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point_cloud_library / latest / classpcl_1_1ism_1_1_implicit_shape_model_estimation-members.html

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 > 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_LABELS pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > protectedstatic
~ImplicitShapeModelEstimation() pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT > virtual

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Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1ism_1_1_implicit_shape_model_estimation-members.html