The Point Cloud Library (or PCL) is a large scale, open project  for 2D/3D image and point cloud processing. The PCL framework contains numerous state-of-the art algorithms including filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. These algorithms can be used, for example, to filter outliers from noisy data, stitch 3D point clouds together, segment relevant parts of a scene, extract keypoints and compute descriptors to recognize objects in the world based on their geometric appearance, and create surfaces from point clouds and visualize them -- to name a few.
PCL is released under the terms of the 3-clause BSD license and is open source software. It is free for commercial and research use.
PCL is cross-platform, and has been successfully compiled and deployed on Linux, MacOS, Windows, and Android/iOS. To simplify development, PCL is split into a series of smaller code libraries, that can be compiled separately. This modularity is important for distributing PCL on platforms with reduced computational or size constraints (for more information about each module see the documentation page). Another way to think about PCL is as a graph of code libraries, similar to the Boost set of C++ libraries.
1.11.012 May 2020 12:05
Bump version for release
Bump version for release.
ing duplication in API/ABI.
1.10.020 Jan 2020 11:45
Added pcl::make_shared and Class::Ptr/Class::ConstPtr type-aliases. Use these instead of direct names like boost, std ::shared_ptr or boost, std ::make_shared with PCL types.
Added pcl::shared_ptr that offers the same abstraction for non-PCL types.
1.9.103 Nov 2019 13:49