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ICP

Description

ICP is an implementation of the Iterative Closest Point algorithm for registering two 3-D point clouds when the clouds are roughly aligned. It is based on algorithms of Besl and McKay (PAMI, February 1992) and Zhang (IJCV 1994). This implementation uses the faces in the surface mesh to get a accurate alignments and it uses kdtrees to speed up the registration process. SpinRecognize can be followed by ICP to get very accurate registration of surfaces with no knowledge of the transformation between views. During object modeling, a coarse registration of two views is obtained with SpinRecognize. This transformation is then refined with using fine resolution representations of the views.

Files

Usage

Usage: ICP (see ICP.html for complete usage)

Detailed Usage

%S scene faceset filename [required]

%S model faceset filename [required]

%S output faceset filename [required]

-translate %F %F %F initial translation [0 0 0]

-rotate %F %F %F initial rotation [0 0 0]

-nPer %d number of perturbations about minimum [0]

-maxDist %F maximum distance between points [1e8]

-maxIter %d maximum number of iterations [20]

-errT %F threshold on error [0.05]

-transT %F stopping criterion for translations [0.05]

-angleT %F stopping criterion for rotations in degrees [0.1]

-readTrans %S read initial transformation from file [off]

-writeTrans %S write final transformation to file [off]

Examples

An example of usage where no options are set thus providing a quick execution is:

An example which sets the algorithm to run for a longer time, but probably provide a better answer is:

up


The VMR Lab is part of the Vision and Autonomous Systems Center within the Robotics Institute in the School of Computer Science, Carnegie Mellon University.