PCL平面投影

通过projectPoint将点投影到平面上，代码如下：

#include


#include


#include


#include


#include


#include


#include


using namespace pcl;
using namespace pcl::io;
using namespace pcl::console;
Eigen::Vector4f translation;
Eigen::Quaternionf orientation;
void
printHelp (int, char **argv)
{
print_error ("Syntax is: %s input.pcd output.pcd A B C D\n", argv[0]);
print_info (" where the plane is represented by the following equation:\n");
print_info (" Ax + By + Cz + D = 0\n");
}
bool
loadCloud (const std::string &filename, pcl::PCLPointCloud2 &cloud)
{
TicToc tt;
print_highlight ("Loading "); print_value ("%s ", filename.c_str ());
tt.tic ();
if (loadPCDFile (filename, cloud, translation, orientation) <0)
return (false);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", cloud.width * cloud.height); print_info (" points]\n");
print_info ("Available dimensions: "); print_value ("%s\n", pcl::getFieldsList (cloud).c_str ());
return (true);
}
void
project (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output, float a, float b, float c, float d)
{
Eigen::Vector4f coeffs;
coeffs < // Convert data to PointCloud
PointCloud

::Ptr xyz (new PointCloud

);
fromPCLPointCloud2 (*input, *xyz);
// Estimate
TicToc tt;
tt.tic ();
//First, we'll find a point on the plane
print_highlight (stderr, "Projecting ");
PointCloud

::Ptr projected_cloud_pcl (new PointCloud

);
projected_cloud_pcl->width = xyz->width;
projected_cloud_pcl->height = xyz->height;
projected_cloud_pcl->is_dense = xyz->is_dense;
projected_cloud_pcl->sensor_origin_ = xyz->sensor_origin_;
projected_cloud_pcl->sensor_orientation_ = xyz->sensor_orientation_;
for(size_t i = 0; i points.size(); ++i)
{
pcl::PointXYZ projection;
pcl::projectPoint

(xyz->points[i], coeffs, projection);
projected_cloud_pcl->points.push_back(projection);
}
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : ");
pcl::io::savePCDFile ("foo.pcd", *projected_cloud_pcl);
// Convert data back
pcl::PCLPointCloud2 projected_cloud;
toPCLPointCloud2 (*projected_cloud_pcl, projected_cloud);
//we can actually use concatenate fields to inject our projection into the
//output, the second argument overwrites the first's fields for those that
//are shared
concatenateFields (*input, projected_cloud, output);
}
void
saveCloud (const std::string &filename, const pcl::PCLPointCloud2 &output)
{
TicToc tt;
tt.tic ();
print_highlight ("Saving "); print_value ("%s ", filename.c_str ());

pcl::io::savePCDFile (filename, output, translation, orientation, false);

print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output.width * output.height); print_info (" points]\n");
}
/* ---[ */
int
main (int argc, char** argv)
{
print_info ("Estimate surface normals using pcl::NormalEstimation. For more information, use: %s -h\n", argv[0]);
if (argc <3)
{
printHelp (argc, argv);
return (-1);
}
// Parse the command line arguments for .pcd files
std::vector p_file_indices;
p_file_indices = parse_file_extension_argument (argc, argv, ".pcd");
if (p_file_indices.size () != 2)
{
print_error ("Need one input PCD file and one output PCD file to continue.\n");
return (-1);
}
if(argc != 7)
{
print_error("This function takes: input_file output_file A B C D");
return(-1);
}
// Command line parsing
float a = static_cast (atof (argv[3]));
float b = static_cast (atof (argv[4]));
float c = static_cast (atof (argv[5]));
float d = static_cast (atof (argv[6]));
// Load the first file
pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2);
if (!loadCloud (argv[p_file_indices[0]], *cloud))
return (-1);
// Perform the feature estimation
pcl::PCLPointCloud2 output;
project (cloud, output, a, b, c, d);
// Save into the second file
saveCloud (argv[p_file_indices[1]], output);
}


来源：PCL官方示例