PCL_平面模型上构建凹（凸）多边形

步骤：

1. 滤波预处理，减小分割干扰；
2. 创建分割对象，获取平面模型参数；
3. 创建投影滤波对象，滤波点云投影到平面模型上，获取投影后点云；
4. 创建多边形投影对象，获取多边形边界上的点。

代码：

#include <pcl/ModelCoefficients.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/sample_consensus/method_types.h>
#include <pcl/sample_consensus/model_types.h>
#include <pcl/filters/passthrough.h>
#include <pcl/filters/project_inliers.h>
#include <pcl/segmentation/sac_segmentation.h>
#include <pcl/surface/concave_hull.h>

int
main (int argc, char** argv)
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>), 
                                      cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>), 
                                      cloud_projected (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PCDReader reader;

  reader.read ("table_scene_mug_stereo_textured.pcd", *cloud);
  // Build a filter to remove spurious NaNs
  pcl::PassThrough<pcl::PointXYZ> pass;
  pass.setInputCloud (cloud);
  pass.setFilterFieldName ("z");
  pass.setFilterLimits (0, 1.1);
  pass.filter (*cloud_filtered);
  std::cerr << "PointCloud after filtering has: "
            << cloud_filtered->points.size () << " data points." << std::endl;

  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
  pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
  // Create the segmentation object
  pcl::SACSegmentation<pcl::PointXYZ> seg;
  // Optional
  seg.setOptimizeCoefficients (true);
  // Mandatory
  seg.setModelType (pcl::SACMODEL_PLANE);
  seg.setMethodType (pcl::SAC_RANSAC);
  seg.setDistanceThreshold (0.01);

  seg.setInputCloud (cloud_filtered);
  seg.segment (*inliers, *coefficients);
  std::cerr << "PointCloud after segmentation has: "
            << inliers->indices.size () << " inliers." << std::endl;

  // Project the model inliers
  pcl::ProjectInliers<pcl::PointXYZ> proj;
  proj.setModelType (pcl::SACMODEL_PLANE);
  proj.setInputCloud (cloud_filtered);
  proj.setModelCoefficients (coefficients);
  proj.filter (*cloud_projected);
  std::cerr << "PointCloud after projection has: "
            << cloud_projected->points.size () << " data points." << std::endl;

  // Create a Concave Hull representation of the projected inliers
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_hull (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::ConcaveHull<pcl::PointXYZ> chull;
  chull.setInputCloud (cloud_projected);
  chull.setAlpha (0.1);
  chull.reconstruct (*cloud_hull);

  std::cerr << "Concave hull has: " << cloud_hull->points.size ()
            << " data points." << std::endl;

  pcl::PCDWriter writer;
  writer.write ("table_scene_mug_stereo_textured_hull.pcd", *cloud_hull, false);

  return (0);
}