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| author | Nikolay Nikolov <nikobnikolov[at]gmail[dot]com> | 2017-01-14 18:31:29 +0700 |
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| committer | Willy Sudiarto Raharjo <willysr@slackbuilds.org> | 2017-01-14 18:32:12 +0700 |
| commit | 58b660366a64e5081b99df1f68beb687581eb767 (patch) | |
| tree | 4418238eb2af53e4e0d490ccdce431aa16a92f91 /libraries/pcl/README | |
| parent | 61b9a42bad44e6d274c7fcf0736304dd6bb70fc5 (diff) | |
| download | slackbuilds-58b660366a64e5081b99df1f68beb687581eb767.tar.gz | |
libraries/pcl: Added (2D/3D image library).
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
Diffstat (limited to 'libraries/pcl/README')
| -rw-r--r-- | libraries/pcl/README | 9 |
1 files changed, 9 insertions, 0 deletions
diff --git a/libraries/pcl/README b/libraries/pcl/README new file mode 100644 index 0000000000..09c79c9e8b --- /dev/null +++ b/libraries/pcl/README @@ -0,0 +1,9 @@ +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. |