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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2011, 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 the copyright holder(s) 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.
*
* $Id$
*
*/
#include <pcl/console/parse.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/registration/icp.h>
#include <pcl/registration/icp_nl.h>
#include <pcl/registration/transformation_estimation_lm.h>
#include <pcl/registration/warp_point_rigid_3d.h>
#include <string>
#include <iostream>
#include <vector>
using PointType = pcl::PointXYZ;
using Cloud = pcl::PointCloud<PointType>;
using CloudConstPtr = Cloud::ConstPtr;
using CloudPtr = Cloud::Ptr;
int
main (int argc, char **argv)
{
double dist = 0.05;
pcl::console::parse_argument (argc, argv, "-d", dist);
double rans = 0.05;
pcl::console::parse_argument (argc, argv, "-r", rans);
int iter = 50;
pcl::console::parse_argument (argc, argv, "-i", iter);
std::vector<int> pcd_indices;
pcd_indices = pcl::console::parse_file_extension_argument (argc, argv, ".pcd");
CloudPtr model (new Cloud);
if (pcl::io::loadPCDFile (argv[pcd_indices[0]], *model) == -1)
{
std::cout << "Could not read file" << std::endl;
return -1;
}
std::cout << argv[pcd_indices[0]] << " width: " << model->width << " height: " << model->height << std::endl;
std::string result_filename (argv[pcd_indices[0]]);
result_filename = result_filename.substr (result_filename.rfind ('/') + 1);
pcl::io::savePCDFile (result_filename, *model);
std::cout << "saving first model to " << result_filename << std::endl;
Eigen::Matrix4f t (Eigen::Matrix4f::Identity ());
for (std::size_t i = 1; i < pcd_indices.size (); i++)
{
CloudPtr data (new Cloud);
if (pcl::io::loadPCDFile (argv[pcd_indices[i]], *data) == -1)
{
std::cout << "Could not read file" << std::endl;
return -1;
}
std::cout << argv[pcd_indices[i]] << " width: " << data->width << " height: " << data->height << std::endl;
pcl::IterativeClosestPointNonLinear<PointType, PointType> icp;
pcl::registration::WarpPointRigid3D<PointType, PointType>::Ptr warp_fcn
(new pcl::registration::WarpPointRigid3D<PointType, PointType>);
// Create a TransformationEstimationLM object, and set the warp to it
pcl::registration::TransformationEstimationLM<PointType, PointType>::Ptr te (new pcl::registration::TransformationEstimationLM<PointType, PointType>);
te->setWarpFunction (warp_fcn);
// Pass the TransformationEstimation objec to the ICP algorithm
icp.setTransformationEstimation (te);
icp.setMaximumIterations (iter);
icp.setMaxCorrespondenceDistance (dist);
icp.setRANSACOutlierRejectionThreshold (rans);
icp.setInputTarget (model);
icp.setInputSource (data);
CloudPtr tmp (new Cloud);
icp.align (*tmp);
t *= icp.getFinalTransformation ();
pcl::transformPointCloud (*data, *tmp, t);
std::cout << icp.getFinalTransformation () << std::endl;
*model = *data;
std::string result_filename (argv[pcd_indices[i]]);
result_filename = result_filename.substr (result_filename.rfind ('/') + 1);
pcl::io::savePCDFileBinary (result_filename, *tmp);
std::cout << "saving result to " << result_filename << std::endl;
}
return 0;
}
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