scoobadood/ice_mat

A Matlab implementation of the Iterative Closest Point (ICP) algorithm described in Besl, P.J. & McKay, N.D. 1992, 'A Method for Registration of 3-D Shapes', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2,  IEEE Computer Society.

ICP

This is a Matlab implementation of the Iterative Closest Point algorithm described in Besl, P.J. & McKay, N.D. 1992, 'A Method for Registration of 3-D Shapes', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, IEEE Computer Society.

It consists of two files, icp.m and icp_driver.m. icp_driver.m is an example of using the icp function.

Use

[R, t] = icp( srcPoints, targetPoints, tau ) iteratively seeks the rotation R and translation t which align srcPoints most closely with targetPoints. srcPoints and targetPoints are matrices of 3D points with a column for each point. Note that there is no requirement for srcPoints to have the same number of points as targetPoints. tau is a threshold such that when the RMSE between transformed srcPoints and targetPoints does not change by more than this threshold between iterations the algorithm is deemed to have converged.

[R, t, k] = ICP( srcPoints, targetPoints, tau ) also returns k, the number of iterations required to complete the match.

More Information

For more information see The Besl and McKay paper