HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals. More...
#include <pcl/keypoints/harris_3d.h>
Public Types | |
enum |
ResponseMethod { HARRIS = 1, NOBLE, LOWE, TOMASI, CURVATURE } |
using | Ptr = shared_ptr< HarrisKeypoint3D< PointInT, PointOutT, NormalT > > |
using | ConstPtr = shared_ptr< const HarrisKeypoint3D< PointInT, PointOutT, NormalT > > |
using | PointCloudIn = typename Keypoint< PointInT, PointOutT >::PointCloudIn |
using | PointCloudOut = typename Keypoint< PointInT, PointOutT >::PointCloudOut |
using | KdTree = typename Keypoint< PointInT, PointOutT >::KdTree |
using | PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
using | PointCloudN = pcl::PointCloud< NormalT > |
using | PointCloudNPtr = typename PointCloudN::Ptr |
using | PointCloudNConstPtr = typename PointCloudN::ConstPtr |
Public Types inherited from pcl::Keypoint< PointInT, PointOutT > | |
using | Ptr = shared_ptr< Keypoint< PointInT, PointOutT > > |
using | ConstPtr = shared_ptr< const Keypoint< PointInT, PointOutT > > |
using | BaseClass = PCLBase< PointInT > |
using | KdTree = pcl::search::Search< PointInT > |
using | KdTreePtr = typename KdTree::Ptr |
using | PointCloudIn = pcl::PointCloud< PointInT > |
using | PointCloudInPtr = typename PointCloudIn::Ptr |
using | PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
using | PointCloudOut = pcl::PointCloud< PointOutT > |
using | SearchMethod = std::function< int(pcl::index_t, double, pcl::Indices &, std::vector< float > &)> |
using | SearchMethodSurface = std::function< int(const PointCloudIn &cloud, pcl::index_t index, double, pcl::Indices &, std::vector< float > &)> |
Public Member Functions | |
HarrisKeypoint3D (ResponseMethod method=HARRIS, float radius=0.01f, float threshold=0.0f) | |
Constructor. More... |
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~HarrisKeypoint3D () | |
Empty destructor. More... |
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void | setInputCloud (const PointCloudInConstPtr &cloud) override |
Provide a pointer to the input dataset. More... |
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void | setMethod (ResponseMethod type) |
Set the method of the response to be calculated. More... |
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void | setRadius (float radius) |
Set the radius for normal estimation and non maxima supression. More... |
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void | setThreshold (float threshold) |
Set the threshold value for detecting corners. More... |
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void | setNonMaxSupression (bool=false) |
Whether non maxima suppression should be applied or the response for each point should be returned. More... |
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void | setRefine (bool do_refine) |
Whether the detected key points should be refined or not. More... |
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void | setNormals (const PointCloudNConstPtr &normals) |
Set normals if precalculated normals are available. More... |
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void | setSearchSurface (const PointCloudInConstPtr &cloud) override |
Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. More... |
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void | setNumberOfThreads (unsigned int nr_threads=0) |
Initialize the scheduler and set the number of threads to use. More... |
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Public Member Functions inherited from pcl::Keypoint< PointInT, PointOutT > | |
Keypoint () | |
Keypoint () | |
Empty constructor. More... |
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void | harrisCorner (PointInT &output, PointInT &input, const float sigma_d, const float sigma_i, const float alpha, const float thresh) |
void | hessianBlob (PointInT &output, PointInT &input, const float sigma, bool SCALE) |
void | hessianBlob (PointInT &output, PointInT &input, const float start_scale, const float scaling_factor, const int num_scales) |
void | imageElementMultiply (PointInT &output, PointInT &input1, PointInT &input2) |
~Keypoint () | |
Empty destructor. More... |
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PointCloudInConstPtr | getSearchSurface () |
Get a pointer to the surface point cloud dataset. More... |
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void | setSearchMethod (const KdTreePtr &tree) |
Provide a pointer to the search object. More... |
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KdTreePtr | getSearchMethod () |
Get a pointer to the search method used. More... |
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double | getSearchParameter () |
Get the internal search parameter. More... |
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void | setKSearch (int k) |
Set the number of k nearest neighbors to use for the feature estimation. More... |
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int | getKSearch () |
get the number of k nearest neighbors used for the feature estimation. More... |
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void | setRadiusSearch (double radius) |
Set the sphere radius that is to be used for determining the nearest neighbors used for the key point detection. More... |
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double | getRadiusSearch () |
Get the sphere radius used for determining the neighbors. More... |
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pcl::PointIndicesConstPtr | getKeypointsIndices () |
void | compute (PointCloudOut &output) |
Base method for key point detection for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More... |
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int | searchForNeighbors (pcl::index_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const |
Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More... |
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Protected Member Functions | |
bool | initCompute () override |
void | detectKeypoints (PointCloudOut &output) override |
void | responseHarris (PointCloudOut &output) const |
gets the corner response for valid input points More... |
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void | responseNoble (PointCloudOut &output) const |
void | responseLowe (PointCloudOut &output) const |
void | responseTomasi (PointCloudOut &output) const |
void | responseCurvature (PointCloudOut &output) const |
void | refineCorners (PointCloudOut &corners) const |
void | calculateNormalCovar (const pcl::Indices &neighbors, float *coefficients) const |
calculates the upper triangular part of unnormalized covariance matrix over the normals given by the indices. More... |
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Protected Member Functions inherited from pcl::Keypoint< PointInT, PointOutT > | |
const std::string & | getClassName () const |
Get a string representation of the name of this class. More... |
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virtual void | detectKeypoints (PointCloudOut &output)=0 |
Abstract key point detection method. More... |
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Additional Inherited Members | |
Protected Attributes inherited from pcl::Keypoint< PointInT, PointOutT > | |
std::string | name_ |
The key point detection method's name. More... |
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SearchMethod | search_method_ |
The search method template for indices. More... |
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SearchMethodSurface | search_method_surface_ |
The search method template for points. More... |
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PointCloudInConstPtr | surface_ |
An input point cloud describing the surface that is to be used for nearest neighbors estimation. More... |
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KdTreePtr | tree_ |
A pointer to the spatial search object. More... |
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double | search_parameter_ |
The actual search parameter (casted from either search_radius_ or k_). More... |
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double | search_radius_ |
The nearest neighbors search radius for each point. More... |
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int | k_ |
The number of K nearest neighbors to use for each point. More... |
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pcl::PointIndicesPtr | keypoints_indices_ |
Indices of the keypoints in the input cloud. More... |
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HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals.
Definition at line 51 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::ConstPtr = shared_ptr<const HarrisKeypoint3D<PointInT, PointOutT, NormalT> > |
Definition at line 55 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::KdTree = typename Keypoint<PointInT, PointOutT>::KdTree |
Definition at line 59 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::PointCloudIn = typename Keypoint<PointInT, PointOutT>::PointCloudIn |
Definition at line 57 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
Definition at line 60 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::PointCloudN = pcl::PointCloud<NormalT> |
Definition at line 62 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::PointCloudNConstPtr = typename PointCloudN::ConstPtr |
Definition at line 64 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::PointCloudNPtr = typename PointCloudN::Ptr |
Definition at line 63 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::PointCloudOut = typename Keypoint<PointInT, PointOutT>::PointCloudOut |
Definition at line 58 of file harris_3d.h.
using pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::Ptr = shared_ptr<HarrisKeypoint3D<PointInT, PointOutT, NormalT> > |
Definition at line 54 of file harris_3d.h.
enum pcl::HarrisKeypoint3D::ResponseMethod |
Enumerator | |
---|---|
HARRIS | |
NOBLE | |
LOWE | |
TOMASI | |
CURVATURE |
Definition at line 78 of file harris_3d.h.
| inline |
Constructor.
[in] | method | the method to be used to determine the corner responses |
[in] | radius | the radius for normal estimation as well as for non maxima suppression |
[in] | threshold | the threshold to filter out weak corners |
Definition at line 85 of file harris_3d.h.
References pcl::Keypoint< PointInT, PointOutT >::name_, and pcl::Keypoint< PointInT, PointOutT >::search_radius_.
| inline |
Empty destructor.
Definition at line 97 of file harris_3d.h.
| protected |
calculates the upper triangular part of unnormalized covariance matrix over the normals given by the indices.
Definition at line 103 of file harris_3d.hpp.
| overrideprotected |
Definition at line 238 of file harris_3d.hpp.
References pcl::PointCloud< PointT >::is_dense, pcl::isFinite(), pcl::PointCloud< PointT >::points, and pcl::PointCloud< PointT >::size().
| overrideprotectedvirtual |
Reimplemented from pcl::Keypoint< PointInT, PointOutT >.
Definition at line 192 of file harris_3d.hpp.
References pcl::Feature< PointInT, PointOutT >::compute(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::setInputCloud(), pcl::NormalEstimation< PointInT, PointOutT >::setInputCloud(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::setNormalEstimationMethod(), pcl::IntegralImageNormalEstimation< PointInT, PointOutT >::setNormalSmoothingSize(), and pcl::Feature< PointInT, PointOutT >::setRadiusSearch().
| protected |
Definition at line 502 of file harris_3d.hpp.
References pcl::invert3x3SymMatrix().
| protected |
Definition at line 439 of file harris_3d.hpp.
| protected |
gets the corner response for valid input points
Definition at line 318 of file harris_3d.hpp.
References pcl::isFinite().
| protected |
Definition at line 399 of file harris_3d.hpp.
References pcl::isFinite().
| protected |
Definition at line 359 of file harris_3d.hpp.
References pcl::isFinite().
| protected |
Definition at line 457 of file harris_3d.hpp.
References pcl::eigen33(), and pcl::isFinite().
| override |
Provide a pointer to the input dataset.
[in] | cloud | the const boost shared pointer to a PointCloud message |
Definition at line 52 of file harris_3d.hpp.
void pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::setMethod | ( | ResponseMethod | type | ) |
Set the method of the response to be calculated.
[in] | type |
Definition at line 61 of file harris_3d.hpp.
void pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::setNonMaxSupression | ( | bool |
nonmax = false
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) |
Whether non maxima suppression should be applied or the response for each point should be returned.
[in] | nonmax | default is false |
Definition at line 89 of file harris_3d.hpp.
void pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::setNormals | ( | const PointCloudNConstPtr & | normals | ) |
Set normals if precalculated normals are available.
normals |
Definition at line 96 of file harris_3d.hpp.
| inline |
Initialize the scheduler and set the number of threads to use.
nr_threads | the number of hardware threads to use (0 sets the value back to automatic) |
Definition at line 158 of file harris_3d.h.
void pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::setRadius | ( | float | radius | ) |
Set the radius for normal estimation and non maxima supression.
[in] | radius |
Definition at line 75 of file harris_3d.hpp.
void pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::setRefine | ( | bool | do_refine | ) |
Whether the detected key points should be refined or not.
If turned of, the key points are a subset of the original point cloud. Otherwise the key points may be arbitrary.
note non maxima supression needs to be on in order to use this feature.
[in] | do_refine |
Definition at line 82 of file harris_3d.hpp.
| inlineoverridevirtual |
Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset.
This is optional, if this is not set, it will only use the data in the input cloud to estimate the features. This is useful when you only need to compute the features for a downsampled cloud.
[in] | cloud | a pointer to a PointCloud message |
Reimplemented from pcl::Keypoint< PointInT, PointOutT >.
Definition at line 152 of file harris_3d.h.
References pcl::Keypoint< PointInT, PointOutT >::surface_.
void pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::setThreshold | ( | float | threshold | ) |
Set the threshold value for detecting corners.
This is only evaluated if non maxima suppression is turned on.
note non maxima suppression needs to be activated in order to use this feature.
[in] | threshold |
Definition at line 68 of file harris_3d.hpp.
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_harris_keypoint3_d.html