#include <iostream> #include <pcl/ModelCoefficients.h> #include <pcl/io/pcd_io.h> #include <pcl/point_types.h> #include <pcl/sample_consensus/method_types.h> #include <pcl/sample_consensus/model_types.h> #include <pcl/segmentation/sac_segmentation.h> int main(int argc, char** argv) { pcl::PointCloud<pcl::PointXYZ> cloud; //填充点云数据 cloud.width = 15; cloud.height = 1; cloud.points.resize(cloud.width * cloud.height); //生成数据 for (size_t i = 0; i < cloud.points.size(); ++i) { cloud.points[i].x = 1024 * rand() / (RAND_MAX + 1.0f); cloud.points[i].y = 1024 * rand() / (RAND_MAX + 1.0f); cloud.points[i].z = 1.0; } //设置几个局外点 cloud.points[0].z = 2.0; cloud.points[3].z = -2.0; cloud.points[6].z = 4.0; std::cerr << "Point cloud data: " << cloud.points.size() << " points" << std::endl; for (size_t i = 0; i < cloud.points.size(); ++i) std::cerr << " " << cloud.points[i].x << " " << cloud.points[i].y << " " << cloud.points[i].z << std::endl; //设置平面模型系数对象coefficients pcl::ModelCoefficients::Ptr coefficients(new pcl::ModelCoefficients); //储存内点的点索引几何对象inliers pcl::PointIndices::Ptr inliers(new pcl::PointIndices); //创建分割对象 pcl::SACSegmentation<pcl::PointXYZ> seg; //可选设置 seg.setOptimizeCoefficients(true); //必须设置,设置分割模型类型 seg.setModelType(pcl::SACMODEL_PLANE); //所用的随机参数估计方法 seg.setMethodType(pcl::SAC_RANSAC); //距离阈值 seg.setDistanceThreshold(0.01); //输入点云 seg.setInputCloud(cloud.makeShared()); seg.segment(*inliers, *coefficients); if (inliers->indices.size() == 0) { PCL_ERROR("Could not estimate a planar model for the given dataset."); return (-1); } std::cerr << "Model coefficients: " << coefficients->values[0] << " " << coefficients->values[1] << " " << coefficients->values[2] << " " << coefficients->values[3] << std::endl; std::cerr << "Model inliers: " << inliers->indices.size() << std::endl; for (size_t i = 0; i < inliers->indices.size(); ++i) std::cerr << inliers->indices[i] << " " << cloud.points[inliers->indices[i]].x << " " << cloud.points[inliers->indices[i]].y << " " << cloud.points[inliers->indices[i]].z << std::endl; return (0); }