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