@article{
 title = {3D is here: Point Cloud Library (PCL)},
 type = {article},
 year = {2011},
 pages = {1-4},
 publisher = {IEEE},
 id = {5b9697e8-dacb-3136-8bb7-66025c39633b},
 created = {2023-06-23T09:19:58.498Z},
 file_attached = {true},
 profile_id = {ad172e55-c0e8-3aa4-8465-09fac4d5f5c8},
 group_id = {1ff583c0-be37-34fa-9c04-73c69437d354},
 last_modified = {2023-06-23T09:20:04.256Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {ab7b0cb1-7203-4b9c-9239-f9bdc3038cda},
 private_publication = {false},
 abstract = {With the advent of new, low-cost 3D sensing hardware such as the Kinect, and continued efforts in advanced point cloud processing, 3D perception gains more and more importance in robotics, as well as other fields. In this paper we present one of our most recent initiatives in the areas of point cloud perception: PCL (Point Cloud Library - http://pointclouds.org). PCL presents an advanced and extensive approach to the subject of 3D perception, and it's meant to provide support for all the common 3D building blocks that applications need. The library contains state-of-the art algorithms for: filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. PCL is supported by an international community of robotics and perception researchers. We provide a brief walkthrough of PCL including its algorithmic capabilities and implementation strategies. © 2011 IEEE.},
 bibtype = {article},
 author = {Rusu, Radu Bogdan and Cousins, Steve},
 doi = {10.1109/ICRA.2011.5980567},
 journal = {Proceedings - IEEE International Conference on Robotics and Automation}
}

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