_
The search object for picking subsequent samples using radius search.
bool getOptimizeCoefficients() const
Get the coefficient refinement internal flag.
PointCloud::ConstPtr PointCloudConstPtr
Eigen::Vector3f axis_
The axis along which we need to search for a model perpendicular to.
void setAxis(const Eigen::Vector3f &ax)
Set the axis along which we need to search for a model perpendicular to.
SampleConsensus< PointT >::Ptr SampleConsensusPtr
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...
double getProbability() const
Get the probability of choosing at least one sample free from outliers.
SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods...
bool optimize_coefficients_
Set to true if a coefficient refinement is required.
PointCloudN::Ptr PointCloudNPtr
void setModelType(int model)
The type of model to use (user given parameter).
double getDistanceFromOrigin() const
Get the distance of a plane model from the origin.
SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
SampleConsensusPtr sac_
The sample consensus segmentation method.
virtual void segment(PointIndices &inliers, ModelCoefficients &model_coefficients)
Base method for segmentation of a model in a PointCloud given by <setInputCloud (), setIndices ()>
boost::shared_ptr< SampleConsensusModel > Ptr
SampleConsensusModelFromNormals< PointT, PointNT >::Ptr SampleConsensusModelFromNormalsPtr
virtual ~SACSegmentation()
Empty destructor.
void setMaxIterations(int max_iterations)
Set the maximum number of iterations before giving up.
boost::shared_ptr< SampleConsensusModelFromNormals > Ptr
void setDistanceFromOrigin(const double d)
Set the distance we expect a plane model to be from the origin.
double getNormalDistanceWeight() const
Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point n...
void getRadiusLimits(double &min_radius, double &max_radius)
Get the minimum and maximum allowable radius limits for the model as set by the user.
Eigen::Vector3f getAxis() const
Get the axis along which we need to search for a model perpendicular to.
SACSegmentation(bool random=false)
Empty constructor.
void setMinMaxOpeningAngle(const double &min_angle, const double &max_angle)
Set the minimum opning angle for a cone model.
A point structure representing Euclidean xyz coordinates, and the RGB color.
void setDistanceThreshold(double threshold)
Distance to the model threshold (user given parameter).
virtual void initSAC(const int method_type)
Initialize the Sample Consensus method and set its parameters.
SampleConsensusPtr getMethod() const
Get a pointer to the SAC method used.
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
SACSegmentation< PointT >::PointCloud PointCloud
PointCloud::Ptr PointCloudPtr
SampleConsensus represents the base class.
void setNormalDistanceWeight(double distance_weight)
Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point n...
virtual bool initSACModel(const int model_type)
Initialize the Sample Consensus model and set its parameters.
int method_type_
The type of sample consensus method to use (user given parameter).