PCL1.8.1 Feature - VFH

Viewpoint Feature Histogram

VFH（视点特征直方图）描述子，可以应用在点云聚类识别和六自由度位姿估计问题。最终计算得到的VFH点云大小为1，即vfhs->points.size()=1.

http://www.pointclouds.org/documentation/tutorials/vfh_estimation.php#vfh

#include <pcl/point_types.h>
#include <pcl/features/vfh.h>

{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::Normal>::Ptr normals (new pcl::PointCloud<pcl::Normal> ());

  ... read, pass in or create a point cloud with normals ...
  ... (note: you can create a single PointCloud<PointNormal> if you want) ...

  // Create the VFH estimation class, and pass the input dataset+normals to it
  pcl::VFHEstimation<pcl::PointXYZ, pcl::Normal, pcl::VFHSignature308> vfh;
  vfh.setInputCloud (cloud);
  vfh.setInputNormals (normals);
  // alternatively, if cloud is of type PointNormal, do vfh.setInputNormals (cloud);

  // Create an empty kdtree representation, and pass it to the FPFH estimation object.
  // Its content will be filled inside the object, based on the given input dataset (as no other search surface is given).
  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ> ());
  vfh.setSearchMethod (tree);

  // Output datasets
  pcl::PointCloud<pcl::VFHSignature308>::Ptr vfhs (new pcl::PointCloud<pcl::VFHSignature308> ());

  // Compute the features
  vfh.compute (*vfhs);

  // vfhs->points.size () should be of size 1*
}