点云视窗类CloudViewer和PCLVisualizer

版权声明：本文为博主原创文章，未经博主允许不得转载。 https://blog.csdn.net/chuquanchang1051/article/details/79192651

(1)pcl CloudViewer
点云视窗类CloudViewer是简单显示点云的可视化工具类，可以让用户用尽可能少的代码查看点云。注意：点云视窗类不能应用于多线程应用程序中。
简单点云可视化
如果用户想用几行代码可视化程序中所对应的地物，可以使用下面的代码：

#include <pcl/visualization/cloud_viewer.h>
//...
void
foo ()
 {
   pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud;
//... 为cloud添加对应的场景
pcl::visualization::CloudViewer viewer ("Simple Cloud Viewer");
   viewer.showCloud (cloud);
while (!viewer.wasStopped ())
   {
   }
 }

#include <pcl/visualization/cloud_viewer.h>
#include <iostream>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
int user_data;
void viewerOneOff(pcl::visualization::PCLVisualizer& viewer)
{
    viewer.setBackgroundColor(1.0, 0.5, 1.0);//设置背景颜色
    pcl::PointXYZ o;//存储球的圆心位置
    o.x = 1.0;
    o.y = 0;
    o.z = 0;
    viewer.addSphere(o, 0.25, "sphere", 0);//添加圆球几何对象
    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<pcl::PointXYZRGBA>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGBA>);
    pcl::io::loadPCDFile("example.pcd的位置", *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())
    {
        //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;
}

pcl_viewr几个常用的命令：
r键: 重现视角。如果读入文件没有在主窗口显示，不妨按下键盘的r键一试。
j键：截图功能。
g键：显示/隐藏 坐标轴。
鼠标：左键，使图像绕自身旋转; 滚轮, 按住滚轮不松，可移动图像，滚动滚轮，可放大/缩小 图像; 右键,“原地” 放大/缩小。
-/+：-（减号）可缩小点; +(加号)，可放大点。
pcl_viewe -bc r,g,b /path/to/.pcd:可改变背景色.
pcl_viewer还可以用来直接显示pfh，fpfh（fast point feature histogram），vfh等直方图。
常用的pcl_viewer 好像就这些，其他未涉及到的功能可通过pcl_viewer /path/.pcd 打开图像，按键盘h（获取帮助）的方式获得.
(2)PCLVisualizer
PCLVisualizer是PCL的全功能可视化类。虽然使用比CloudViewer更复杂，但功能更强大，可提供显示法线，绘图形状和多个视口等功能。
代码一直编译出错，先跳过此段内容，看接下来的内容。
////////////////********2018.5.18号重新看终于看懂***********////

#include <iostream>  
#include <boost/thread/thread.hpp>  
#include <pcl/common/common_headers.h>  
#include <pcl/common/common_headers.h>  
#include <pcl/features/normal_3d.h>  
#include <pcl/io/pcd_io.h>  
#include <pcl/visualization/pcl_visualizer.h>  
#include <pcl/console/parse.h>  
// 帮助  
void
printUsage(const char* progName)
{
    std::cout << "\n\nUsage: " << progName << " [options]\n\n"
        << "Options:\n"
        << "-------------------------------------------\n"
        << "-h           this help\n"
        << "-s           Simple visualisation example\n"
        << "-r           RGB colour visualisation example\n"
        << "-c           Custom colour visualisation example\n"
        << "-n           Normals visualisation example\n"
        << "-a           Shapes visualisation example\n"
        << "-v           Viewports example\n"
        << "-i           Interaction Customization example\n"
        << "\n\n";
}

//Simple visualisation example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> simpleVis(pcl::PointCloud<pcl::PointXYZ>::ConstPtr cloud)
{
    //创建3D窗口并添加点云  
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->setBackgroundColor(0, 0, 0);
    viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud");
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "sample cloud");
    viewer->addCoordinateSystem(1.0);
    viewer->initCameraParameters();
    return (viewer);
}

//RGB colour visualisation example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> rgbVis(pcl::PointCloud<pcl::PointXYZRGB>::ConstPtr cloud)
{
    //创建3D窗口并添加点云   
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->setBackgroundColor(0, 0, 0);
    pcl::visualization::PointCloudColorHandlerRGBField<pcl::PointXYZRGB> rgb(cloud);
    viewer->addPointCloud<pcl::PointXYZRGB>(cloud, rgb, "sample cloud");
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud");
    viewer->addCoordinateSystem(1.0);
    viewer->initCameraParameters();
    return (viewer);
}

//Custom colour visualisation example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> customColourVis(pcl::PointCloud<pcl::PointXYZ>::ConstPtr cloud)
{
    //创建3D窗口并添加点云  
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->setBackgroundColor(0, 0, 0);
    pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> single_color(cloud, 0, 255, 0);
    viewer->addPointCloud<pcl::PointXYZ>(cloud, single_color, "sample cloud");
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud");
    viewer->addCoordinateSystem(1.0);
    viewer->initCameraParameters();
    return (viewer);
}

//Normals visualisation example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> normalsVis(
    pcl::PointCloud<pcl::PointXYZRGB>::ConstPtr cloud, pcl::PointCloud<pcl::Normal>::ConstPtr normals)
{
    //创建3D窗口并添加点云其包括法线    
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->setBackgroundColor(0, 0, 0);
    pcl::visualization::PointCloudColorHandlerRGBField<pcl::PointXYZRGB> rgb(cloud);
    viewer->addPointCloud<pcl::PointXYZRGB>(cloud, rgb, "sample cloud");
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud");
    viewer->addPointCloudNormals<pcl::PointXYZRGB, pcl::Normal>(cloud, normals, 10, 0.05, "normals");
    viewer->addCoordinateSystem(1.0);
    viewer->initCameraParameters();
    return (viewer);
}

//Shapes visualisation example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> shapesVis(pcl::PointCloud<pcl::PointXYZRGB>::ConstPtr cloud)
{
    //创建3D窗口并添加点云      
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->setBackgroundColor(0, 0, 0);
    pcl::visualization::PointCloudColorHandlerRGBField<pcl::PointXYZRGB> rgb(cloud);
    viewer->addPointCloud<pcl::PointXYZRGB>(cloud, rgb, "sample cloud");
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud");
    viewer->addCoordinateSystem(1.0);
    viewer->initCameraParameters();
    //在点云上添加直线和球体模型  
    viewer->addLine<pcl::PointXYZRGB>(cloud->points[0],
        cloud->points[cloud->size() - 1], "line");
    viewer->addSphere(cloud->points[0], 0.2, 0.5, 0.5, 0.0, "sphere");
    //在其他位置添加基于模型参数的平面及圆锥体  
    pcl::ModelCoefficients coeffs;
    coeffs.values.push_back(0.0);
    coeffs.values.push_back(0.0);
    coeffs.values.push_back(1.0);
    coeffs.values.push_back(0.0);
    viewer->addPlane(coeffs, "plane");
    coeffs.values.clear();
    coeffs.values.push_back(0.3);
    coeffs.values.push_back(0.3);
    coeffs.values.push_back(0.0);
    coeffs.values.push_back(0.0);
    coeffs.values.push_back(1.0);
    coeffs.values.push_back(0.0);
    coeffs.values.push_back(5.0);
    viewer->addCone(coeffs, "cone");

    return (viewer);
}

//Viewports example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> viewportsVis(
    pcl::PointCloud<pcl::PointXYZRGB>::ConstPtr cloud, pcl::PointCloud<pcl::Normal>::ConstPtr normals1, pcl::PointCloud<pcl::Normal>::ConstPtr normals2)
{
    // 创建3D窗口并添加显示点云其包括法线  
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->initCameraParameters();
    int v1(0);
    viewer->createViewPort(0.0, 0.0, 0.5, 1.0, v1);
    viewer->setBackgroundColor(0, 0, 0, v1);
    viewer->addText("Radius: 0.01", 10, 10, "v1 text", v1);
    pcl::visualization::PointCloudColorHandlerRGBField<pcl::PointXYZRGB> rgb(cloud);
    viewer->addPointCloud<pcl::PointXYZRGB>(cloud, rgb, "sample cloud1", v1);
    int v2(0);
    viewer->createViewPort(0.5, 0.0, 1.0, 1.0, v2);
    viewer->setBackgroundColor(0.3, 0.3, 0.3, v2);
    viewer->addText("Radius: 0.1", 10, 10, "v2 text", v2);
    pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZRGB> single_color(cloud, 0, 255, 0);
    viewer->addPointCloud<pcl::PointXYZRGB>(cloud, single_color, "sample cloud2", v2);
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud1");
    viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud2");
    viewer->addCoordinateSystem(1.0);

    viewer->addPointCloudNormals<pcl::PointXYZRGB, pcl::Normal>(cloud, normals1, 10, 0.05, "normals1", v1);
    viewer->addPointCloudNormals<pcl::PointXYZRGB, pcl::Normal>(cloud, normals2, 10, 0.05, "normals2", v2);

    return (viewer);
}


unsigned int text_id = 0;
void keyboardEventOccurred(const pcl::visualization::KeyboardEvent &event,
    void* viewer_void)
{
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer = *static_cast<boost::shared_ptr<pcl::visualization::PCLVisualizer> *> (viewer_void);
    if (event.getKeySym() == "r" && event.keyDown())
    {
        std::cout << "r was pressed => removing all text" << std::endl;

        char str[512];
        for (unsigned int i = 0; i < text_id; ++i)
        {
            sprintf(str, "text#%03d", i);
            viewer->removeShape(str);
        }
        text_id = 0;
    }
}

void mouseEventOccurred(const pcl::visualization::MouseEvent &event,
    void* viewer_void)
{
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer = *static_cast<boost::shared_ptr<pcl::visualization::PCLVisualizer> *> (viewer_void);
    if (event.getButton() == pcl::visualization::MouseEvent::LeftButton &&
        event.getType() == pcl::visualization::MouseEvent::MouseButtonRelease)
    {
        std::cout << "Left mouse button released at position (" << event.getX() << ", " << event.getY() << ")" << std::endl;

        char str[512];
        sprintf(str, "text#%03d", text_id++);
        viewer->addText("clicked here", event.getX(), event.getY(), str);
    }
}

//Interaction Customization example  
boost::shared_ptr<pcl::visualization::PCLVisualizer> interactionCustomizationVis()
{
    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
    viewer->setBackgroundColor(0, 0, 0);
    viewer->addCoordinateSystem(1.0);

    viewer->registerKeyboardCallback(keyboardEventOccurred, (void*)&viewer);
    viewer->registerMouseCallback(mouseEventOccurred, (void*)&viewer);

    return (viewer);
}
// -----Main-----  
int
main(int argc, char** argv)
{
    // 解析命令行参数  
    if (pcl::console::find_argument(argc, argv, "-h") >= 0)
    {
        printUsage(argv[0]);
        return 0;
    }
    bool simple(false), rgb(false), custom_c(false), normals(false),
        shapes(false), viewports(false), interaction_customization(false);
    if (pcl::console::find_argument(argc, argv, "-s") >= 0)
    {
        simple = true;
        std::cout << "Simple visualisation example\n";
    }
    else if (pcl::console::find_argument(argc, argv, "-c") >= 0)
    {
        custom_c = true;
        std::cout << "Custom colour visualisation example\n";
    }
    else if (pcl::console::find_argument(argc, argv, "-r") >= 0)
    {
        rgb = true;
        std::cout << "RGB colour visualisation example\n";
    }
    else if (pcl::console::find_argument(argc, argv, "-n") >= 0)
    {
        normals = true;
        std::cout << "Normals visualisation example\n";
    }
    else if (pcl::console::find_argument(argc, argv, "-a") >= 0)
    {
        shapes = true;
        std::cout << "Shapes visualisation example\n";
    }
    else if (pcl::console::find_argument(argc, argv, "-v") >= 0)
    {
        viewports = true;
        std::cout << "Viewports example\n";
    }
    else if (pcl::console::find_argument(argc, argv, "-i") >= 0)
    {
        interaction_customization = true;
        std::cout << "Interaction Customization example\n";
    }
    else
    {
        printUsage(argv[0]);
        return 0;
    }
    // 自行创建一随机点云  
    pcl::PointCloud<pcl::PointXYZ>::Ptr basic_cloud_ptr(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZRGB>::Ptr point_cloud_ptr(new pcl::PointCloud<pcl::PointXYZRGB>);
    std::cout << "Genarating example point clouds.\n\n";
    // 以椭圆为边线沿z轴拉伸获取其点云，并赋予红绿蓝渐变色。  
    uint8_t r(255), g(15), b(15);
    for (float z(-1.0); z <= 1.0; z += 0.05)
    {
        for (float angle(0.0); angle <= 360.0; angle += 5.0)
        {
            pcl::PointXYZ basic_point;
            basic_point.x = 0.5 * cosf(pcl::deg2rad(angle));
            basic_point.y = sinf(pcl::deg2rad(angle));
            basic_point.z = z;
            basic_cloud_ptr->points.push_back(basic_point);

            pcl::PointXYZRGB point;
            point.x = basic_point.x;
            point.y = basic_point.y;
            point.z = basic_point.z;
            uint32_t rgb = (static_cast<uint32_t>(r) << 16 |
                static_cast<uint32_t>(g) << 8 | static_cast<uint32_t>(b));
            point.rgb = *reinterpret_cast<float*>(&rgb);
            point_cloud_ptr->points.push_back(point);
        }
        if (z < 0.0)
        {
            r -= 12;
            g += 12;
        }
        else
        {
            g -= 12;
            b += 12;
        }
    }
    basic_cloud_ptr->width = (int)basic_cloud_ptr->points.size();
    basic_cloud_ptr->height = 1;
    point_cloud_ptr->width = (int)point_cloud_ptr->points.size();
    point_cloud_ptr->height = 1;
    // 0.05为搜索半径获取点云法线  
    pcl::NormalEstimation<pcl::PointXYZRGB, pcl::Normal> ne;
    ne.setInputCloud(point_cloud_ptr);
    pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZRGB>());
    ne.setSearchMethod(tree);
    pcl::PointCloud<pcl::Normal>::Ptr cloud_normals1(new pcl::PointCloud<pcl::Normal>);
    ne.setRadiusSearch(0.05);
    ne.compute(*cloud_normals1);
    //  0.1为搜索半径获取点云法线  
    pcl::PointCloud<pcl::Normal>::Ptr cloud_normals2(new pcl::PointCloud<pcl::Normal>);
    ne.setRadiusSearch(0.1);
    ne.compute(*cloud_normals2);

    boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer;
    if (simple)
    {
        viewer = simpleVis(basic_cloud_ptr);
    }
    else if (rgb)
    {
        viewer = rgbVis(point_cloud_ptr);
    }
    else if (custom_c)
    {
        viewer = customColourVis(basic_cloud_ptr);
    }
    else if (normals)
    {
        viewer = normalsVis(point_cloud_ptr, cloud_normals2);
    }
    else if (shapes)
    {
        viewer = shapesVis(point_cloud_ptr);
    }
    else if (viewports)
    {
        viewer = viewportsVis(point_cloud_ptr, cloud_normals1, cloud_normals2);
    }
    else if (interaction_customization)
    {
        viewer = interactionCustomizationVis();
    }
    // 主循环  
    while (!viewer->wasStopped())
    {
        viewer->spinOnce(100);
        boost::this_thread::sleep(boost::posix_time::microseconds(100000));
    }
}

window 下vs2013编译：
调试运行：
F5或者Ctrl+F5是没有作用的，需要在控制台中运行
1）Win+r，确定，进入控制台
2）输入：cd /d D:D:\VS2013 project\Project15\x64\Debug（程序放在哪个文件夹下就输入哪个文件夹）
3）输入：Project.exe -s
运行结果：

可以观察第一个例程，其他的例子操作类似。
参考博客
(https://blog.csdn.net/fandq1223/article/details/53186244)
（3）Concatenate the points of two Point Clouds
In this tutorial we will learn how to concatenating the points of two different point clouds. The constraint imposed here is that the type and number of fields in the two datasets has to be equal. We will also learn how to concatenate the fields (e.g., dimensions) of two different point clouds. The constraint imposed here is that the number of points in the two datasets has to be equal.

• 如何拼接两个不同的点云的点，约束条件是两个数据集中的域的数量和类型必须相等。* 如何拼接两个不同点云的域，约束条件是连个数据集中的点的数量必须相等。

#include <iostream> //标准输入输出流
#include <pcl/io/pcd_io.h> //PCL的PCD格式文件的输入输出头文件
#include <pcl/point_types.h> //PCL对各种格式的点的支持头文件
// 程序拼接A和B到C
int main (int argc, char** argv)
{
  if (argc != 2) // 需要一个参数 -f 或 -p
  {
    std::cerr << "please specify command line arg '-f' or '-p'" << std::endl;
    exit(0);
  }
    // 用于拼接不同点云的点的变量
  pcl::PointCloud<pcl::PointXYZ> cloud_a, cloud_b, cloud_c; //创建点云（不是指针），存储点坐标xyz
    // 用于拼接不同点云的域（点和法向量）的变量
  pcl::PointCloud<pcl::Normal> n_cloud_b; //创建点云，储存法向量
  pcl::PointCloud<pcl::PointNormal> p_n_cloud_c; //创建点云，储存点坐标和法向量

  //填充点云数据
  cloud_a.width  = 5; //设置宽度
  cloud_a.height = cloud_b.height = n_cloud_b.height = 1; //设置高度
  cloud_a.points.resize (cloud_a.width * cloud_a.height); //变形，无序
  if (strcmp(argv[1], "-p") == 0) //根据输入参数，设置点云
  {
    cloud_b.width  = 3; //cloud_b用于拼接不同点云的点
    cloud_b.points.resize (cloud_b.width * cloud_b.height);
  }
  else{
    n_cloud_b.width = 5; //n_cloud_b用于拼接不同点云的域
    n_cloud_b.points.resize (n_cloud_b.width * n_cloud_b.height);
  }
  for (size_t i = 0; i < cloud_a.points.size (); ++i) //设置cloud_a中点的坐标（随机数）
  {
    cloud_a.points[i].x = 1024 * rand () / (RAND_MAX + 1.0f);
    cloud_a.points[i].y = 1024 * rand () / (RAND_MAX + 1.0f);
    cloud_a.points[i].z = 1024 * rand () / (RAND_MAX + 1.0f);
  }
  if (strcmp(argv[1], "-p") == 0)
    for (size_t i = 0; i < cloud_b.points.size (); ++i) //设置cloud_b中点的坐标（随机数）
    {
      cloud_b.points[i].x = 1024 * rand () / (RAND_MAX + 1.0f);
      cloud_b.points[i].y = 1024 * rand () / (RAND_MAX + 1.0f);
      cloud_b.points[i].z = 1024 * rand () / (RAND_MAX + 1.0f);
    }
  else // -f
    for (size_t i = 0; i < n_cloud_b.points.size (); ++i) //设置n_cloud_b中点的坐标（随机数）
    {
      n_cloud_b.points[i].normal[0] = 1024 * rand () / (RAND_MAX + 1.0f);
      n_cloud_b.points[i].normal[1] = 1024 * rand () / (RAND_MAX + 1.0f);
      n_cloud_b.points[i].normal[2] = 1024 * rand () / (RAND_MAX + 1.0f);
    }

    // 打印拼接用的数据 A和B
  std::cerr << "Cloud A: " << std::endl;
  for (size_t i = 0; i < cloud_a.points.size (); ++i) //打印cloud_a的点坐标信息
    std::cerr << "    " << cloud_a.points[i].x << " " << cloud_a.points[i].y << " " << cloud_a.points[i].z << std::endl;

  std::cerr << "Cloud B: " << std::endl; //打印Cloud B
  if (strcmp(argv[1], "-p") == 0) //若输入参数是-p，打印cloud_b；
    for (size_t i = 0; i < cloud_b.points.size (); ++i)
      std::cerr << "    " << cloud_b.points[i].x << " " << cloud_b.points[i].y << " " << cloud_b.points[i].z << std::endl;
  else //若-f，打印n_cloud_b
    for (size_t i = 0; i < n_cloud_b.points.size (); ++i)
      std::cerr << "    " << n_cloud_b.points[i].normal[0] << " " << n_cloud_b.points[i].normal[1] << " " << n_cloud_b.points[i].normal[2] << std::endl;

  //复制点云中的点
  if (strcmp(argv[1], "-p") == 0)
  {
    cloud_c  = cloud_a;
    cloud_c += cloud_b; // cloud_a + cloud_b 意思是cloud_c包含了a和b中的点，c的点数 = a的点数+b的点数
    std::cerr << "Cloud C: " << std::endl; ////打印Cloud C
    for (size_t i = 0; i < cloud_c.points.size (); ++i) //打印Cloud C
      std::cerr << "    " << cloud_c.points[i].x << " " << cloud_c.points[i].y << " " << cloud_c.points[i].z << " " << std::endl;
  }
  else //若输入参数是-f
  {
    pcl::concatenateFields (cloud_a, n_cloud_b, p_n_cloud_c); //拼接（点）cloud_a和（法向量）n_cloud_b到p_n_cloud_c
    std::cerr << "Cloud C: " << std::endl;
    for (size_t i = 0; i < p_n_cloud_c.points.size (); ++i) //打印Cloud C
      std::cerr << "    " <<
        p_n_cloud_c.points[i].x << " " << p_n_cloud_c.points[i].y << " " << p_n_cloud_c.points[i].z << " " <<
        p_n_cloud_c.points[i].normal[0] << " " << p_n_cloud_c.points[i].normal[1] << " " << p_n_cloud_c.points[i].normal[2] << std::endl;
  }

  return (0);
}

编译一下，生成解决方案，然后打开cmd窗口，跳转到该项目的debug目录下，输入命令，addclouds.exe -p，执行拼接不同点云的点，结果如下图所示。

在cmd窗口输入addclouds.exe -f,执行拼接不同点云的域（比如点和法向量），结果如下图

参考：
(http://blog.csdn.net/xuezhisdc/article/details/51014388)
非常感谢这篇博客教我如何编译得到效果