点云滤波---投影滤波器

适用对象

适用于已知几何模型的点云滤波，根据几何模型的数学约束进行投影
例如一个球体通过3D扫描设备扫描之后，由于扫描精度的限制，引入了很多杂散点，这时已知实际球体的各个参数，可以用指定参数的球模型进行投影滤波，去除噪声。

工作原理

点云数据中的所有点 都用 向参数模型上投影之后的点代替。

PCL核心代码实现

  //使用ax+by+cz+d=0平面模型
  //Create a set of planar coefficients with a=b=d=0,c=1，即平面z=0
  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
  coefficients->values.resize (4);
  coefficients->values[0] = coefficients->values[1] = 0;
  coefficients->values[2] = 1.0;
  coefficients->values[3] = 0;

  // Create the filtering object
  pcl::ProjectInliers<pcl::PointXYZ> proj;			//创建投影滤波对象
  proj.setModelType (pcl::SACMODEL_PLANE);			//设置模型类型
  proj.setInputCloud (cloud);						//设置输入的点云
  proj.setModelCoefficients (coefficients);			//设置模型参数
  proj.filter (*cloud_projected);					//执行滤波

完整代码：

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/ModelCoefficients.h>
#include <pcl/filters/project_inliers.h>

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

  // Fill in the cloud data
  cloud->width  = 5;
  cloud->height = 1;
  cloud->points.resize (cloud->width * cloud->height);

  for (size_t i = 0; i < cloud->points.size (); ++i)
  {
    cloud->points[i].x = 1024 * rand () / (RAND_MAX + 1.0f);
    cloud->points[i].y = 1024 * rand () / (RAND_MAX + 1.0f);
    cloud->points[i].z = 1024 * rand () / (RAND_MAX + 1.0f);
  }

  std::cerr << "Cloud before projection: " << std::endl;
  for (size_t i = 0; i < cloud->points.size (); ++i)
    std::cerr << "    " << cloud->points[i].x << " " 
                        << cloud->points[i].y << " " 
                        << cloud->points[i].z << std::endl;

  // Create a set of planar coefficients with X=Y=0,Z=1
  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
  coefficients->values.resize (4);
  coefficients->values[0] = coefficients->values[1] = 0;
  coefficients->values[2] = 1.0;
  coefficients->values[3] = 0;

  // Create the filtering object
  pcl::ProjectInliers<pcl::PointXYZ> proj;
  proj.setModelType (pcl::SACMODEL_PLANE);
  proj.setInputCloud (cloud);
  proj.setModelCoefficients (coefficients);
  proj.filter (*cloud_projected);

  std::cerr << "Cloud after projection: " << std::endl;
  for (size_t i = 0; i < cloud_projected->points.size (); ++i)
    std::cerr << "    " << cloud_projected->points[i].x << " " 
                        << cloud_projected->points[i].y << " " 
                        << cloud_projected->points[i].z << std::endl;

  return (0);
}

参考资料

Projecting points using a parametric model