"#include \n#include <pcl/io/ply_io.h>\n#include <pcl/point_types.h>\n#include <pcl/common/pca.h>\n#include <pcl/segmentation/sac_segmentation.h>\n#include <pcl/visualization/pcl_visualizer.h>\n\nint main()\n{\n\t//------------------------------输入点云-----------------------------------\n\tpcl::PointCloudpcl::PointXYZ::Ptr cloud(new pcl::PointCloudpcl::PointXYZ);\n\tif (pcl::io::loadPLYFilepcl::PointXYZ("D:\DIANYUNWENJIANJIA\newkruskal2_ply.ply", *cloud) < 0)\n\t{\n\t PCL_ERROR("读取文件错误");\n\t return -1;\n\t}\n\t//---------------------------------PCA-------------------------------------\n\tpcl::PCApcl::PointXYZ pca;\n\tpca.setInputCloud(cloud);\n\n\t// 获取特征值对应的特征向量\n\tEigen::Vector3f V1 = pca.getEigenVectors().col(0);\n\tEigen::Vector3f V2 = pca.getEigenVectors().col(1);\n\tEigen::Vector3f V3 = pca.getEigenVectors().col(2);\n\n\t//---------------------------直线的点向式---------------------------------\n\tfloat m = V1[0], n = V1[1], p = V1[2];\n\tfloat x0 = pca.getMean()[0], y0 = pca.getMean()[1], z0 = pca.getMean()[2];\n\tstd::cout << "直线的方向向量为：" << V1.transpose() << std::endl;\n\tstd::cout << "直线上一点的坐标为：" << pca.getMean().head<3>().transpose() << std::endl;\n\n\t//---------------------------直线的一般式---------------------------------\n\tEigen::Matrix<float, 2, 3> A;\n\tA.row(0) = V2.transpose();\n\tA.row(1) = V3.transpose();\n\tEigen::Vector3f sigma = pca.getMean().head<3>();\n\tEigen::Vector2f b = A * sigma;\n\n\tstd::cout << "直线的一般式为：" << std::endl;\n\tstd::cout << V2[0] << "x+(" << V2[1] << "y)+(" << V2[2] << "z)=" << b[0] << std::endl;\n\tstd::cout << V3[0] << "x+(" << V3[1] << "y)+(" << V3[2] << "z)=" << b[1] << std::endl;\n\n\t//----------------------------点云可视化----------------------------------\n\tpcl::visualization::PCLVisualizer viewer("Point Cloud Viewer");\n\tviewer.setBackgroundColor(0, 0, 0);\n\tviewer.addPointCloudpcl::PointXYZ(cloud, "cloud");\n\tviewer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "cloud");\n\n\t//--------------------------拟合直线可视化--------------------------------\n\tpcl::ModelCoefficients::Ptr coefficients(new pcl::ModelCoefficients);\n\tcoefficients->values.resize(6);\n\tcoefficients->values[0] = x0;\n\tcoefficients->values[1] = y0;\n\tcoefficients->values[2] = z0;\n\tcoefficients->values[3] = m;\n\tcoefficients->values[4] = n;\n\tcoefficients->values[5] = p;\n\n\tpcl::PointXYZ pt1, pt2;\n\tpt1.x = x0;\n\tpt1.y = y0;\n\tpt1.z = z0;\n\tpt2.x = x0 + m;\n\tpt2.y = y0 + n;\n\tpt2.z = z0 + p;\n\tviewer.addLine(pt1, pt2, "line");\n\tviewer.setShapeRenderingProperties(pcl::visualization::PCL_VISUALIZER_COLOR, 1.0, 0.0, 0.0, "line");\n\n\twhile (!viewer.wasStopped())\n\t{\n\t viewer.spinOnce();\n\t}\n\n\t//----------------------------输出点云-----------------------------------\n\tpcl::io::savePLYFile("D:\DIANYUNWENJIANJIA\最小二乘法拟合直线_ply.ply", *cloud);\n\n\treturn 0;\n}\n