This repository provides data and source code for the Iterative Most-Likely Oriented Point (IMLP) algorithm described in the paper:

Seth Billings, Emad Boctor, and Russell Taylor, "Iterative Most-Likely Point Registration (IMLP): A Robust Algorithm for Computing Optimal Shape Alignment", PLOS One (2015)

To compile the C++ library containing the IMLP source code: see "cisstICP" folder. To run the experiments described in the PLOS One paper: see "PLOSONE" folder.

Source code is provided for the following algorithms (see PLOS One paper for details):

• IMLP
• IMLP-CP
• IMLP-MD
• ICP
• Robust ICP

Other algorithms (of other authors) evaluated in the PLOS One paper, for which source code is not provided, include:

GICP:

• was downloaded from: http://www.robots.ox.ac.uk/~avsegal/generalized_icp.html
• see IMLP paper for minor modifications required for termination condition and to set covariance matrices

CPD:

• was downloaded from: www.bme.ogi.edu/~myron/matlab/cpd
• now available at: https://sites.google.com/site/myronenko/research/cpd
• see IMLP paper for minor modifications required for termination condition

These algorithms can be downloaded at the URLs provided above and run using output
from the IMLP algorithm above; i.e. point sets, noisy points, covariances, etc. are all saved and can be loaded and run by these algorithms.