基于pcl库拟合已知空间两点坐标的直线并计算点云ply文件内点到该直线的距离的C++代码
下面是一个使用pcl库拟合已知空间两点坐标的直线,并计算点云ply文件内点到该直线的距离的C++代码的示例:
#include <iostream>
#include <pcl/io/ply_io.h>
#include <pcl/point_types.h>
#include <pcl/ModelCoefficients.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)
{
// 读取点云数据
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
pcl::PLYReader reader;
reader.read(argv[1], *cloud);
// 定义直线模型系数对象
pcl::ModelCoefficients::Ptr coefficients(new pcl::ModelCoefficients);
pcl::PointIndices::Ptr inliers(new pcl::PointIndices);
// 创建分割对象
pcl::SACSegmentation<pcl::PointXYZ> seg;
seg.setOptimizeCoefficients(true);
seg.setModelType(pcl::SACMODEL_LINE);
seg.setMethodType(pcl::SAC_RANSAC);
seg.setDistanceThreshold(0.01);
// 设置输入点云
seg.setInputCloud(cloud);
// 执行分割
seg.segment(*inliers, *coefficients);
// 输出直线模型系数
std::cout << "Line coefficients: " << coefficients->values[0] << " "
<< coefficients->values[1] << " " << coefficients->values[2] << " "
<< coefficients->values[3] << std::endl;
// 计算点到直线的距离
for (size_t i = 0; i < cloud->points.size(); ++i)
{
// 获取点坐标
pcl::PointXYZ point = cloud->points[i];
// 计算点到直线的距离
float distance = fabs(coefficients->values[0] * point.x +
coefficients->values[1] * point.y +
coefficients->values[2] * point.z +
coefficients->values[3]) /
sqrt(coefficients->values[0] * coefficients->values[0] +
coefficients->values[1] * coefficients->values[1] +
coefficients->values[2] * coefficients->values[2]);
std::cout << "Point " << i << " distance to line: " << distance << std::endl;
}
return 0;
}
请确保已经安装了pcl库,并将点云数据保存为ply格式的文件。在命令行中编译并运行该代码,将点云文件的路径作为命令行参数传递给该程序。程序将输出拟合直线的系数以及每个点到直线的距离
原文地址: https://www.cveoy.top/t/topic/hLZN 著作权归作者所有。请勿转载和采集!