== Package Summary ==
PCL - Point Cloud Library: a comprehensive open source library for n-D Point Clouds and 3D geometry processing. The library contains numerous state-of-the art algorithms for: filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation, etc.

{{{#!wiki red/solid
This is the '''unstable''' package! The used namespace is '''pcl17'''.
}}}
 * License: BSD
 * External website: http://pointclouds.org
 * Source: git clone https://github.com/ros-perception/perception_pcl.git -b fuerte-unstable-devel fuerte-unstable-devel

{{http://ros.org/images/wiki/PCL_logo.png||align="right"}}

== Introduction ==
The Point Cloud Library (PCL) is a stand-alone C++ library for 3D point cloud processing. You can learn more about PCL by visiting its website, [[http://www.pointclouds.org/|pointclouds.org]]. The documentation on ROS.org will help you get started using PCL in your ROS applications.

In particular, if you're just getting started with PCL in ROS, we encourage you to make use of the following resources:

 * [[pcl17/Tutorials|Tutorials]] - Try out a few examples to get an idea of what PCL can do.
 * [[http://docs.pointclouds.org/|API documentation]] - Browse the online API reference to find information about PCL's various classes and functions.
 * [[http://pointclouds.org/contact.html|Mailing list]] - If you need help, just ask! PCL has a great user community, with lots of people willing to help answer any questions you might have.

For new users of PCL, those resources will provide you with most of the information you'll need to get familiar with the library. Additional information pertaining to using PCL in your ROS applications can be found here on this wiki.

== Compilation and update ==
The makefile in this package checkouts the original PCL repository (https://github.com/PointCloudLibrary/pcl.git) and patches the source code, to be compatible with ROS and to have his own namespace (pcl17). The revision is coded in the Makefile. This revision is tested (It should compile, but it is still unstable.) with the ROS package and updated continuously. You can use the argument ''r'' to overwrite this presetting, e.g. ''r=8026'' or ''r=head''. You can update the used revision to the presetted revision with

{{{
make GIT_UP
}}}
,to a specific revision with

{{{
make GIT_UP r={REVISION}
}}}
and to the head with

{{{
make GIT_UP r=head
}}}
== Using PCL in ROS ==
For information about how to use PCL's ROS-specific data types and how to publish and subscribe to point cloud data, please consult the [[pcl/Overview|PCL/ROS overview]].

== Using KinfuLS (Kinect Fusion Large Scale) in ROS ==
You can checkout a experimental KinfuLS-ROS-Wrapper from

{{{
svn http://fsstud.is.uni-due.de/svn/ros/is/kinfu/
}}}
You have to launch openni and run kinfuLS from the kinfu package. The rendered model image is published as ''/camera/kinfuLS/depth''. Please make sure, that you have activated the compilation of kinfu in pcl17/Makefile:

{{{
-DBUILD_GPU=ON
}}}
and that you are using a compatible PCL revision (see the wrapper's svn log):

{{{
roscd pcl17 && make GIT_UP r=5aac0cbe8f4a82df18a13ca554f949b9bee848f8
}}}
== Tutorials ==
You can find numerous code examples on PCL's [[http://www.pointclouds.org/documentation/tutorials|tutorials page]].

For examples of how to include PCL code in a ROS node, please refer to the  [[pcl/Tutorials|Tutorials]] page.

== Documentation ==
For a detailed reference of PCL's classes and functions, please consult the [[http://docs.pointclouds.org/1.5.1/|online API documentation]].

For a reference guide to PCL's ROS-specific APIs, see the [[http://www.ros.org/doc/api/pcl_ros/html/|API documentation]] for the [[pcl_ros]] package.

== Using pre compiled PCL 1.7 ==
To use the pcl 1.7 standalone pre compiled follow this [[http://wiki.ros.org/pcl17_standalone|link]]