toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN > Class Template Reference

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...

#include <agast_keypoints.hpp>

Inheritance diagram for toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >:

Public Types
using	base_type = base_keypoint_extractor_t< agast_keypoint_extractor_t< DataType, KNN >, DataType, KNN >
using	data_type = typename base_type::data_type
using	knn_type = typename base_type::knn_type
using	point_cloud = typename base_type::point_cloud
using	point_cloud_ptr = typename base_type::point_cloud_ptr
using	indices_vector = typename base_type::indices_vector

Public Member Functions
	agast_keypoint_extractor_t ()=default
std::size_t	set_input_impl (const point_cloud &cloud)
std::size_t	set_input_impl (const point_cloud_ptr &cloud)
std::size_t	set_knn_impl (const knn_type &knn)
std::size_t	set_search_radius_impl (data_type radius)
void	enable_parallel_impl (bool enable)
indices_vector	extract_impl ()
void	extract_impl (indices_vector &keypoint_indices)
point_cloud	extract_keypoints_impl ()
void	extract_keypoints_impl (point_cloud_ptr output)
void	set_threshold (data_type threshold)
void	set_pattern_radius (data_type radius)
void	set_non_maxima_radius (data_type radius)
void	set_num_test_points (std::size_t num)
void	set_min_arc_length (std::size_t length)
data_type	get_threshold () const
data_type	get_pattern_radius () const
data_type	get_non_maxima_radius () const
std::size_t	get_num_test_points () const
std::size_t	get_min_arc_length () const

Detailed Description

template<typename DataType, typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>
class toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >

AGAST (Adaptive and Generic Accelerated Segment Test) 3D关键点提取器 / AGAST (Adaptive and Generic Accelerated Segment Test) 3D keypoint extractor.

Template Parameters

DataType	数据类型（float或double） / Data type (float or double)
KNN	最近邻搜索算法类型，默认使用 kdtree_generic_t / K-nearest neighbor search algorithm type, defaults to kdtree_generic_t

AGAST是FAST算法的改进版本，在3D点云中通过自适应决策树快速检测角点 / AGAST is an improved version of FAST, detecting corners quickly in 3D point clouds through adaptive decision trees

Member Typedef Documentation

base_type

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

using toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::base_type = base_keypoint_extractor_t<agast_keypoint_extractor_t<DataType, KNN>, DataType, KNN>

data_type

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

using toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::data_type = typename base_type::data_type

indices_vector

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

using toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::indices_vector = typename base_type::indices_vector

knn_type

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

using toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::knn_type = typename base_type::knn_type

point_cloud

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

using toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::point_cloud = typename base_type::point_cloud

point_cloud_ptr

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

using toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::point_cloud_ptr = typename base_type::point_cloud_ptr

Constructor & Destructor Documentation

agast_keypoint_extractor_t()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::agast_keypoint_extractor_t ( )

default

Member Function Documentation

enable_parallel_impl()

template<typename DataType , typename KNN >

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::enable_parallel_impl

(

bool

enable

)

extract_impl() [1/2]

template<typename DataType , typename KNN >

agast_keypoint_extractor_t< DataType, KNN >::indices_vector toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::extract_impl

(

)

extract_impl() [2/2]

template<typename DataType , typename KNN >

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::extract_impl

(

indices_vector &

keypoint_indices

)

extract_keypoints_impl() [1/2]

template<typename DataType , typename KNN >

agast_keypoint_extractor_t< DataType, KNN >::point_cloud toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::extract_keypoints_impl

(

)

extract_keypoints_impl() [2/2]

template<typename DataType , typename KNN >

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::extract_keypoints_impl

(

point_cloud_ptr

output

)

get_min_arc_length()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

std::size_t toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::get_min_arc_length ( ) const

inline

get_non_maxima_radius()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

data_type toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::get_non_maxima_radius ( ) const

inline

get_num_test_points()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

std::size_t toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::get_num_test_points ( ) const

inline

get_pattern_radius()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

data_type toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::get_pattern_radius ( ) const

inline

get_threshold()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

data_type toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::get_threshold ( ) const

inline

set_input_impl() [1/2]

template<typename DataType , typename KNN >

std::size_t toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_input_impl

(

const point_cloud &

cloud

)

set_input_impl() [2/2]

template<typename DataType , typename KNN >

std::size_t toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_input_impl

(

const point_cloud_ptr &

cloud

)

set_knn_impl()

template<typename DataType , typename KNN >

std::size_t toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_knn_impl

(

const knn_type &

knn

)

set_min_arc_length()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_min_arc_length ( std::size_t  length )

inline

set_non_maxima_radius()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_non_maxima_radius ( data_type  radius )

inline

set_num_test_points()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_num_test_points ( std::size_t  num )

inline

set_pattern_radius()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_pattern_radius ( data_type  radius )

inline

set_search_radius_impl()

template<typename DataType , typename KNN >

std::size_t toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_search_radius_impl

(

data_type

radius

)

set_threshold()

template<typename DataType , typename KNN = kdtree_generic_t<point_t<DataType>, toolbox::metrics::L2Metric<DataType>>>

void toolbox::pcl::agast_keypoint_extractor_t< DataType, KNN >::set_threshold ( data_type  threshold )

inline

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The documentation for this class was generated from the following files:

• src/include/cpp-toolbox/pcl/features/agast_keypoints.hpp
• src/include/cpp-toolbox/pcl/features/impl/agast_keypoints_impl.hpp