点云下采样和使用 PCL 进行正态估计

我正在研究下采样点云和正态估计。正常的估计对我很好，并且也进行了缩减采样;但是，当它们组合在一起时，它们不起作用，我收到这个： (核心倾倒(。下面是我的代码。感谢任何帮助？

pcl::PCLPointCloud2 pcl_pc2;
pcl::PointCloud<pcl::PointXYZ>::Ptr temp_cloud2(new    pcl::PointCloud<pcl::PointXYZ>);
pcl_conversions::toPCL(*input,pcl_pc2);
pcl::PointCloud<pcl::PointXYZ>::Ptr temp_cloud(new pcl::PointCloud<pcl::PointXYZ>);
pcl::fromPCLPointCloud2(pcl_pc2,*temp_cloud);
// Perform the actual filtering
pcl::VoxelGrid<pcl::PointXYZ> sor;
sor.setInputCloud (temp_cloud);
sor.setLeafSize (0.1f, 0.1f, 0.1f);
sor.filter (*temp_cloud2); 
//do stuff with temp_cloud here
pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> ne;
ne.setInputCloud (temp_cloud2);
// Create an empty kdtree representation, and pass it to the normal 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> ());
ne.setSearchMethod (tree);
// Output datasets
pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal>);
// Use all neighbors in a sphere of radius 3cm
ne.setRadiusSearch (0.03);
// Compute the features
ne.compute (*cloud_normals);