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pcl::filter::GaussianKernal_pcl::gaussiankernel

作者：小蓝xlanll | 2024-03-14 19:33:41

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pcl::gaussiankernel
//Create the input and filtered cloud objects
  pcl::PointCloud<pcl::PointXYZ>::Ptr inputcloud (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::PointXYZ>::Ptr outputcloud (new pcl::PointCloud<pcl::PointXYZ>);



  //Read in the input file
  if (pcl::io::loadPCDFile("SR4500LOG_pt0.pcd", *inputcloud) == -1) //* load the file
    {
      PCL_ERROR ("Couldn't read file test_pcd.pcd \n"); // if couldnt open the file ?
      return (-1);
    }



  //Set up the Gaussian Kernel
  pcl::filters::GaussianKernel<pcl::PointXYZ,pcl::PointXYZ>:: Ptr kernel (new pcl::filters::GaussianKernel<pcl::PointXYZ, pcl::PointXYZ>);
  (*kernel).setSigma(4);
  (*kernel).setThresholdRelativeToSigma(4);
  std::cout << "Kernel made" << std::endl;



  //Set up the KDTree
  pcl::search::KdTree<pcl::PointXYZ>::Ptr kdtree (new pcl::search::KdTree<pcl::PointXYZ>);
  (*kdtree).setInputCloud(inputcloud);
  std::cout << "KdTree made" << std::endl;



  //Set up the Convolution Filter
  pcl::filters::Convolution3D <pcl::PointXYZ, pcl::PointXYZ, pcl::filters::GaussianKernel<pcl::PointXYZ,pcl::PointXYZ> > convolution;
  convolution.setKernel(*kernel);
  convolution.setInputCloud(inputcloud);
  convolution.setSearchMethod(kdtree);
  convolution.setRadiusSearch(100);
  std::cout << "Convolution Start" << std::endl;
  convolution.convolve(*outputcloud);
  std::cout << "Convoluted" << std::endl;



  //write to file
  pcl::io::savePCDFileASCII ("smoothpallet.pcd", *outputcloud);

  std::cout << "Written to File" << std::endl;

转载：http://www.pcl-users.org/3D-Gaussian-Smoothing-td4030953.html



up vote 1 down vote favorite

I need help in applying a Gaussian Kernel on my points cloud to smooth the cloud.

I could not figure out how I should write the code and I could not find any plain examples.

Update:

I am using Point Cloud Library (pcl):

  1. pcl::io::loadPCDFile ("/home/..../2240.pcd", *raw_cloud);
  2. Eigen::VectorXf horizontal;
  3. //Set up the Gaussian Kernel
  4. pcl::GaussianKernel<pcl::PointXYZRGB> gaussianKernel;
  5. gaussianKernel.compute(5,horizontal,40);
  6.  
  7. pcl::filters::Convolution<pcl::PointXYZRGB> conv;
  8. conv.setInputCloud(raw_cloud);
  9. conv.setKernel(horizontal);

This is the code, it is not complete and I am not sure what if the approach is right?

anyone have an idea about this?

gaussian  convolution  point-cloud-library  kernel-density
share improve this question
 
 
You need to provide the code you tried and explain why it is that it's not doing what you need it to - including providing sample input and output. Refer to stackoverflow.com/help/mcve –  Nathaniel Ford  Jan 28 at 22:04

1 Answer

up vote 0 down vote accepted

I found the right way to make a Gaussian Smoothing via PCL:

  1. pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputCloud,cloud;
  2. pcl::filters::Convolution<pcl::PointXYZRGB, pcl::PointXYZRGB>  convolution;
  3. Eigen::ArrayXf gaussian_kernel(5);
  4. gaussian_kernel << 1.f/16, 1.f/4, 3.f/8, 1.f/4, 1.f/16;
  5. convolution.setBordersPolicy(
  6.                 pcl::filters::Convolution<pcl::PointXYZRGB, pcl::PointXYZRGB>::BORDERS_POLICY_IGNORE);
  7. convolution.setDistanceThreshold (static_cast<float> (0.1));
  8. convolution.setInputCloud (inputCloud);
  9. convolution.setKernel (gaussian_kernel);
  10. convolution.convolve(*cloud);

Hope it would help anyone in his work :)

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转载：http://stackoverflow.com/questions/35024359/pcl-gaussian-kernal-example
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