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compute_cloud_error.cpp
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225 lines (188 loc) · 9.07 KB
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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2010-2011, 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/PCLPointCloud2.h>
#include <pcl/point_types.h>
#include <pcl/common/distances.h>
#include <pcl/io/pcd_io.h>
#include <pcl/console/print.h>
#include <pcl/console/parse.h>
#include <pcl/search/auto.h>
using namespace pcl;
using namespace pcl::io;
using namespace pcl::console;
std::string default_correspondence_type = "index";
void
printHelp (int, char **argv)
{
print_error ("Syntax is: %s source.pcd target.pcd output_intensity.pcd <options>\n", argv[0]);
print_info (" where options are:\n");
print_info (" -correspondence X = the way of selecting the corresponding pair in the target cloud for the current point in the source cloud\n");
print_info (" options are: index = points with identical indices are paired together. Note: both clouds need to have the same number of points\n");
print_info (" nn = source point is paired with its nearest neighbor in the target cloud\n");
print_info (" nnplane = source point is paired with its projection on the plane determined by the nearest neighbor in the target cloud. Note: target cloud needs to contain normals\n");
print_info (" (default: ");
print_value ("%s", default_correspondence_type.c_str ()); print_info (")\n");
}
void
compute (const pcl::PCLPointCloud2::ConstPtr &cloud_source, const pcl::PCLPointCloud2::ConstPtr &cloud_target,
pcl::PCLPointCloud2 &output, const std::string &correspondence_type)
{
PointCloud<PointXYZ>::Ptr xyz_source (new PointCloud<PointXYZ> ());
fromPCLPointCloud2 (*cloud_source, *xyz_source);
PointCloud<PointXYZ>::Ptr xyz_target (new PointCloud<PointXYZ> ());
fromPCLPointCloud2 (*cloud_target, *xyz_target);
PointCloud<PointXYZI>::Ptr output_xyzi (new PointCloud<PointXYZI> ());
output_xyzi->points.resize (xyz_source->size ());
output_xyzi->height = cloud_source->height;
output_xyzi->width = cloud_source->width;
float rmse = 0.0f;
if (correspondence_type == "index")
{
// print_highlight (stderr, "Computing using the equal indices correspondence heuristic.\n");
if (xyz_source->size () != xyz_target->size ())
{
print_error ("Source and target clouds do not have the same number of points.\n");
return;
}
for (std::size_t point_i = 0; point_i < xyz_source->size (); ++point_i)
{
if (!std::isfinite ((*xyz_source)[point_i].x) || !std::isfinite ((*xyz_source)[point_i].y) || !std::isfinite ((*xyz_source)[point_i].z))
continue;
if (!std::isfinite ((*xyz_target)[point_i].x) || !std::isfinite ((*xyz_target)[point_i].y) || !std::isfinite ((*xyz_target)[point_i].z))
continue;
float dist = squaredEuclideanDistance ((*xyz_source)[point_i], (*xyz_target)[point_i]);
rmse += dist;
(*output_xyzi)[point_i].x = (*xyz_source)[point_i].x;
(*output_xyzi)[point_i].y = (*xyz_source)[point_i].y;
(*output_xyzi)[point_i].z = (*xyz_source)[point_i].z;
(*output_xyzi)[point_i].intensity = dist;
}
rmse = std::sqrt (rmse / static_cast<float> (xyz_source->size ()));
}
else if (correspondence_type == "nn")
{
// print_highlight (stderr, "Computing using the nearest neighbor correspondence heuristic.\n");
pcl::search::Search<PointXYZ>::Ptr tree(pcl::search::autoSelectMethod<PointXYZ>(xyz_target, false, pcl::search::Purpose::one_knn_search));
for (std::size_t point_i = 0; point_i < xyz_source->size (); ++ point_i)
{
if (!std::isfinite ((*xyz_source)[point_i].x) || !std::isfinite ((*xyz_source)[point_i].y) || !std::isfinite ((*xyz_source)[point_i].z))
continue;
pcl::Indices nn_indices (1);
std::vector<float> nn_distances (1);
if (!tree->nearestKSearch ((*xyz_source)[point_i], 1, nn_indices, nn_distances))
continue;
std::size_t point_nn_i = nn_indices.front();
float dist = squaredEuclideanDistance ((*xyz_source)[point_i], (*xyz_target)[point_nn_i]);
rmse += dist;
(*output_xyzi)[point_i].x = (*xyz_source)[point_i].x;
(*output_xyzi)[point_i].y = (*xyz_source)[point_i].y;
(*output_xyzi)[point_i].z = (*xyz_source)[point_i].z;
(*output_xyzi)[point_i].intensity = dist;
}
rmse = std::sqrt (rmse / static_cast<float> (xyz_source->size ()));
}
else if (correspondence_type == "nnplane")
{
// print_highlight (stderr, "Computing using the nearest neighbor plane projection correspondence heuristic.\n");
PointCloud<Normal>::Ptr normals_target (new PointCloud<Normal> ());
fromPCLPointCloud2 (*cloud_target, *normals_target);
pcl::search::Search<PointXYZ>::Ptr tree(pcl::search::autoSelectMethod<PointXYZ>(xyz_target, false, pcl::search::Purpose::one_knn_search));
for (std::size_t point_i = 0; point_i < xyz_source->size (); ++ point_i)
{
if (!std::isfinite ((*xyz_source)[point_i].x) || !std::isfinite ((*xyz_source)[point_i].y) || !std::isfinite ((*xyz_source)[point_i].z))
continue;
pcl::Indices nn_indices (1);
std::vector<float> nn_distances (1);
if (!tree->nearestKSearch ((*xyz_source)[point_i], 1, nn_indices, nn_distances))
continue;
std::size_t point_nn_i = nn_indices.front();
Eigen::Vector3f normal_target = (*normals_target)[point_nn_i].getNormalVector3fMap (),
point_source = (*xyz_source)[point_i].getVector3fMap (),
point_target = (*xyz_target)[point_nn_i].getVector3fMap ();
float dist = normal_target.dot (point_source - point_target);
rmse += dist * dist;
(*output_xyzi)[point_i].x = (*xyz_source)[point_i].x;
(*output_xyzi)[point_i].y = (*xyz_source)[point_i].y;
(*output_xyzi)[point_i].z = (*xyz_source)[point_i].z;
(*output_xyzi)[point_i].intensity = dist * dist;
}
rmse = std::sqrt (rmse / static_cast<float> (xyz_source->size ()));
}
else
{
// print_error ("Unrecognized correspondence type. Check legal arguments by using the -h option\n");
return;
}
toPCLPointCloud2 (*output_xyzi, output);
print_highlight ("RMSE Error: %f\n", rmse);
}
/* ---[ */
int
main (int argc, char** argv)
{
// print_info ("Compute the differences between two point clouds and visualizing them as an output intensity cloud. For more information, use: %s -h\n", argv[0]);
if (argc < 4)
{
printHelp (argc, argv);
return (-1);
}
// 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 () != 3)
{
print_error ("Need two input PCD files and one output PCD file to continue.\n");
return (-1);
}
// Command line parsing
std::string correspondence_type = default_correspondence_type;
parse_argument (argc, argv, "-correspondence", correspondence_type);
// Load the first file
pcl::PCLPointCloud2::Ptr cloud_source (new pcl::PCLPointCloud2 ());
if (loadPCDFile (argv[p_file_indices[0]], *cloud_source) != 0)
return (-1);
// Load the second file
pcl::PCLPointCloud2::Ptr cloud_target (new pcl::PCLPointCloud2 ());
if (loadPCDFile (argv[p_file_indices[1]], *cloud_target) != 0)
return (-1);
pcl::PCLPointCloud2 output;
// Perform the feature estimation
compute (cloud_source, cloud_target, output, correspondence_type);
// Output the third file
savePCDFile (argv[p_file_indices[2]], output);
}