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 typedef | pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > |
feature_estimator_ | pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > | protected
FeaturePtr typedef | pcl::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 typedef | pcl::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_CENTERS | pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > | protected static
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_LABELS | pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > | protected static
~ImplicitShapeModelEstimation() | pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > | virtual