pcl之transform a point cloud
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pcl之transform a point cloud
#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/io/ply_io.h>
#include <pcl/point_cloud.h>
#include <pcl/console/parse.h>
#include <pcl/common/transforms.h>
#include <pcl/visualization/pcl_visualizer.h>
// This function displays the help
void showHelp(char * program_name)
{
std::cout << std::endl;
std::cout << "Usage: " << program_name << " cloud_filename.[pcd|ply]" << std::endl;
std::cout << "-h: Show this help." << std::endl;
}
// This is the main function
int main (int argc, char** argv)
{
// Show help
if (pcl::console::find_switch (argc, argv, "-h") || pcl::console::find_switch (argc, argv, "--help"))
{
showHelp (argv[0]);
return 0;
}
// Fetch point cloud filename in arguments | Works with PCD and PLY files
std::vector<int> filenames;
bool file_is_pcd = false;
filenames = pcl::console::parse_file_extension_argument (argc, argv, ".ply");
if (filenames.size () != 1)
{
filenames = pcl::console::parse_file_extension_argument (argc, argv, ".pcd");
if (filenames.size () != 1)
{
showHelp (argv[0]);
return -1;
}
else
{
file_is_pcd = true;
}
}
// Load file | Works with PCD and PLY files
pcl::PointCloud<pcl::PointXYZ>::Ptr source_cloud (new pcl::PointCloud<pcl::PointXYZ> ());
if (file_is_pcd)
{
if (pcl::io::loadPCDFile (argv[filenames[0]], *source_cloud) < 0)
{
std::cout << "Error loading point cloud " << argv[filenames[0]] << std::endl << std::endl;
showHelp (argv[0]);
return -1;
}
}
else
{
if (pcl::io::loadPLYFile (argv[filenames[0]], *source_cloud) < 0)
{
std::cout << "Error loading point cloud " << argv[filenames[0]] << std::endl << std::endl;
showHelp (argv[0]);
return -1;
}
}
/* Reminder: how transformation matrices work :
|-------> This column is the translation
| 1 0 0 x | | 0 1 0 y | }-> The identity 3x3 matrix (no rotation) on the left
| 0 0 1 z | /
| 0 0 0 1 | -> We do not use this line (and it has to stay 0,0,0,1)
METHOD #1: Using a Matrix4f
This is the "manual" method, perfect to understand but error prone !
*/
Eigen::Matrix4f transform_1 = Eigen::Matrix4f::Identity();
// Define a rotation matrix (see https://en.wikipedia.org/wiki/Rotation_matrix)
float theta = M_PI/4; // The angle of rotation in radians
transform_1 (0,0) = cos (theta);
transform_1 (0,1) = -sin(theta);
transform_1 (1,0) = sin (theta);
transform_1 (1,1) = cos (theta);
// (row, column)
// Define a translation of 2.5 meters on the x axis.
transform_1 (0,3) = 2.5;
// Print the transformation
printf ("Method #1: using a Matrix4f
");
std::cout << transform_1 << std::endl;
/* METHOD #2: Using a Affine3f
This method is easier and less error prone
*/
Eigen::Affine3f transform_2 = Eigen::Affine3f::Identity();
// Define a translation of 2.5 meters on the x axis.
transform_2.translation() << 2.5, 0.0, 0.0;
// The same rotation matrix as before; theta radians around Z axis
transform_2.rotate (Eigen::AngleAxisf (theta, Eigen::Vector3f::UnitZ()));
// Print the transformation
printf ("
Method #2: using an Affine3f
");
std::cout << transform_2.matrix() << std::endl;
// Executing the transformation
pcl::PointCloud<pcl::PointXYZ>::Ptr transformed_cloud (new pcl::PointCloud<pcl::PointXYZ> ());
// You can either apply transform_1 or transform_2; they are the same
pcl::transformPointCloud (*source_cloud, *transformed_cloud, transform_2);
// Visualization
printf( "
Point cloud colors : white = original point cloud
"
" red = transformed point cloud
");
pcl::visualization::PCLVisualizer viewer ("Matrix transformation example");
// Define R,G,B colors for the point cloud
pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> source_cloud_color_handler (source_cloud, 255, 255, 255);
// We add the point cloud to the viewer and pass the color handler
viewer.addPointCloud (source_cloud, source_cloud_color_handler, "original_cloud");
pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> transformed_cloud_color_handler (transformed_cloud, 230, 20, 20); // Red
viewer.addPointCloud (transformed_cloud, transformed_cloud_color_handler, "transformed_cloud");
viewer.addCoordinateSystem (1.0, "cloud", 0);
viewer.setBackgroundColor(0.05, 0.05, 0.05, 0); // Setting background to a dark grey
viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 2, "original_cloud");
viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 2, "transformed_cloud");
//viewer.setPosition(800, 400); // Setting visualiser window position
while (!viewer.wasStopped ())
{ // Display the visualiser until 'q' key is pressed
viewer.spinOnce ();
}
return 0;
}
What if you want to transform a single point ? A vector ?
We need a vector with 4 components. What do you put in the last component ? It depends on what you want to do:
- If you want to transform a point: put 1 at the end of the vector so that the translation is taken in account.
- If you want to transform the direction of a vector: put 0 at the end of the vector to ignore the translation.
Here’s a quick example, we want to transform the following vector:
[10, 5, 0, 3, 0, -1]
Where the first 3 components defines the origin coordinates and the last 3 components the direction.
This vector starts at point 10, 5, 0 and ends at 13, 5, -1.
This is what you need to do to transform the vector:
[10, 5, 0, 1] * 4x4_transformation_matrix
[3, 0, -1, 0] * 4x4_transformation_matrix
参考
Documentation - Point Cloud Library (PCL)
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