The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use.
Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available at https://github.com/PointCloudLibrary/pcl/wiki.
Getting Started
To simplify both usage and development, we split PCL into a series of modular libraries. The most important set of released modules in PCL is shown below.
| filters | features | keypoints |
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| registration | kdtree | octree |
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| segmentation | sample_consensus | surface |
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| recognition | io | visualization |
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Tutorials
Our comprehensive list of tutorials for PCL, covers many topics, ranging from simple Point Cloud Input/Output operations to more complicated applications that include visualization, feature estimation, segmentation, etc.
Advanced Topics
If you’re interested in how PCL works internally, or are looking at optimizing your workflow, we have assembled a set of topics that cover interesting subjects from reducing your compile time to code profiling.
API Reference
The Application Programming Interface (API) documentation for PCL includes explanations about how each public method and class works, shows simple code snippets that can be used quickly to prototype and test a particular algorithm, and links to scientific publications for those interested in finding out more about the theoretical aspects of a particular method.