使用矩阵来转换点云

版权声明：本文为博主原创文章，未经博主允许不得转载。 https://blog.csdn.net/chuquanchang1051/article/details/80423031

我们将学习如何使用4x4矩阵转换点云。我们将旋转和平移应用到加载的点云并显示结果。

该程序能够加载一个PCD或PLY文件; 对其应用矩阵变换并显示原始变换的点云。

#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>
#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\n");
	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 arround Z axis
	transform_2.rotate(Eigen::AngleAxisf(theta, Eigen::Vector3f::UnitZ()));

	// Print the transformation
	printf("\nMethod #2: using an Affine3f\n");
	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("\nPoint cloud colors :  white  = original point cloud\n"
		"                        red  = transformed point cloud\n");
	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;
}

但是不会编译，尴尬，未完。

参考 

http://pointclouds.org/documentation/tutorials/matrix_transform.php