Point Cloud Library (PCL)
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include
pcl
keypoints
iss_3d.h
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/*
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* Software License Agreement (BSD License)
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*
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* Copyright (c) 2010, Willow Garage, Inc.
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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*/
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#ifndef PCL_ISS_3D_H_
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#define PCL_ISS_3D_H_
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#include <pcl/keypoints/keypoint.h>
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namespace
pcl
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{
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/** \brief ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given
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* point cloud. This class is based on a particular implementation made by Federico
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* Tombari and Samuele Salti and it has been explicitly adapted to PCL.
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*
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* For more information about the original ISS detector, see:
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*
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*\par
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* Yu Zhong, “Intrinsic shape signatures: A shape descriptor for 3D object recognition,”
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* Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on ,
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* vol., no., pp.689-696, Sept. 27 2009-Oct. 4 2009
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*
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* Code example:
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*
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* \code
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* pcl::PointCloud<pcl::PointXYZRGBA>::Ptr model (new pcl::PointCloud<pcl::PointXYZRGBA> ());;
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* pcl::PointCloud<pcl::PointXYZRGBA>::Ptr model_keypoints (new pcl::PointCloud<pcl::PointXYZRGBA> ());
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* pcl::search::KdTree<pcl::PointXYZRGBA>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGBA> ());
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*
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* // Fill in the model cloud
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*
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* double model_resolution;
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*
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* // Compute model_resolution
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*
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* pcl::ISSKeypoint3D<pcl::PointXYZRGBA, pcl::PointXYZRGBA> iss_detector;
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*
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* iss_detector.setSearchMethod (tree);
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* iss_detector.setSalientRadius (6 * model_resolution);
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* iss_detector.setNonMaxRadius (4 * model_resolution);
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* iss_detector.setThreshold21 (0.975);
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* iss_detector.setThreshold32 (0.975);
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* iss_detector.setMinNeighbors (5);
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* iss_detector.setNumberOfThreads (4);
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* iss_detector.setInputCloud (model);
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* iss_detector.compute (*model_keypoints);
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* \endcode
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*
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* \author Gioia Ballin
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* \ingroup keypoints
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*/
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template
<
typename
Po
int
InT,
typename
Po
int
OutT,
typename
NormalT = pcl::Normal>
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class
ISSKeypoint3D
:
public
Keypoint
<PointInT, PointOutT>
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{
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public
:
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typedef
boost::shared_ptr<ISSKeypoint3D<PointInT, PointOutT, NormalT> >
Ptr
;
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typedef
boost::shared_ptr<const ISSKeypoint3D<PointInT, PointOutT, NormalT> >
ConstPtr
;
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typedef
typename
Keypoint<PointInT, PointOutT>::PointCloudIn
PointCloudIn
;
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typedef
typename
Keypoint<PointInT, PointOutT>::PointCloudOut
PointCloudOut
;
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typedef
typename
pcl::PointCloud<NormalT>
PointCloudN
;
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typedef
typename
PointCloudN::Ptr
PointCloudNPtr
;
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typedef
typename
PointCloudN::ConstPtr
PointCloudNConstPtr
;
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typedef
typename
pcl::octree::OctreePointCloudSearch<PointInT>
OctreeSearchIn
;
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typedef
typename
OctreeSearchIn::Ptr
OctreeSearchInPtr
;
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using
Keypoint<PointInT, PointOutT>::name_
;
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using
Keypoint<PointInT, PointOutT>::input_
;
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using
Keypoint<PointInT, PointOutT>::surface_
;
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using
Keypoint<PointInT, PointOutT>::tree_
;
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using
Keypoint<PointInT, PointOutT>::search_radius_
;
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using
Keypoint<PointInT, PointOutT>::search_parameter_
;
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/** \brief Constructor.
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* \param[in] salient_radius the radius of the spherical neighborhood used to compute the scatter matrix.
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*/
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ISSKeypoint3D
(
double
salient_radius = 0.0001)
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:
salient_radius_
(salient_radius)
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,
non_max_radius_
(0.0)
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,
normal_radius_
(0.0)
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,
border_radius_
(0.0)
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,
gamma_21_
(0.975)
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,
gamma_32_
(0.975)
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,
third_eigen_value_
(0)
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,
edge_points_
(0)
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,
min_neighbors_
(5)
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,
normals_
(new pcl::
PointCloud
<
NormalT
>)
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,
angle_threshold_
(static_cast<float> (M_PI) / 2.0f)
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,
threads_
(0)
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{
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name_
=
"ISSKeypoint3D"
;
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search_radius_
=
salient_radius_
;
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}
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/** \brief Set the radius of the spherical neighborhood used to compute the scatter matrix.
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* \param[in] salient_radius the radius of the spherical neighborhood
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*/
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void
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setSalientRadius
(
double
salient_radius);
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/** \brief Set the radius for the application of the non maxima supression algorithm.
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* \param[in] non_max_radius the non maxima suppression radius
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*/
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void
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setNonMaxRadius
(
double
non_max_radius);
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/** \brief Set the radius used for the estimation of the surface normals of the input cloud. If the radius is
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* too large, the temporal performances of the detector may degrade significantly.
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* \param[in] normals_radius the radius used to estimate surface normals
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*/
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void
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setNormalRadius
(
double
normal_radius);
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/** \brief Set the radius used for the estimation of the boundary points. If the radius is too large,
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* the temporal performances of the detector may degrade significantly.
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* \param[in] border_radius the radius used to compute the boundary points
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*/
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void
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setBorderRadius
(
double
border_radius);
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/** \brief Set the upper bound on the ratio between the second and the first eigenvalue.
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* \param[in] gamma_21 the upper bound on the ratio between the second and the first eigenvalue
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*/
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void
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setThreshold21
(
double
gamma_21);
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/** \brief Set the upper bound on the ratio between the third and the second eigenvalue.
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* \param[in] gamma_32 the upper bound on the ratio between the third and the second eigenvalue
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*/
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void
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setThreshold32
(
double
gamma_32);
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/** \brief Set the minimum number of neighbors that has to be found while applying the non maxima suppression algorithm.
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* \param[in] min_neighbors the minimum number of neighbors required
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*/
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void
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setMinNeighbors
(
int
min_neighbors);
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/** \brief Set the normals if pre-calculated normals are available.
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* \param[in] normals the given cloud of normals
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*/
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void
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setNormals
(
const
PointCloudNConstPtr
&normals);
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/** \brief Set the decision boundary (angle threshold) that marks points as boundary or regular.
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* (default \f$\pi / 2.0\f$)
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* \param[in] angle the angle threshold
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*/
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inline
void
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setAngleThreshold
(
float
angle)
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{
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angle_threshold_
= angle;
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}
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/** \brief Initialize the scheduler and set the number of threads to use.
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* \param[in] nr_threads the number of hardware threads to use (0 sets the value back to automatic)
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*/
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inline
void
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setNumberOfThreads
(
unsigned
int
nr_threads = 0) {
threads_
= nr_threads; }
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protected
:
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/** \brief Compute the boundary points for the given input cloud.
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* \param[in] input the input cloud
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* \param[in] border_radius the radius used to compute the boundary points
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* \param[in] the decision boundary that marks the points as boundary
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* \return the vector of boolean values in which the information about the boundary points is stored
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*/
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bool
*
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getBoundaryPoints
(
PointCloudIn
&input,
double
border_radius,
float
angle_threshold);
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/** \brief Compute the scatter matrix for a point index.
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* \param[in] index the index of the point
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* \param[out] cov_m the point scatter matrix
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*/
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void
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getScatterMatrix
(
const
int
¤t_index, Eigen::Matrix3d &cov_m);
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/** \brief Perform the initial checks before computing the keypoints.
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* \return true if all the checks are passed, false otherwise
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*/
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bool
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initCompute
();
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/** \brief Detect the keypoints by performing the EVD of the scatter matrix.
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* \param[out] output the resultant cloud of keypoints
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*/
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void
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detectKeypoints
(
PointCloudOut
&output);
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/** \brief The radius of the spherical neighborhood used to compute the scatter matrix.*/
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double
salient_radius_
;
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/** \brief The non maxima suppression radius. */
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double
non_max_radius_
;
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/** \brief The radius used to compute the normals of the input cloud. */
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double
normal_radius_
;
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/** \brief The radius used to compute the boundary points of the input cloud. */
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double
border_radius_
;
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/** \brief The upper bound on the ratio between the second and the first eigenvalue returned by the EVD. */
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double
gamma_21_
;
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/** \brief The upper bound on the ratio between the third and the second eigenvalue returned by the EVD. */
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double
gamma_32_
;
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/** \brief Store the third eigen value associated to each point in the input cloud. */
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double
*
third_eigen_value_
;
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/** \brief Store the information about the boundary points of the input cloud. */
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bool
*
edge_points_
;
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/** \brief Minimum number of neighbors that has to be found while applying the non maxima suppression algorithm. */
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int
min_neighbors_
;
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/** \brief The cloud of normals related to the input surface. */
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PointCloudNConstPtr
normals_
;
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/** \brief The decision boundary (angle threshold) that marks points as boundary or regular. (default \f$\pi / 2.0\f$) */
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float
angle_threshold_
;
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/** \brief The number of threads that has to be used by the scheduler. */
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unsigned
int
threads_
;
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};
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}
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#include <pcl/keypoints/impl/iss_3d.hpp>
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#endif
/* PCL_ISS_3D_H_ */