PCL:旋转、平移点云
#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> // pcl::transformPointCloud 用到这个头文件
#include <pcl/visualization/pcl_visualizer.h>
// 帮助函数
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;
}
// 主函数
int
main (int argc, char** argv)
{
// 如果没有输入预期的参数程序将显示帮助
if (pcl::console::find_switch (argc, argv, "-h") || pcl::console::find_switch (argc, argv, "--help")) {
showHelp (argv[0]);
return 0;
}
// 从主函数参数查找点云数据文件 (.PCD|.PLY)
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;
}
}
// 加载点云数据文件
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;
}
}
/* 提示: 变换矩阵工作原理 :
|-------> 变换矩阵列
| 1 0 0 x | \
| 0 1 0 y | }-> 左边是一个3阶的单位阵(无旋转)
| 0 0 1 z | /
| 0 0 0 1 | -> 这一行用不到 (这一行保持 0,0,0,1)
方法一 #1: 使用 Matrix4f
这个是“手工方法”,可以完美地理解,但容易出错!
*/
Eigen::Matrix4f transform_1 = Eigen::Matrix4f::Identity();
// 定义一个旋转矩阵 (见 https://en.wikipedia.org/wiki/Rotation_matrix)
float theta = M_PI/4; // 弧度角
transform_1 (0,0) = cos (theta);
transform_1 (0,1) = -sin(theta);
transform_1 (1,0) = sin (theta);
transform_1 (1,1) = cos (theta);
// (行, 列)
// 在 X 轴上定义一个 2.5 米的平移.
transform_1 (0,3) = 2.5;
// 打印变换矩阵
printf ("Method #1: using a Matrix4f\n");
std::cout << transform_1 << std::endl;
/* 方法二 #2: 使用 Affine3f
这种方法简单,不易出错
*/
Eigen::Affine3f transform_2 = Eigen::Affine3f::Identity();
// 在 X 轴上定义一个 2.5 米的平移.
transform_2.translation() << 2.5, 0.0, 0.0;
// 和前面一样的旋转; Z 轴上旋转 theta 弧度
transform_2.rotate (Eigen::AngleAxisf (theta, Eigen::Vector3f::UnitZ()));
// 打印变换矩阵
printf ("\nMethod #2: using an Affine3f\n");
std::cout << transform_2.matrix() << std::endl;
// 执行变换,并将结果保存在新创建的 transformed_cloud 中
pcl::PointCloud<pcl::PointXYZ>::Ptr transformed_cloud (new pcl::PointCloud<pcl::PointXYZ> ());
// 可以使用 transform_1 或 transform_2; t它们是一样的
pcl::transformPointCloud (*source_cloud, *transformed_cloud, transform_2);
// 可视化
// 可视化将原始点云显示为白色,变换后的点云为红色,还设置了坐标轴、背景颜色、点显示大小
printf( "\nPoint cloud colors : white = original point cloud\n"
" red = transformed point cloud\n");
pcl::visualization::PCLVisualizer viewer ("Matrix transformation example");
// 为点云定义 R,G,B 颜色
pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> source_cloud_color_handler (source_cloud, 255, 255, 255);
// 输出点云到查看器,使用颜色管理
viewer.addPointCloud (source_cloud, source_cloud_color_handler, "original_cloud");
pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> transformed_cloud_color_handler (transformed_cloud, 230, 20, 20); // 红
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); // 设置背景为深灰
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); // 设置窗口位置
while (!viewer.wasStopped ()) { // 在按下 "q" 键之前一直会显示窗口
viewer.spinOnce ();
}
return 0;
}
cmake:
cmake_minimum_required(VERSION 2.6 FATAL_ERROR)
project(pcl-matrix_transform)
find_package(PCL 1.7 REQUIRED)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
add_executable (matrix_transform matrix_transform.cpp)
target_link_libraries (matrix_transform ${PCL_LIBRARIES})
result:
./matrix_transform cube.ply
[pcl::PLYReader] /home/victor/cube.ply:12: property 'list uint8 uint32 vertex_indices' of element 'face' is not handled
Method #1: using a Matrix4f
0.707107 -0.707107 0 2.5
0.707107 0.707107 0 0
0 0 1 0
0 0 0 1
Method #2: using an Affine3f
0.707107 -0.707107 0 2.5
0.707107 0.707107 0 0
0 0 1 0
0 0 0 1
Point cloud colors : white = original point cloud
red = transformed point cloud