Point Cloud Library (PCL)
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/** \mainpage PCL API Documentation
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<h1>Overview</h1>
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The <b>Point Cloud Library (PCL)</b> is a <b>large scale, open project</b>[1]
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for point cloud processing. The PCL framework contains numerous state-of-the
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art algorithms including filtering, feature estimation, surface reconstruction,
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registration, model fitting and segmentation. These algorithms can be used, for
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example, to filter outliers from noisy data, stitch 3D point clouds together,
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segment relevant parts of a scene, extract keypoints and compute descriptors to
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recognize objects in the world based on their geometric appearance, and create
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surfaces from point clouds and visualize them -- to name a few.
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PCL is released under the terms of the <a
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href="http://en.wikipedia.org/wiki/BSD_licenses#3-clause_license_.28.22New_BSD_License.22_or_.22Modified_BSD_License.22.29">
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BSD license</a> and is open source software. <b>It is free for commercial and
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research use.</b>
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\image html pointcloudlibrary_logo.png
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PCL is cross-platform, and has been successfully compiled and deployed on
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Linux, MacOS, Windows, and Android. To simplify development, PCL is split into
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a series of smaller code libraries, that can be compiled separately. This
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modularity is important for distributing PCL on platforms with reduced
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computational or size constraints.
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Please visit http://www.pointclouds.org for more information.
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<h1>Quick Links</h1>
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<ul>
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<li>Main Website: http://www.pointclouds.org</li>
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<li>GitHub Repository: https://github.com/PointCloudLibrary</li>
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<li>Continuous Integration: https://dev.azure.com/PointCloudLibrary/pcl/_build</li>
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<li>Changelog: https://pointcloudlibrary.github.io/documentation/changelog.html</li>
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</ul>
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<h1>References</h1>
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[1] For more information, including a scientific citation (more to be added soon), please see:
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<pre>
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@@InProceedings{Rusu_ICRA2011_PCL,
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author = {Radu Bogdan Rusu and Steve Cousins},
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title = {{3D is here: Point Cloud Library (PCL)}},
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booktitle = {{IEEE International Conference on Robotics and Automation (ICRA)}},
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month = {May 9-13},
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year = {2011},
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address = {Shanghai, China},
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publisher = {IEEE}
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}
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</pre>
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<a href="http://www.pointclouds.org/assets/pdf/pcl_icra2011.pdf">Download PDF here</a>.
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If you are referencing PCL in your work, please do <a
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href="http://www.pointclouds.org/contact.html">contact us</a>. We're trying to
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gather a list of publications that use PCL, and present it here. That will give
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your work visibility, and it would help us understand what parts of PCL should
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we be working on. Thank you.
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*/