cpp-toolbox  0.0.1
A toolbox library for C++
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Classes | Typedefs | Enumerations | Functions
toolbox::pcl Namespace Reference

Classes

class  agast_keypoint_extractor_t
 AGAST (Adaptive and Generic Accelerated Segment Test) 3D关键点提取器 / AGAST (Adaptive and Generic Accelerated Segment Test) 3D keypoint extractor. More...
 
class  base_coarse_registration_t
 粗配准算法的基类（CRTP模式） / Base class for coarse registration algorithms (CRTP pattern) More...
 
class  base_correspondence_generator_t
 对应点生成器的基类（CRTP模式） / Base class for correspondence generators (CRTP pattern) More...
 
class  base_descriptor_extractor_t
 描述子提取器的基类（CRTP模式） / Base class for descriptor extractors (CRTP pattern) More...
 
class  base_fine_registration_t
 细配准算法的基类（CRTP模式） / Base class for fine registration algorithms (CRTP pattern) More...
 
class  base_keypoint_extractor_t
 关键点提取器的基类，使用CRTP模式实现静态多态 / Base class for keypoint extractors using CRTP pattern for static polymorphism More...
 
class  base_knn_generic_t
 KNN算法的基类（CRTP模式） / Base class for KNN algorithms (CRTP pattern) More...
 
class  base_norm_extractor_t
 法向量提取器的基类（CRTP模式） / Base class for normal extractors (CRTP pattern) More...
 
struct  base_signature_t
 描述子签名的基类 / Base class for descriptor signatures More...
 
class  bfknn_generic_t
 暴力K近邻搜索算法的通用实现 / Generic brute-force K-nearest neighbors search implementation More...
 
class  bfknn_parallel_generic_t
 
class  brute_force_correspondence_generator_t
 暴力搜索对应点生成器 / Brute-force correspondence generator More...
 
struct  correspondence_t
 对应关系结构体 / Correspondence structure More...
 
class  curvature_keypoint_extractor_t
 基于曲率的关键点提取器 / Curvature-based keypoint extractor More...
 
class  cvfh_extractor_t
 
struct  cvfh_signature_t
 
class  dsc3d_extractor_t
 
struct  dsc3d_signature_t
 3D形状上下文描述子签名 / 3D Shape Context descriptor signature More...
 
class  filter_t
 
struct  fine_registration_result_t
 细配准结果 / Fine registration result More...
 
class  four_pcs_registration_t
 4PCS（4-Point Congruent Sets）粗配准算法 / 4PCS coarse registration algorithm More...
 
class  fpfh_extractor_t
 FPFH (Fast Point Feature Histogram) descriptor extractor. More...
 
struct  fpfh_signature_t
 FPFH (Fast Point Feature Histogram) signature. More...
 
class  harris3d_keypoint_extractor_t
 Harris 3D 关键点提取器 / Harris 3D keypoint extractor. More...
 
class  iss_keypoint_extractor_t
 ISS (Intrinsic Shape Signatures) 关键点提取器 / ISS (Intrinsic Shape Signatures) keypoint extractor. More...
 
struct  iteration_state_t
 配准迭代状态 / Registration iteration state More...
 
class  kdtree_generic_t
 
class  knn_correspondence_generator_t
 基于KNN的对应点生成器 / KNN-based correspondence generator More...
 
struct  knn_traits
 KNN算法的特征定义 / KNN algorithm traits definition. More...
 
class  loam_feature_extractor_t
 LOAM (Lidar Odometry and Mapping) 特征提取器 / LOAM (Lidar Odometry and Mapping) feature extractor. More...
 
class  mls_keypoint_extractor_t
 MLS (Moving Least Squares) 关键点提取器 / MLS (Moving Least Squares) keypoint extractor. More...
 
class  pca_norm_extractor_t
 基于PCA的法向量提取器 / PCA-based normal extractor More...
 
class  pfh_extractor_t
 PFH (Point Feature Histogram) descriptor extractor. More...
 
struct  pfh_signature_t
 PFH (Point Feature Histogram) signature. More...
 
class  random_downsampling_t
 
class  ransac_registration_t
 RANSAC粗配准算法 / RANSAC coarse registration algorithm. More...
 
struct  registration_result_t
 配准结果结构体 / Registration result structure More...
 
class  rops_extractor_t
 
struct  rops_signature_t
 
class  shot_extractor_t
 SHOT (Signature of Histograms of Orientations) descriptor extractor. More...
 
struct  shot_signature_t
 SHOT (Signature of Histograms of Orientations) signature. More...
 
class  sift3d_keypoint_extractor_t
 SIFT 3D (Scale-Invariant Feature Transform) 关键点提取器 / SIFT 3D (Scale-Invariant Feature Transform) keypoint extractor. More...
 
class  super_four_pcs_registration_t
 Super4PCS 粗配准算法 / Super4PCS coarse registration algorithm. More...
 
class  susan_keypoint_extractor_t
 SUSAN (Smallest Univalue Segment Assimilating Nucleus) 3D关键点提取器 / SUSAN (Smallest Univalue Segment Assimilating Nucleus) 3D keypoint extractor. More...
 
class  uniform_grid_subsampling_t
 
class  vfh_extractor_t
 
struct  vfh_signature_t
 
class  voxel_grid_downsampling_t
 

Typedefs

template<typename DataType , typename Signature , typename KNN >
using correspondence_generator_t = knn_correspondence_generator_t< DataType, Signature, KNN >
 向后兼容的类型别名 / Backward compatibility type alias
 
template<typename DataType >
using curvature_keypoint_extractor_kdtree_t = curvature_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 特征提取器类型别名 / Feature extractor type aliases
 
template<typename DataType >
using curvature_keypoint_extractor_bfknn_t = curvature_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using curvature_keypoint_extractor_bfknn_parallel_t = curvature_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using iss_keypoint_extractor_kdtree_t = iss_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using iss_keypoint_extractor_bfknn_t = iss_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using iss_keypoint_extractor_bfknn_parallel_t = iss_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using harris3d_keypoint_extractor_kdtree_t = harris3d_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using harris3d_keypoint_extractor_bfknn_t = harris3d_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using harris3d_keypoint_extractor_bfknn_parallel_t = harris3d_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using sift3d_keypoint_extractor_kdtree_t = sift3d_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using sift3d_keypoint_extractor_bfknn_t = sift3d_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using sift3d_keypoint_extractor_bfknn_parallel_t = sift3d_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using loam_feature_extractor_kdtree_t = loam_feature_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using loam_feature_extractor_bfknn_t = loam_feature_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using loam_feature_extractor_bfknn_parallel_t = loam_feature_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using susan_keypoint_extractor_kdtree_t = susan_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using susan_keypoint_extractor_bfknn_t = susan_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using susan_keypoint_extractor_bfknn_parallel_t = susan_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using agast_keypoint_extractor_kdtree_t = agast_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using agast_keypoint_extractor_bfknn_t = agast_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using agast_keypoint_extractor_bfknn_parallel_t = agast_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using mls_keypoint_extractor_kdtree_t = mls_keypoint_extractor_t< DataType, kdtree_t< DataType > >
 
template<typename DataType >
using mls_keypoint_extractor_bfknn_t = mls_keypoint_extractor_t< DataType, bfknn_t< DataType > >
 
template<typename DataType >
using mls_keypoint_extractor_bfknn_parallel_t = mls_keypoint_extractor_t< DataType, bfknn_parallel_t< DataType > >
 
template<typename DataType >
using bfknn_t = bfknn_generic_t< point_t< DataType >, toolbox::metrics::L2Metric< DataType > >
 用于点云的暴力KNN类型别名 / Type alias for brute-force KNN with point clouds
 
template<typename DataType >
using bfknn_parallel_t = bfknn_parallel_generic_t< point_t< DataType >, toolbox::metrics::L2Metric< DataType > >
 
template<typename DataType >
using kdtree_t = kdtree_generic_t< point_t< DataType >, toolbox::metrics::L2Metric< DataType > >
 
using ransac_registration = ransac_registration_t< float >
 
using four_pcs_registration = four_pcs_registration_t< float >
 
using super_four_pcs_registration = super_four_pcs_registration_t< float >
 
using registration_result = registration_result_t< float >
 
using ransac_registration_d = ransac_registration_t< double >
 
using four_pcs_registration_d = four_pcs_registration_t< double >
 
using super_four_pcs_registration_d = super_four_pcs_registration_t< double >
 
using registration_result_d = registration_result_t< double >
 

Enumerations

enum class  correspondence_type_e {
  POINT_TO_POINT , POINT_TO_PLANE , PLANE_TO_PLANE , POINT_TO_DISTRIBUTION ,
  CUSTOM
}
 对应关系类型枚举 / Correspondence type enumeration More...
 

Functions

template<typename DataType , typename Signature , typename KNN >
std::vector< correspondence_t > generate_correspondences_knn (const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &src_cloud, const std::shared_ptr< std::vector< Signature > > &src_descriptors, const std::shared_ptr< std::vector< std::size_t > > &src_keypoints, const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &dst_cloud, const std::shared_ptr< std::vector< Signature > > &dst_descriptors, const std::shared_ptr< std::vector< std::size_t > > &dst_keypoints, float ratio=0.8f, bool mutual=true)
 对应关系生成策略 / Correspondence generation strategies
 
template<typename DataType , typename Signature >
std::vector< correspondence_t > generate_correspondences_brute_force (const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &src_cloud, const std::shared_ptr< std::vector< Signature > > &src_descriptors, const std::shared_ptr< std::vector< std::size_t > > &src_keypoints, const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &dst_cloud, const std::shared_ptr< std::vector< Signature > > &dst_descriptors, const std::shared_ptr< std::vector< std::size_t > > &dst_keypoints, float ratio=0.8f, bool mutual=true, bool parallel=false)
 快速生成对应关系的便捷函数（使用暴力搜索） / Convenience function for quick correspondence generation (using brute force)
 
size_t filter_correspondences_by_distance (std::vector< correspondence_t > &correspondences, float max_distance)
 过滤对应关系的辅助函数 / Helper function to filter correspondences
 
std::tuple< float, float, float, float > compute_correspondence_statistics (const std::vector< correspondence_t > &correspondences)
 计算对应关系的统计信息 / Compute statistics of correspondences
 
void print_correspondences (const std::vector< correspondence_t > &correspondences, size_t max_display=10)
 可视化对应关系的辅助信息 / Helper to visualize correspondence information
 
template<typename Signature >
std::vector< std::pair< size_t, size_t > > match_descriptors (const std::vector< Signature > &source_descriptors, const std::vector< Signature > &target_descriptors, typename Signature::data_type max_distance)
 描述子类型及其特点 / Descriptor types and their characteristics
 
template<typename Signature >
std::vector< std::pair< size_t, size_t > > match_descriptors_ratio_test (const std::vector< Signature > &source_descriptors, const std::vector< Signature > &target_descriptors, float ratio_threshold=0.8f)
 使用比率测试的描述子匹配 / Descriptor matching with ratio test
 
template<typename Signature >
Signature compute_descriptor_centroid (const std::vector< Signature > &descriptors)
 计算描述子集的统计信息 / Compute statistics of descriptor set
 
template<typename Signature >
std::pair< float, float > evaluate_descriptor_matching (const std::vector< Signature > &descriptors1, const std::vector< Signature > &descriptors2, const std::vector< std::pair< size_t, size_t > > &ground_truth_matches, typename Signature::data_type max_distance)
 描述子性能评估辅助函数 / Descriptor performance evaluation helper
 
template<typename T >
auto create_default_knn (size_t num_points=0)
 KNN算法的选择指南 / Guide for choosing KNN algorithms.
 
template<typename KNN >
double benchmark_knn (KNN &knn, const std::vector< typename KNN::element_type > &queries, size_t k)
 性能基准测试辅助函数 / Performance benchmark helper function
 
template<typename T >
auto create_normal_extractor ()
 法向量提取算法的选择指南 / Guide for choosing normal extraction algorithms
 
template<typename T >
void orient_normals_towards_viewpoint (toolbox::types::point_cloud_t< T > &normals, const point_t< T > &viewpoint, const toolbox::types::point_cloud_t< T > &cloud)
 法向量方向一致性处理 / Normal orientation consistency processing
 
template<typename T >
double validate_normals (const toolbox::types::point_cloud_t< T > &normals)
 验证法向量的有效性 / Validate normal validity
 
template<typename DataType >
registration_result_t< DataType > quick_registration (const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &source, const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &target, const std::string &algorithm="super4pcs", DataType overlap=0.5f)
 配准算法选择指南 / Registration algorithm selection guide
 

Typedef Documentation

◆ agast_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::agast_keypoint_extractor_bfknn_parallel_t = typedef agast_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ agast_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::agast_keypoint_extractor_bfknn_t = typedef agast_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ agast_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::agast_keypoint_extractor_kdtree_t = typedef agast_keypoint_extractor_t<DataType, kdtree_t<DataType> >

◆ bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::bfknn_parallel_t = typedef bfknn_parallel_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType> >

◆ bfknn_t

template<typename DataType >
using toolbox::pcl::bfknn_t = typedef bfknn_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType> >

用于点云的暴力KNN类型别名 / Type alias for brute-force KNN with point clouds

Template Parameters
DataType数据类型（如float或double） / Data type (e.g., float or double)
// 使用类型别名简化代码 / Using type alias to simplify code
bfknn_t<float> knn;
point_cloud_t<float> cloud = load_point_cloud("data.pcd");
knn.set_input(cloud);
point_t<float> query = {1.0f, 2.0f, 3.0f};
std::vector<std::size_t> indices;
std::vector<float> distances;
knn.kneighbors(query, 10, indices, distances);
toolbox::pcl::base_knn_generic_t::kneighbors
bool kneighbors(const element_type &query, std::size_t num_neighbors, std::vector< std::size_t > &indices, std::vector< distance_type > &distances)
K近邻搜索 / K-nearest neighbors search.
Definition base_knn.hpp:179
toolbox::pcl::base_knn_generic_t::set_input
std::size_t set_input(const container_type &data)
设置输入数据 / Set input data
Definition base_knn.hpp:83
toolbox::pcl::bfknn_generic_t
暴力K近邻搜索算法的通用实现 / Generic brute-force K-nearest neighbors search implementation
Definition bfknn.hpp:45
toolbox::types::point_t
3D点/向量模板类 / A 3D point/vector template class
Definition point.hpp:48

◆ correspondence_generator_t

template<typename DataType , typename Signature , typename KNN >
using toolbox::pcl::correspondence_generator_t = typedef knn_correspondence_generator_t<DataType, Signature, KNN>

向后兼容的类型别名 / Backward compatibility type alias

Deprecated:
请使用 knn_correspondence_generator_t / Please use knn_correspondence_generator_t

◆ curvature_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::curvature_keypoint_extractor_bfknn_parallel_t = typedef curvature_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ curvature_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::curvature_keypoint_extractor_bfknn_t = typedef curvature_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ curvature_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::curvature_keypoint_extractor_kdtree_t = typedef curvature_keypoint_extractor_t<DataType, kdtree_t<DataType> >

特征提取器类型别名 / Feature extractor type aliases

为每种特征提取器和KNN算法的组合提供便利的类型别名，简化使用 / Provides convenient type aliases for each combination of feature extractor and KNN algorithm

// 使用示例 - 选择合适的特征提取器 / Usage example - choosing appropriate feature extractor
using namespace toolbox::pcl;
// 1. 曲率关键点提取器（快速，适合一般用途） / Curvature keypoint extractor (fast, general purpose)
curvature_keypoint_extractor_kdtree_t<float> curvature_extractor;
// 2. ISS关键点提取器（稳定，适合配准） / ISS keypoint extractor (stable, good for registration)
iss_keypoint_extractor_kdtree_t<float> iss_extractor;
// 3. Harris3D关键点提取器（经典，检测角点） / Harris3D keypoint extractor (classic, corner detection)
harris3d_keypoint_extractor_kdtree_t<float> harris_extractor;
// 4. SIFT3D关键点提取器（尺度不变，描述能力强） / SIFT3D keypoint extractor (scale-invariant, strong descriptive power)
sift3d_keypoint_extractor_kdtree_t<float> sift_extractor;
// 5. LOAM特征提取器（激光雷达SLAM专用） / LOAM feature extractor (specialized for LiDAR SLAM)
loam_feature_extractor_kdtree_t<float> loam_extractor;
// 6. SUSAN关键点提取器（噪声鲁棒） / SUSAN keypoint extractor (noise robust)
susan_keypoint_extractor_kdtree_t<float> susan_extractor;
// 7. AGAST关键点提取器（快速角点检测） / AGAST keypoint extractor (fast corner detection)
agast_keypoint_extractor_kdtree_t<float> agast_extractor;
// 8. MLS关键点提取器（基于曲面拟合） / MLS keypoint extractor (based on surface fitting)
mls_keypoint_extractor_kdtree_t<float> mls_extractor;
toolbox::pcl::agast_keypoint_extractor_t
AGAST (Adaptive and Generic Accelerated Segment Test) 3D关键点提取器 / AGAST (Adaptive and Generic Accelera...
Definition agast_keypoints.hpp:26
toolbox::pcl::curvature_keypoint_extractor_t
基于曲率的关键点提取器 / Curvature-based keypoint extractor
Definition curvature_keypoints.hpp:61
toolbox::pcl::harris3d_keypoint_extractor_t
Harris 3D 关键点提取器 / Harris 3D keypoint extractor.
Definition harris3d_keypoints.hpp:63
toolbox::pcl::iss_keypoint_extractor_t
ISS (Intrinsic Shape Signatures) 关键点提取器 / ISS (Intrinsic Shape Signatures) keypoint extractor.
Definition iss_keypoints.hpp:61
toolbox::pcl::loam_feature_extractor_t
LOAM (Lidar Odometry and Mapping) 特征提取器 / LOAM (Lidar Odometry and Mapping) feature extractor.
Definition loam_feature_extractor.hpp:26
toolbox::pcl::mls_keypoint_extractor_t
MLS (Moving Least Squares) 关键点提取器 / MLS (Moving Least Squares) keypoint extractor.
Definition mls_keypoints.hpp:28
toolbox::pcl::sift3d_keypoint_extractor_t
SIFT 3D (Scale-Invariant Feature Transform) 关键点提取器 / SIFT 3D (Scale-Invariant Feature Transform) keyp...
Definition sift3d_keypoints.hpp:26
toolbox::pcl::susan_keypoint_extractor_t
SUSAN (Smallest Univalue Segment Assimilating Nucleus) 3D关键点提取器 / SUSAN (Smallest Univalue Segment As...
Definition susan_keypoints.hpp:27
toolbox::pcl
Definition base_correspondence_generator.hpp:18
// 选择不同的KNN算法 / Choosing different KNN algorithms
// KDTree - 适合低维数据，查询效率高 / KDTree - suitable for low-dimensional data, efficient queries
curvature_keypoint_extractor_kdtree_t<float> kdtree_extractor;
// BruteForce - 适合小数据集，实现简单 / BruteForce - suitable for small datasets, simple implementation
curvature_keypoint_extractor_bfknn_t<float> bf_extractor;
// Parallel BruteForce - 适合多核CPU，大数据集 / Parallel BruteForce - suitable for multi-core CPU, large datasets
curvature_keypoint_extractor_bfknn_parallel_t<float> parallel_extractor;

◆ harris3d_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::harris3d_keypoint_extractor_bfknn_parallel_t = typedef harris3d_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ harris3d_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::harris3d_keypoint_extractor_bfknn_t = typedef harris3d_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ harris3d_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::harris3d_keypoint_extractor_kdtree_t = typedef harris3d_keypoint_extractor_t<DataType, kdtree_t<DataType> >

◆ iss_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::iss_keypoint_extractor_bfknn_parallel_t = typedef iss_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ iss_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::iss_keypoint_extractor_bfknn_t = typedef iss_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ iss_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::iss_keypoint_extractor_kdtree_t = typedef iss_keypoint_extractor_t<DataType, kdtree_t<DataType> >

◆ kdtree_t

template<typename DataType >
using toolbox::pcl::kdtree_t = typedef kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType> >

◆ loam_feature_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::loam_feature_extractor_bfknn_parallel_t = typedef loam_feature_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ loam_feature_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::loam_feature_extractor_bfknn_t = typedef loam_feature_extractor_t<DataType, bfknn_t<DataType> >

◆ loam_feature_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::loam_feature_extractor_kdtree_t = typedef loam_feature_extractor_t<DataType, kdtree_t<DataType> >

◆ mls_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::mls_keypoint_extractor_bfknn_parallel_t = typedef mls_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ mls_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::mls_keypoint_extractor_bfknn_t = typedef mls_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ mls_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::mls_keypoint_extractor_kdtree_t = typedef mls_keypoint_extractor_t<DataType, kdtree_t<DataType> >

◆ sift3d_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::sift3d_keypoint_extractor_bfknn_parallel_t = typedef sift3d_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ sift3d_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::sift3d_keypoint_extractor_bfknn_t = typedef sift3d_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ sift3d_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::sift3d_keypoint_extractor_kdtree_t = typedef sift3d_keypoint_extractor_t<DataType, kdtree_t<DataType> >

◆ susan_keypoint_extractor_bfknn_parallel_t

template<typename DataType >
using toolbox::pcl::susan_keypoint_extractor_bfknn_parallel_t = typedef susan_keypoint_extractor_t<DataType, bfknn_parallel_t<DataType> >

◆ susan_keypoint_extractor_bfknn_t

template<typename DataType >
using toolbox::pcl::susan_keypoint_extractor_bfknn_t = typedef susan_keypoint_extractor_t<DataType, bfknn_t<DataType> >

◆ susan_keypoint_extractor_kdtree_t

template<typename DataType >
using toolbox::pcl::susan_keypoint_extractor_kdtree_t = typedef susan_keypoint_extractor_t<DataType, kdtree_t<DataType> >

Enumeration Type Documentation

◆ correspondence_type_e

enum class toolbox::pcl::correspondence_type_e
strong

对应关系类型枚举 / Correspondence type enumeration

Enumerator
POINT_TO_POINT 

点到点 / Point to point

POINT_TO_PLANE 

点到面 / Point to plane

PLANE_TO_PLANE 

面到面 / Plane to plane

POINT_TO_DISTRIBUTION 

点到分布（如NDT） / Point to distribution (e.g., NDT)

CUSTOM 

自定义 / Custom