3d激光雷达开发（法向量预测）

        法向量在3d点云当中扮演很重要的一个角色。一个三维数据点的特征，不仅和它自己有关，还和它周围的点有关。而法向量，正是基于这一点所提出来的特征属性。​

1、准备normal_estimation.cpp文件

#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/kdtree/kdtree_flann.h>
#include <pcl/features/normal_3d.h>
#include <pcl/surface/gp3.h>
#include <pcl/visualization/pcl_visualizer.h>

int main(int argc, char* argv[])
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);

  if (pcl::io::loadPCDFile<pcl::PointXYZ>(argv[1], *cloud) == -1)
  {
    PCL_ERROR("Could not read file\n");
    return -1;
  }

  pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> n;
  pcl::PointCloud<pcl::Normal>::Ptr normals(new pcl::PointCloud<pcl::Normal>);
  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZ>);
  tree->setInputCloud(cloud);
  n.setInputCloud(cloud);
  n.setSearchMethod(tree);
  n.setKSearch(20);
  n.compute(*normals);

  boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D viewer"));
  //viewer->initCameraParameters();

  int v1(0), v2(1), v3(2), v4(3);
  viewer->createViewPort(0.0, 0.0, 0.5, 0.5, v1);
  viewer->createViewPort(0.5, 0.0, 1.0, 0.5, v2);
  viewer->createViewPort(0.0, 0.5, 0.5, 1.0, v3);
  viewer->createViewPort(0.5, 0.5, 1.0, 1.0, v4);

  viewer->setBackgroundColor(5, 55, 10, v1);
  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> single_color(cloud, 0, 225, 0);

  viewer->addCoordinateSystem(0.5,"reference", v1);

  viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud", v1);
  viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud0", v2);
  viewer->addPointCloudNormals<pcl::PointXYZ, pcl::Normal>(cloud, normals, 50, 0.01, "normals", v2);
  viewer->addPointCloud<pcl::PointXYZ>(cloud, single_color, "sample cloud1", v3);
  viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud3", v4);

  viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 2, "sample cloud3", 4);

  while (!viewer->wasStopped())
  {
    viewer->spinOnce(100);
    boost::this_thread::sleep(boost::posix_time::microseconds(100000));
  }

  return 0;
}

2、准备CMakeLists.txt文件

cmake_minimum_required(VERSION 2.6 FATAL_ERROR)

project(normal_estimation)

find_package(PCL 1.2 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (normal_estimation normal_estimation.cpp)
target_link_libraries (normal_estimation ${PCL_LIBRARIES})

3、生成sln文件，准备编译

4、执行normal_estimation.exe文件

        注意执行的时候，需要添加pcd点云文件，比如normal_estimation.exe bunny.pcd，

        其中，右下角这副图片里面的兔子，看上去身上有很多的“刺”。这其实是对应的法向量数值，放大一点看，是这样的，