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#include <pcl/console/parse.h>
#include <pcl/point_types.h>
#include <pcl/point_cloud.h>
#include <pcl/point_representation.h>
#include <pcl/io/pcd_io.h>
#include <pcl/conversions.h>
#include <pcl/filters/uniform_sampling.h>
#include <pcl/features/normal_3d.h>
#include <pcl/features/fpfh.h>
#include <pcl/registration/correspondence_estimation.h>
#include <pcl/registration/correspondence_rejection_distance.h>
#include <pcl/registration/transformation_estimation_svd.h>
using namespace pcl;
using namespace pcl::io;
using namespace pcl::console;
using namespace pcl::registration;
PointCloud<PointXYZ>::Ptr src, tgt;
////////////////////////////////////////////////////////////////////////////////
void
estimateKeypoints (const PointCloud<PointXYZ>::Ptr &src,
const PointCloud<PointXYZ>::Ptr &tgt,
PointCloud<PointXYZ> &keypoints_src,
PointCloud<PointXYZ> &keypoints_tgt)
{
// Get an uniform grid of keypoints
UniformSampling<PointXYZ> uniform;
uniform.setRadiusSearch (1); // 1m
uniform.setInputCloud (src);
uniform.filter (keypoints_src);
uniform.setInputCloud (tgt);
uniform.filter (keypoints_tgt);
// For debugging purposes only: uncomment the lines below and use pcl_viewer to view the results, i.e.:
// pcl_viewer source_pcd keypoints_src.pcd -ps 1 -ps 10
savePCDFileBinary ("keypoints_src.pcd", keypoints_src);
savePCDFileBinary ("keypoints_tgt.pcd", keypoints_tgt);
}
////////////////////////////////////////////////////////////////////////////////
void
estimateNormals (const PointCloud<PointXYZ>::Ptr &src,
const PointCloud<PointXYZ>::Ptr &tgt,
PointCloud<Normal> &normals_src,
PointCloud<Normal> &normals_tgt)
{
NormalEstimation<PointXYZ, Normal> normal_est;
normal_est.setInputCloud (src);
normal_est.setRadiusSearch (0.5); // 50cm
normal_est.compute (normals_src);
normal_est.setInputCloud (tgt);
normal_est.compute (normals_tgt);
// For debugging purposes only: uncomment the lines below and use pcl_viewer to view the results, i.e.:
// pcl_viewer normals_src.pcd
PointCloud<PointNormal> s, t;
copyPointCloud (*src, s);
copyPointCloud (normals_src, s);
copyPointCloud (*tgt, t);
copyPointCloud (normals_tgt, t);
savePCDFileBinary ("normals_src.pcd", s);
savePCDFileBinary ("normals_tgt.pcd", t);
}
////////////////////////////////////////////////////////////////////////////////
void
estimateFPFH (const PointCloud<PointXYZ>::Ptr &src,
const PointCloud<PointXYZ>::Ptr &tgt,
const PointCloud<Normal>::Ptr &normals_src,
const PointCloud<Normal>::Ptr &normals_tgt,
const PointCloud<PointXYZ>::Ptr &keypoints_src,
const PointCloud<PointXYZ>::Ptr &keypoints_tgt,
PointCloud<FPFHSignature33> &fpfhs_src,
PointCloud<FPFHSignature33> &fpfhs_tgt)
{
FPFHEstimation<PointXYZ, Normal, FPFHSignature33> fpfh_est;
fpfh_est.setInputCloud (keypoints_src);
fpfh_est.setInputNormals (normals_src);
fpfh_est.setRadiusSearch (1); // 1m
fpfh_est.setSearchSurface (src);
fpfh_est.compute (fpfhs_src);
fpfh_est.setInputCloud (keypoints_tgt);
fpfh_est.setInputNormals (normals_tgt);
fpfh_est.setSearchSurface (tgt);
fpfh_est.compute (fpfhs_tgt);
// For debugging purposes only: uncomment the lines below and use pcl_viewer to view the results, i.e.:
// pcl_viewer fpfhs_src.pcd
PCLPointCloud2 s, t, out;
toPCLPointCloud2 (*keypoints_src, s); toPCLPointCloud2 (fpfhs_src, t); concatenateFields (s, t, out);
savePCDFile ("fpfhs_src.pcd", out);
toPCLPointCloud2 (*keypoints_tgt, s); toPCLPointCloud2 (fpfhs_tgt, t); concatenateFields (s, t, out);
savePCDFile ("fpfhs_tgt.pcd", out);
}
////////////////////////////////////////////////////////////////////////////////
void
findCorrespondences (const PointCloud<FPFHSignature33>::Ptr &fpfhs_src,
const PointCloud<FPFHSignature33>::Ptr &fpfhs_tgt,
Correspondences &all_correspondences)
{
CorrespondenceEstimation<FPFHSignature33, FPFHSignature33> est;
est.setInputCloud (fpfhs_src);
est.setInputTarget (fpfhs_tgt);
est.determineReciprocalCorrespondences (all_correspondences);
}
////////////////////////////////////////////////////////////////////////////////
void
rejectBadCorrespondences (const CorrespondencesPtr &all_correspondences,
const PointCloud<PointXYZ>::Ptr &keypoints_src,
const PointCloud<PointXYZ>::Ptr &keypoints_tgt,
Correspondences &remaining_correspondences)
{
CorrespondenceRejectorDistance rej;
rej.setInputSource<PointXYZ> (keypoints_src);
rej.setInputTarget<PointXYZ> (keypoints_tgt);
rej.setMaximumDistance (1); // 1m
rej.setInputCorrespondences (all_correspondences);
rej.getCorrespondences (remaining_correspondences);
}
////////////////////////////////////////////////////////////////////////////////
void
computeTransformation (const PointCloud<PointXYZ>::Ptr &src,
const PointCloud<PointXYZ>::Ptr &tgt,
Eigen::Matrix4f &transform)
{
// Get an uniform grid of keypoints
PointCloud<PointXYZ>::Ptr keypoints_src (new PointCloud<PointXYZ>),
keypoints_tgt (new PointCloud<PointXYZ>);
estimateKeypoints (src, tgt, *keypoints_src, *keypoints_tgt);
print_info ("Found %zu and %zu keypoints for the source and target datasets.\n", static_cast<std::size_t>(keypoints_src->size ()), static_cast<std::size_t>(keypoints_tgt->size ()));
// Compute normals for all points keypoint
PointCloud<Normal>::Ptr normals_src (new PointCloud<Normal>),
normals_tgt (new PointCloud<Normal>);
estimateNormals (src, tgt, *normals_src, *normals_tgt);
print_info ("Estimated %zu and %zu normals for the source and target datasets.\n", static_cast<std::size_t>(normals_src->size ()), static_cast<std::size_t>(normals_tgt->size ()));
// Compute FPFH features at each keypoint
PointCloud<FPFHSignature33>::Ptr fpfhs_src (new PointCloud<FPFHSignature33>),
fpfhs_tgt (new PointCloud<FPFHSignature33>);
estimateFPFH (src, tgt, normals_src, normals_tgt, keypoints_src, keypoints_tgt, *fpfhs_src, *fpfhs_tgt);
// Copy the data and save it to disk
/* PointCloud<PointNormal> s, t;
copyPointCloud (*keypoints_src, s);
copyPointCloud (normals_src, s);
copyPointCloud (*keypoints_tgt, t);
copyPointCloud (normals_tgt, t);*/
// Find correspondences between keypoints in FPFH space
CorrespondencesPtr all_correspondences (new Correspondences),
good_correspondences (new Correspondences);
findCorrespondences (fpfhs_src, fpfhs_tgt, *all_correspondences);
// Reject correspondences based on their XYZ distance
rejectBadCorrespondences (all_correspondences, keypoints_src, keypoints_tgt, *good_correspondences);
for (int i = 0; i < good_correspondences->size (); ++i)
std::cerr << good_correspondences->at (i) << std::endl;
// Obtain the best transformation between the two sets of keypoints given the remaining correspondences
TransformationEstimationSVD<PointXYZ, PointXYZ> trans_est;
trans_est.estimateRigidTransformation (*keypoints_src, *keypoints_tgt, *good_correspondences, transform);
}
/* ---[ */
int
main (int argc, char** argv)
{
// Parse the command line arguments for .pcd files
std::vector<int> p_file_indices;
p_file_indices = parse_file_extension_argument (argc, argv, ".pcd");
if (p_file_indices.size () != 2)
{
print_error ("Need one input source PCD file and one input target PCD file to continue.\n");
print_error ("Example: %s source.pcd target.pcd\n", argv[0]);
return (-1);
}
// Load the files
print_info ("Loading %s as source and %s as target...\n", argv[p_file_indices[0]], argv[p_file_indices[1]]);
src.reset (new PointCloud<PointXYZ>);
tgt.reset (new PointCloud<PointXYZ>);
if (loadPCDFile (argv[p_file_indices[0]], *src) == -1 || loadPCDFile (argv[p_file_indices[1]], *tgt) == -1)
{
print_error ("Error reading the input files!\n");
return (-1);
}
// Compute the best transformtion
Eigen::Matrix4f transform;
computeTransformation (src, tgt, transform);
std::cerr << transform << std::endl;
// Transform the data and write it to disk
PointCloud<PointXYZ> output;
transformPointCloud (*src, output, transform);
savePCDFileBinary ("source_transformed.pcd", output);
}
/* ]--- */
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