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using | Ptr = shared_ptr< ISSKeypoint3D< PointInT, PointOutT, NormalT > > |
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using | ConstPtr = shared_ptr< const ISSKeypoint3D< PointInT, PointOutT, NormalT > > |
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using | PointCloudIn = typename Keypoint< PointInT, PointOutT >::PointCloudIn |
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using | PointCloudOut = typename Keypoint< PointInT, PointOutT >::PointCloudOut |
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using | PointCloudN = pcl::PointCloud< NormalT > |
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using | PointCloudNPtr = typename PointCloudN::Ptr |
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using | PointCloudNConstPtr = typename PointCloudN::ConstPtr |
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using | OctreeSearchIn = pcl::octree::OctreePointCloudSearch< PointInT > |
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using | OctreeSearchInPtr = typename OctreeSearchIn::Ptr |
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using | Ptr = shared_ptr< Keypoint< PointInT, PointOutT > > |
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using | ConstPtr = shared_ptr< const Keypoint< PointInT, PointOutT > > |
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using | BaseClass = PCLBase< PointInT > |
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using | KdTree = pcl::search::Search< PointInT > |
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using | KdTreePtr = typename KdTree::Ptr |
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using | PointCloudIn = pcl::PointCloud< PointInT > |
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using | PointCloudInPtr = typename PointCloudIn::Ptr |
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using | PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
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using | PointCloudOut = pcl::PointCloud< PointOutT > |
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using | SearchMethod = std::function< int(pcl::index_t, double, pcl::Indices &, std::vector< float > &)> |
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using | SearchMethodSurface = std::function< int(const PointCloudIn &cloud, pcl::index_t index, double, pcl::Indices &, std::vector< float > &)> |
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using | PointCloud = pcl::PointCloud< PointInT > |
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using | PointCloudPtr = typename PointCloud::Ptr |
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using | PointCloudConstPtr = typename PointCloud::ConstPtr |
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using | PointIndicesPtr = PointIndices::Ptr |
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using | PointIndicesConstPtr = PointIndices::ConstPtr |
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| ISSKeypoint3D (double salient_radius=0.0001) |
| Constructor.
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| ~ISSKeypoint3D () override |
| Destructor.
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void | setSalientRadius (double salient_radius) |
| Set the radius of the spherical neighborhood used to compute the scatter matrix.
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void | setNonMaxRadius (double non_max_radius) |
| Set the radius for the application of the non maxima suppression algorithm.
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void | setNormalRadius (double normal_radius) |
| Set the radius used for the estimation of the surface normals of the input cloud.
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void | setBorderRadius (double border_radius) |
| Set the radius used for the estimation of the boundary points.
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void | setThreshold21 (double gamma_21) |
| Set the upper bound on the ratio between the second and the first eigenvalue.
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void | setThreshold32 (double gamma_32) |
| Set the upper bound on the ratio between the third and the second eigenvalue.
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void | setMinNeighbors (int min_neighbors) |
| Set the minimum number of neighbors that has to be found while applying the non maxima suppression algorithm.
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void | setNormals (const PointCloudNConstPtr &normals) |
| Set the normals if pre-calculated normals are available.
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void | setAngleThreshold (float angle) |
| Set the decision boundary (angle threshold) that marks points as boundary or regular.
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void | setNumberOfThreads (unsigned int nr_threads=0) |
| Initialize the scheduler and set the number of threads to use.
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| Keypoint ()=default |
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| Keypoint () |
| Empty constructor.
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void | harrisCorner (PointInT &output, PointInT &input, const float sigma_d, const float sigma_i, const float alpha, const float thresh) |
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void | hessianBlob (PointInT &output, PointInT &input, const float sigma, bool SCALE) |
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void | hessianBlob (PointInT &output, PointInT &input, const float start_scale, const float scaling_factor, const int num_scales) |
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void | imageElementMultiply (PointInT &output, PointInT &input1, PointInT &input2) |
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| ~Keypoint () override=default |
| Empty destructor.
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virtual void | setSearchSurface (const PointCloudInConstPtr &cloud) |
| Provide a pointer to the input dataset that we need to estimate features at every point for.
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PointCloudInConstPtr | getSearchSurface () |
| Get a pointer to the surface point cloud dataset.
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void | setSearchMethod (const KdTreePtr &tree) |
| Provide a pointer to the search object.
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KdTreePtr | getSearchMethod () |
| Get a pointer to the search method used.
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double | getSearchParameter () |
| Get the internal search parameter.
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void | setKSearch (int k) |
| Set the number of k nearest neighbors to use for the feature estimation.
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int | getKSearch () |
| get the number of k nearest neighbors used for the feature estimation.
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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.
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double | getRadiusSearch () |
| Get the sphere radius used for determining the neighbors.
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pcl::PointIndicesConstPtr | getKeypointsIndices () |
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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 ()
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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.
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| PCLBase () |
| Empty constructor.
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| PCLBase (const PCLBase &base) |
| Copy constructor.
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virtual | ~PCLBase ()=default |
| Destructor.
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virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset.
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PointCloudConstPtr const | getInputCloud () const |
| Get a pointer to the input point cloud dataset.
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virtual void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data.
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virtual void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data.
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virtual void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data.
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virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
| Set the indices for the points laying within an interest region of the point cloud.
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IndicesPtr | getIndices () |
| Get a pointer to the vector of indices used.
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IndicesConstPtr const | getIndices () const |
| Get a pointer to the vector of indices used.
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const PointInT & | operator[] (std::size_t pos) const |
| Override PointCloud operator[] to shorten code.
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double | salient_radius_ |
| The radius of the spherical neighborhood used to compute the scatter matrix.
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double | non_max_radius_ {0.0} |
| The non maxima suppression radius.
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double | normal_radius_ {0.0} |
| The radius used to compute the normals of the input cloud.
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double | border_radius_ {0.0} |
| The radius used to compute the boundary points of the input cloud.
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double | gamma_21_ {0.975} |
| The upper bound on the ratio between the second and the first eigenvalue returned by the EVD.
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double | gamma_32_ {0.975} |
| The upper bound on the ratio between the third and the second eigenvalue returned by the EVD.
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double * | third_eigen_value_ {nullptr} |
| Store the third eigen value associated to each point in the input cloud.
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bool * | edge_points_ {nullptr} |
| Store the information about the boundary points of the input cloud.
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int | min_neighbors_ {5} |
| Minimum number of neighbors that has to be found while applying the non maxima suppression algorithm.
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PointCloudNConstPtr | normals_ |
| The cloud of normals related to the input surface.
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float | angle_threshold_ |
| The decision boundary (angle threshold) that marks points as boundary or regular.
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unsigned int | threads_ {0} |
| The number of threads that has to be used by the scheduler.
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std::string | name_ |
| The key point detection method's name.
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SearchMethod | search_method_ |
| The search method template for indices.
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SearchMethodSurface | search_method_surface_ |
| The search method template for points.
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PointCloudInConstPtr | surface_ |
| An input point cloud describing the surface that is to be used for nearest neighbors estimation.
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KdTreePtr | tree_ |
| A pointer to the spatial search object.
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double | search_parameter_ |
| The actual search parameter (casted from either search_radius_ or k_).
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double | search_radius_ |
| The nearest neighbors search radius for each point.
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int | k_ |
| The number of K nearest neighbors to use for each point.
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pcl::PointIndicesPtr | keypoints_indices_ |
| Indices of the keypoints in the input cloud.
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PointCloudConstPtr | input_ |
| The input point cloud dataset.
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IndicesPtr | indices_ |
| A pointer to the vector of point indices to use.
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bool | use_indices_ |
| Set to true if point indices are used.
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bool | fake_indices_ |
| If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud.
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template<typename PointInT, typename PointOutT, typename
NormalT = pcl::Normal>
class pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >
ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given point cloud.
This class is based on a particular implementation made by Federico Tombari and Samuele Salti and it has been explicitly adapted to PCL.
For more information about the original ISS detector, see:
- Yu Zhong, “Intrinsic shape signatures: A shape descriptor for 3D object recognition,” Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on , vol., no., pp.689-696, Sept. 27 2009-Oct. 4 2009
Code example:
double model_resolution;
iss_detector.
compute (*model_keypoints);
ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given point cloud.
void setNumberOfThreads(unsigned int nr_threads=0)
Initialize the scheduler and set the number of threads to use.
void setSalientRadius(double salient_radius)
Set the radius of the spherical neighborhood used to compute the scatter matrix.
void setThreshold21(double gamma_21)
Set the upper bound on the ratio between the second and the first eigenvalue.
void setMinNeighbors(int min_neighbors)
Set the minimum number of neighbors that has to be found while applying the non maxima suppression al...
void setThreshold32(double gamma_32)
Set the upper bound on the ratio between the third and the second eigenvalue.
void setNonMaxRadius(double non_max_radius)
Set the radius for the application of the non maxima suppression algorithm.
void compute(PointCloudOut &output)
Base method for key point detection for all points given in <setInputCloud (), setIndices ()> using t...
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
virtual void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
PointCloud represents the base class in PCL for storing collections of 3D points.
shared_ptr< PointCloud< PointT > > Ptr
search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search function...
shared_ptr< KdTree< PointT, Tree > > Ptr
- Author
- Gioia Ballin
Definition at line 85 of file iss_3d.h.