连接两个点云中的字段或数据形成新点云以及Opennni Grabber初识

#include <iostream>
#include <pcl/io/pcd_io.h>      //io模块 
#include <pcl/point_types.h>   //数据类型

int main (int argc, char** argv)
{  if (argc != 2) //提示如果执行可执行文件输入两个参数 -f 或者-p  {
   std::cerr << "please specify command line arg '-f' or '-p'" << std::endl;
   exit(0);
 }  //申明三个pcl::PointXYZ点云数据类型，分别为cloud_a, cloud_b, cloud_c
pcl::PointCloud<pcl::PointXYZ> cloud_a, cloud_b, cloud_c;  //存储进行连接时需要的Normal点云,Normal (float n_x, float n_y, float n_z)
pcl::PointCloud<pcl::Normal> n_cloud_b;   //存储连接XYZ与normal后的点云
pcl::PointCloud<pcl::PointNormal> p_n_cloud_c;  // 创建点云数据  //设置cloud_a的个数为5
cloud_a.width  = 5;
 cloud_a.height = cloud_b.height = n_cloud_b.height = 1; //设置都为无序点云
cloud_a.points.resize (cloud_a.width * cloud_a.height); //总数
if (strcmp(argv[1], "-p") == 0)   //判断是否为连接a+b=c(点云连接)  {
   cloud_b.width  = 3;
   cloud_b.points.resize (cloud_b.width * cloud_b.height);
 }  else{
   n_cloud_b.width = 5; //如果是连接XYZ与normal则生成5个法线（字段间连接）
n_cloud_b.points.resize (n_cloud_b.width * n_cloud_b.height);
 }//以下循环生成无序点云填充上面定义的两种类型的点云数据
for (size_t i = 0; i < cloud_a.points.size (); ++i)
 {  //cloud_a产生三个点（每个点都有X Y Z 三个随机填充的值）
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)
   {   //如果连接a+b=c，则cloud_b用三个点作为xyz的数据
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
for (size_t i = 0; i < n_cloud_b.points.size (); ++i)
   {  //如果连接xyz+normal=xyznormal则n_cloud_b用5个点作为normal数据
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);
   }/*******************************************************************
定义了连接点云会用到的5个点云对象：3个输入（cloud_a cloud_b 和n_cloud_b）
两个输出（cloud_c  n_cloud_c）然后就是为两个输入点云cloud_a和 cloud_b或者cloud_a 和n_cloud_b填充数据  
***************///输出Cloud A
std::cerr << "Cloud A: " << std::endl;  for (size_t i = 0; i < cloud_a.points.size (); ++i)
   std::cerr << "    " << cloud_a.points[i].x << " " << cloud_a.points[i].y << " " << cloud_a.points[i].z << std::endl;//输出Cloud B
std::cerr << "Cloud B: " << std::endl;  if (strcmp(argv[1], "-p") == 0)    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//输出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;  // Copy the point cloud data
if (strcmp(argv[1], "-p") == 0)
 {
   cloud_c  = cloud_a;
   cloud_c += cloud_b;//把cloud_a和cloud_b连接一起创建cloud_c  后输出
std::cerr << "Cloud C: " << std::endl;    for (size_t i = 0; i < cloud_c.points.size (); ++i)
     std::cerr << "    " << cloud_c.points[i].x << " " << cloud_c.points[i].y << " " << cloud_c.points[i].z << " " << std::endl;
 }  else
 {  //连接字段  把cloud_a和 n_cloud_b字段连接 一起创建 p_n_cloud_c)    pcl::concatenateFields (cloud_a, n_cloud_b, p_n_cloud_c);
   std::cerr << "Cloud C: " << std::endl;    for (size_t i = 0; i < p_n_cloud_c.points.size (); ++i)
     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);
}

cmake_minimum_required(VERSION 2.8 FATAL_ERROR)project(ch2_2)find_package(PCL 1.2 REQUIRED)include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})add_executable (concatenate_clouds concatenate_clouds.cpp)
target_link_libraries (concatenate_clouds ${PCL_LIBRARIES})

#include <pcl/point_cloud.h>   //点云类定义头文件
#include <pcl/point_types.h>    //点 类型定义头文件
#include <pcl/io/openni_grabber.h>  //OpenNI数据流获取头文件
#include <pcl/common/time.h>         //时间头文件
//类SimpleOpenNIProcessor  的回调函数，作为在获取数据时，对数据进行处理的回调函数的封装，在本例中并没有什么处理，只是实时的在标准输出设备打印处信息。

class SimpleOpenNIProcessor
{public:  void cloud_cb_ (const pcl::PointCloud<pcl::PointXYZRGBA>::ConstPtr &cloud)
 {    static unsigned count = 0;   
       static double last = pcl::getTime ();  //获取当前时间
if (++count == 30)      //每30ms一次输出    {            double now = pcl::getTime ();      //  >>右移
std::cout << "distance of center pixel :" << cloud->points [(cloud->width >> 1) * (cloud->height + 1)].z << " mm. Average framerate: " << double(count)/double(now - last) << " Hz" <<  std::endl;
     count = 0;
     last = now;
   }
 }  
 void run ()
 {
   pcl::Grabber* interface = new pcl::OpenNIGrabber();  //创建OpenNI采集对象    // 定义回调函数
boost::function<void (const pcl::PointCloud<pcl::PointXYZRGBA>::ConstPtr&)> f =
     boost::bind (&SimpleOpenNIProcessor::cloud_cb_, this, _1);
   boost::signals2::connection c = interface->registerCallback (f);//注册回调函数
interface->start ();   //开始接受点云数据     //直到用户按下Ctrl -c
while (true)
     boost::this_thread::sleep (boost::posix_time::seconds (1));    //   停止采集
interface->stop ();
 }
};int main ()
{
 SimpleOpenNIProcessor v;
 v.run ();  return (0);
}

cmake_minimum_required(VERSION 2.8 FATAL_ERROR)
project(openni_grabber)
find_package(PCL 1.2 REQUIRED)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
add_executable (openni_grabber openni_grabber.cpp)
target_link_libraries (openni_grabber ${PCL_LIBRARIES})