Outlier Robust ICP for Minimizing Fractional RMSD
Abstract
We describe a variation of the iterative closest point (ICP) algorithm for aligning two point sets under a set of transformations. Our algorithm is superior to previous algorithms because (1) in determining the optimal alignment, it identifies and discards likely outliers in a statistically robust manner, and (2) it is guaranteed to converge to a locally optimal solution. To this end, we formalize a new distance measure, fractional root mean squared distance (frmsd), which incorporates the fraction of inliers into the distance function. We lay out a specific implementation, but our framework can easily incorporate most techniques and heuristics from modern registration algorithms. We experimentally validate our algorithm against previous techniques on 2 and 3 dimensional data exposed to a variety of outlier types.
 Publication:

arXiv eprints
 Pub Date:
 June 2006
 arXiv:
 arXiv:cs/0606098
 Bibcode:
 2006cs........6098P
 Keywords:

 Computer Science  Graphics;
 Computer Science  Computational Geometry
 EPrint:
 22 pages, 7 Figures, 9 Tables