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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.
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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Our [comprehensive list of tutorials for PCL][tutorials], covers many topics, ranging from simple Point Cloud Input/Output operations to more complicated applications that include visualization, feature estimation, segmentation, etc.
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][tutorials]
If you're interested in how PCL works internally, or are looking at optimizing your workflow, we have assembled a [set of topics][tutorials] that cover interesting subjects from reducing your compile time to code profiling.
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The [Application Programming Interface (API) documentation][api] 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.
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