はじめにPCL(Point Cloud Library)を使うことになったが、点群とか扱うのは初めてでほとんどよくわかっていない。よって、Webにあるサンプルコードの読解を通して、少しずつPCL…
Point Cloud Library (PCL). Contribute to PointCloudLibrary/pcl development by creating an account on GitHub.
C++ (Cpp) PointCloud::size - 30 examples found. These are the top rated real world C++ (Cpp) examples of pcl::PointCloud::size extracted from open source projects. You can rate examples to help us improve the quality of examples.
Added new server app for point cloud streaming to mobile devices (pcl_openni_mobile_server) Added a new demo for the connected component segmentation. Includes a QT gui that allows various features to be toggled on/off. Added SHOT estimator wrapper using OMP Added openni_organized_multi_plane...
OrganizedNeighbor: add additional check to make sure the cloud is sui… [#5729] Modify FlannSearch to return Indices of Point Cloud (issue #5774) [#5780] Let setInputCloud of search methods indicate success or failure [#5840] libpcl_segmentation: ApproximateProgressiveMorphologicalFilter: check ...
Theregistrationlibrary implements a plethora of point cloud registration algorithms for both organized and unorganized (general purpose) datasets. For instance, PCL contains a set of powerful algorithms that allow the estimation of multiple sets of correspondences, as well as methods for rejecting bad ...
pcl::PointCloud<pcl::PointNormal>::Ptrcloud_normals(newpcl::PointCloud<pcl::PointNormal>); pcl::search::KdTree<pcl::PointXYZ>::Ptrtree_n(newpcl::search::KdTree<pcl::PointXYZ>()); ne.setInputCloud(cloud_xyz); ne.setSearchMethod(tree_n); ...
写在前面:本系列学习笔记的主要内容来自官方文档,PCL Documentation 应该是学习 PCL 最好的资料。通过笔记的形式,研读文档,总结概括,既加深理解、又备忘、还便于查阅,一举多得,何乐而不为。 Point Cloud Li…
Updated SupervoxelClustering to use the depth dependent transform by default only if the input cloud is organized; added a function to force use of the transform, and removed corresponding parameter from the constructor [#1115] Substituted hard-coded label point type with template parameter in Organ...
pcl::PointCloud<pcl::PointNormal>::Ptrcloud_normals(newpcl::PointCloud<pcl::PointNormal>); pcl::search::KdTree<pcl::PointXYZ>::Ptrtree_n(newpcl::search::KdTree<pcl::PointXYZ>()); ne.setInputCloud(cloud_xyz); ne.setSearchMethod(tree_n); ...