Point Cloud Library (PCL)  1.7.0
/tmp/buildd/pcl-1.7-1.7.0/registration/registration.doxy
00001 /**
00002   \addtogroup registration Module registration
00003 
00004   \section secRegistrationPresentation Overview
00005 
00006 Combining several datasets into a global consistent model is usually performed
00007 using a technique called registration. The key idea is to identify
00008 corresponding points between the data sets and find a transformation that
00009 minimizes the distance (alignment error) between corresponding points. This
00010 process is repeated, since correspondence search is affected by the relative
00011 position and orientation of the data sets. Once the alignment errors fall below
00012 a given threshold, the registration is said to be complete.
00013 
00014 The <b>pcl_registration</b> library implements a plethora of point cloud
00015 registration algorithms for both organized an unorganized (general purpose)
00016 datasets.
00017 
00018 \image html http://www.pointclouds.org/assets/images/contents/documentation/registration_outdoor.png
00019 \image html http://www.pointclouds.org/assets/images/contents/documentation/registration_closeup.png
00020 
00021   \section secRegistrationRequirements Requirements
00022   - \ref common "common"
00023   - \ref kdtree "kdtree"
00024   - \ref sample_consensus "sample_consensus"
00025   - \ref features "features"
00026 
00027 */