PCL安装以及CGAL构建三维凸包

基础理论专栏目录 - 知乎 (zhihu.com)

凸包问题——概述 - 知乎 (zhihu.com)

 

1、安装PCL

 安装pcl,我的是window10,vs2019。我安装的是1.13

win10系统下 VS2019点云库PCL1.12.0的安装与配置_windows 10使用pcl-CSDN博客

照着上述博客进行配置，再结合这个设置环境变量pcl1.8.0+vs2013环境配置（详细）_pcl:1.8.0 vs:2013 qt:5.9.0-CSDN博客 

 我对bat进行了修改，寻找lib文件，排除d.lib。旨在寻找release的lib

@echo off
(for %%I in (*.lib) do (
    echo %%I | findstr /i /c:"d.lib" >nul
    if errorlevel 1 echo %%I
)) >> release.txt

pause

我这边做了dll环境变量配置，但找不到dll,我就直接配置在项目的生成路径中了，然后就可以找到，不清楚啥原因，反正先学再说

测试代码

#include 
#include 
#include 
#include 
#include 
#include 
int user_data;

void
viewerOneOff(pcl::visualization::PCLVisualizer& viewer)
{
	viewer.setBackgroundColor(1.0, 0.5, 1.0);
	pcl::PointXYZ o;
	o.x = 1.0;
	o.y = 0;
	o.z = 0;
	viewer.addSphere(o, 0.25, "sphere", 0);
	std::cout << "i only run once" << std::endl;
}
void
viewerPsycho(pcl::visualization::PCLVisualizer& viewer)
{
	static unsigned count = 0;
	std::stringstream ss;
	ss << "Once per viewer loop: " << count++;
	viewer.removeShape("text", 0);
	viewer.addText(ss.str(), 200, 300, "text", 0);
	//FIXME: possible race condition here:
	user_data++;
}
int
main()
{
	pcl::PointCloud::Ptr cloud(new pcl::PointCloud);
	pcl::io::loadPCDFile("test_cloud.pcd", *cloud);
	pcl::visualization::CloudViewer viewer("Cloud Viewer");

	//blocks until the cloud is actually rendered
	viewer.showCloud(cloud);

	//use the following functions to get access to the underlying more advanced/powerful
	//PCLVisualizer

	//This will only get called once
	viewer.runOnVisualizationThreadOnce(viewerOneOff);

	//This will get called once per visualization iteration
	viewer.runOnVisualizationThread(viewerPsycho);

	while (!viewer.wasStopped())
	{
		std::cout << cloud->width << endl;
		std::cout << cloud->height << endl;
		//you can also do cool processing here
		//FIXME: Note that this is running in a separate thread from viewerPsycho
		//and you should guard against race conditions yourself...
		user_data++;
	}
	return 0;
}

 

2、三维凸包

用不严谨的话来讲，给定二维平面上的点集，凸包就是将最外层的点连接起来构成的凸多边形，它能包含点集中所有的点。

 

#include 
#include 
#include 
#include 
#include 
#include 

typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;
typedef CGAL::Polyhedron_3 Polyhedron_3;

int main() {
    // 加载三维PCD点云数据
    pcl::PointCloud::Ptr cloud(new pcl::PointCloud);
    if (pcl::io::loadPCDFile(R"(C:\chenqi\CGAL\MeshSimplification\data\chef.pcd)", *cloud) == -1) {
        PCL_ERROR("Could not read file\n");
        return -1;
    }

    // 转换为CGAL支持的格式
    std::vector points;
    for (const auto& point : cloud->points) {
        points.push_back(Kernel::Point_3(point.x, point.y, point.z));
    }

    // 计算三维凸包
    Polyhedron_3 poly;
    CGAL::convex_hull_3(points.begin(), points.end(), poly);

    // 输出凸包的顶点数量
    std::cout << poly.size_of_vertices() << " points on the convex hull" << std::endl;

    // 打开文件用于写入
    std::ofstream out_file(R"(C:\chenqi\CGAL\MeshSimplification\data\chef.xyz)");
    if (!out_file) {
        std::cerr << "Failed to open output file." << std::endl;
        return -1;
    }

    // 遍历Polyhedron_3中的每个顶点
    for (Polyhedron_3::Vertex_const_iterator it = poly.vertices_begin(); it != poly.vertices_end(); ++it) {
        // 获取当前顶点的坐标
        Kernel::Point_3 p = it->point();
        // 将顶点坐标写入文件
        out_file << p.x() << " " << p.y() << " " << p.z() << std::endl;
    }

    // 关闭文件
    out_file.close();

    std::cout << "Convex hull vertices saved to 'convex_hull_vertices.xyz'" << std::endl;

    return 0;
}

 

CGAL 二维点集的凸包提取_二维凸包提取-CSDN博客

CGAL 快速构建三维凸包_bcn三元凸包图-CSDN博客