Usage of Eigen library with PCL PointCloud (PCL uses Eigen::Matrix as its representation for point clouds under the hood )

eigen_ransac.cpp

template<typename PointT>
std::pair<typename pcl::PointCloud<PointT>::Ptr, typename pcl::PointCloud<PointT>::Ptr>
ProcessPointClouds<PointT>::SegmentPlane( typename pcl::PointCloud<PointT>::Ptr cloud, int maxIterations, float distanceThreshold) {

  // Time segmentation process
  auto startTime = std::chrono::steady_clock::now();

  // downsample input point cloud
  auto cloud_ds = DownSample(cloud, 1.0);

  // convert point cloud into a 3xN float matrix
  Eigen::Matrix3Xf cloud_matrix = cloud_ds->getMatrixXfMap(3,4,0);

  // print cloud point matrix shape
  std::cout << "cloud_matrix.rows(): " << cloud_matrix.rows() << std::endl;
  std::cout << "cloud_matrix.cols(): " << cloud_matrix.cols() << std::endl;
  
  // generate 100 triplets of indices
  const int size = cloud_matrix.cols();
  Eigen::Matrix<int,3,100> m = Eigen::Matrix<int,3,100>::Random().array().abs().unaryExpr([size](int x){ return x % size; });
  
  /* ... */
  
  auto endTime = std::chrono::steady_clock::now();
  auto elapsedTime = std::chrono::duration_cast<std::chrono::milliseconds>(endTime - startTime);
  std::cout << "plane segmentation took " << elapsedTime.count() << " milliseconds" << std::endl;
  
  return segResult;
}