#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);
}