Point Cloud Library (PCL)  1.9.1-dev
pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > Member List

This is the complete list of members for pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >, including all inherited members.

alignYCoordWithNormal(const NormalT &in_normal)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
applyTransform(Eigen::Vector3f &io_vec, const Eigen::Matrix3f &in_transform)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
calculateSigmas(std::vector< float > &sigmas)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
calculateWeights(const std::vector< LocationInfo, Eigen::aligned_allocator< LocationInfo > > &locations, const Eigen::MatrixXi &labels, std::vector< float > &sigmas, std::vector< std::vector< unsigned int > > &clusters, std::vector< std::vector< float > > &statistical_weights, std::vector< float > &learned_weights)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
clusterDescriptors(std::vector< pcl::Histogram< FeatureSize > > &histograms, Eigen::MatrixXi &labels, Eigen::MatrixXf &clusters_centers)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
computeDistance(Eigen::VectorXf &vec_1, Eigen::VectorXf &vec_2)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
computeKMeansClustering(const Eigen::MatrixXf &points_to_cluster, int number_of_clusters, Eigen::MatrixXi &io_labels, TermCriteria criteria, int attempts, int flags, Eigen::MatrixXf &cluster_centers)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
estimateFeatures(typename pcl::PointCloud< PointT >::Ptr sampled_point_cloud, typename pcl::PointCloud< NormalT >::Ptr normal_cloud, typename pcl::PointCloud< pcl::Histogram< FeatureSize > >::Ptr feature_cloud)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
extractDescriptors(std::vector< pcl::Histogram< FeatureSize > > &histograms, std::vector< LocationInfo, Eigen::aligned_allocator< LocationInfo > > &locations)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
Feature typedefpcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
feature_estimator_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
FeaturePtr typedefpcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
findObjects(ISMModelPtr model, typename pcl::PointCloud< PointT >::Ptr in_cloud, typename pcl::PointCloud< Normal >::Ptr in_normals, int in_class_of_interest)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
generateCentersPP(const Eigen::MatrixXf &data, Eigen::MatrixXf &out_centers, int number_of_clusters, int trials)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
generateRandomCenter(const std::vector< Eigen::Vector2f, Eigen::aligned_allocator< Eigen::Vector2f > > &boxes, Eigen::VectorXf &center)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
getFeatureEstimator()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getNumberOfClusters()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getNVotState()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getSamplingSize()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getSigmaDists()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getTrainingClasses()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getTrainingClouds()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
getTrainingNormals()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
ImplicitShapeModelEstimation()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
ISMModelPtr typedefpcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
n_vot_ON_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
number_of_clusters_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
operator=(const ImplicitShapeModelEstimation &)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
PP_CENTERSpcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protectedstatic
sampling_size_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
setFeatureEstimator(FeaturePtr feature)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setNumberOfClusters(unsigned int num_of_clusters)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setNVotState(bool state)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setSamplingSize(float sampling_size)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setSigmaDists(const std::vector< float > &training_sigmas)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setTrainingClasses(const std::vector< unsigned int > &training_classes)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setTrainingClouds(const std::vector< typename pcl::PointCloud< PointT >::Ptr > &training_clouds)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
setTrainingNormals(const std::vector< typename pcl::PointCloud< NormalT >::Ptr > &training_normals)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
shiftCloud(typename pcl::PointCloud< PointT >::Ptr in_cloud, Eigen::Vector3f shift_point)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
simplifyCloud(typename pcl::PointCloud< PointT >::ConstPtr in_point_cloud, typename pcl::PointCloud< NormalT >::ConstPtr in_normal_cloud, typename pcl::PointCloud< PointT >::Ptr out_sampled_point_cloud, typename pcl::PointCloud< NormalT >::Ptr out_sampled_normal_cloud)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
training_classes_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
training_clouds_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
training_normals_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
training_sigmas_pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protected
trainISM(ISMModelPtr &trained_model)pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >
USE_INITIAL_LABELSpcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >protectedstatic
~ImplicitShapeModelEstimation()pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >virtual