Program Listing for File susan.h¶
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#ifndef PCL_SUSAN_KEYPOINT_H_
#define PCL_SUSAN_KEYPOINT_H_
#include <pcl/keypoints/keypoint.h>
#include <pcl/common/intensity.h>
namespace pcl
{
/** \brief SUSANKeypoint implements a RGB-D extension of the SUSAN detector including normal
* directions variation in top of intensity variation.
* It is different from Harris in that it exploits normals directly so it is faster.
* Original paper "SUSAN — A New Approach to Low Level Image Processing", Smith,
* Stephen M. and Brady, J. Michael
*
* \author Nizar Sallem
* \ingroup keypoints
*/
template <typename PointInT, typename PointOutT, typename NormalT = pcl::Normal, typename IntensityT= pcl::common::IntensityFieldAccessor<PointInT> >
class SUSANKeypoint : public Keypoint<PointInT, PointOutT>
{
public:
typedef boost::shared_ptr<SUSANKeypoint<PointInT, PointOutT, NormalT, IntensityT> > Ptr;
typedef boost::shared_ptr<const SUSANKeypoint<PointInT, PointOutT, NormalT, Intensity> > ConstPtr;
typedef typename Keypoint<PointInT, PointOutT>::PointCloudIn PointCloudIn;
typedef typename Keypoint<PointInT, PointOutT>::PointCloudOut PointCloudOut;
typedef typename Keypoint<PointInT, PointOutT>::KdTree KdTree;
typedef typename PointCloudIn::ConstPtr PointCloudInConstPtr;
typedef typename pcl::PointCloud<NormalT> PointCloudN;
typedef typename PointCloudN::Ptr PointCloudNPtr;
typedef typename PointCloudN::ConstPtr PointCloudNConstPtr;
using Keypoint<PointInT, PointOutT>::name_;
using Keypoint<PointInT, PointOutT>::input_;
using Keypoint<PointInT, PointOutT>::indices_;
using Keypoint<PointInT, PointOutT>::surface_;
using Keypoint<PointInT, PointOutT>::tree_;
using Keypoint<PointInT, PointOutT>::k_;
using Keypoint<PointInT, PointOutT>::search_radius_;
using Keypoint<PointInT, PointOutT>::search_parameter_;
using Keypoint<PointInT, PointOutT>::keypoints_indices_;
using Keypoint<PointInT, PointOutT>::initCompute;
/** \brief Constructor
* \param[in] radius the radius for normal estimation as well as for non maxima suppression
* \param[in] distance_threshold to test if the nucleus is far enough from the centroid
* \param[in] angular_threshold to test if normals are parallel
* \param[in] intensity_threshold to test if points are of same color
*/
SUSANKeypoint (float radius = 0.01f,
float distance_threshold = 0.001f,
float angular_threshold = 0.0001f,
float intensity_threshold = 7.0f)
: distance_threshold_ (distance_threshold)
, angular_threshold_ (angular_threshold)
, intensity_threshold_ (intensity_threshold)
, normals_ (new pcl::PointCloud<NormalT>)
, threads_ (0)
, label_idx_ (-1)
, out_fields_ ()
{
name_ = "SUSANKeypoint";
search_radius_ = radius;
geometric_validation_ = false;
tolerance_ = 2 * distance_threshold_;
}
/** \brief Empty destructor */
virtual ~SUSANKeypoint () {}
/** \brief set the radius for normal estimation and non maxima supression.
* \param[in] radius
*/
void
setRadius (float radius);
void
setDistanceThreshold (float distance_threshold);
/** \brief set the angular_threshold value for detecting corners. Normals are considered as
* parallel if 1 - angular_threshold <= (Ni.Nj) <= 1
* \param[in] angular_threshold
*/
void
setAngularThreshold (float angular_threshold);
/** \brief set the intensity_threshold value for detecting corners.
* \param[in] intensity_threshold
*/
void
setIntensityThreshold (float intensity_threshold);
/**
* \brief set normals if precalculated normals are available.
* \param normals
*/
void
setNormals (const PointCloudNConstPtr &normals);
virtual void
setSearchSurface (const PointCloudInConstPtr &cloud);
/** \brief Initialize the scheduler and set the number of threads to use.
* \param nr_threads the number of hardware threads to use (0 sets the value back to automatic)
*/
void
setNumberOfThreads (unsigned int nr_threads);
/** \brief Apply non maxima suppression to the responses to keep strongest corners.
* \note in SUSAN points with less response or stronger corners
*/
void
setNonMaxSupression (bool nonmax);
/** \brief Filetr false positive using geometric criteria.
* The nucleus and the centroid should at least distance_threshold_ from each other AND all the
* points belonging to the USAN must be within the segment [nucleus centroid].
* \param[in] validate
*/
void
setGeometricValidation (bool validate);
protected:
bool
initCompute ();
void
detectKeypoints (PointCloudOut &output);
/** \brief return true if a point lies within the line between the nucleus and the centroid
* \param[in] nucleus coordinate of the nucleus
* \param[in] centroid of the SUSAN
* \param[in] nc to centroid vector (used to speed up since it is constant for a given
* neighborhood)
* \param[in] point the query point to test against
* \return true if the point lies within [nucleus centroid]
*/
bool
isWithinNucleusCentroid (const Eigen::Vector3f& nucleus,
const Eigen::Vector3f& centroid,
const Eigen::Vector3f& nc,
const PointInT& point) const;
private:
float distance_threshold_;
float angular_threshold_;
float intensity_threshold_;
float tolerance_;
PointCloudNConstPtr normals_;
unsigned int threads_;
bool geometric_validation_;
bool nonmax_;
/// intensity field accessor
IntensityT intensity_;
/** \brief Set to a value different than -1 if the output cloud has a "label" field and we have
* to save the keypoints indices.
*/
int label_idx_;
/** \brief The list of fields present in the output point cloud data. */
std::vector<pcl::PCLPointField> out_fields_;
pcl::common::IntensityFieldAccessor<PointOutT> intensity_out_;
};
}
#include <pcl/keypoints/impl/susan.hpp>
#endif // #ifndef PCL_SUSAN_KEYPOINT_H_