3D Digital Imaging and Modeling, International Conference on (2007)

Montreal, Quebec, Canada

Aug. 21, 2007 to Aug. 23, 2007

ISSN: 1550-6185

ISBN: 0-7695-2939-4

pp: 427-434

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/3DIM.2007.39

Jeff M. Phillips , Duke University

Ran Liu , Duke University

Carlo Tomasi , Duke University

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. 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.

INDEX TERMS

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CITATION

Jeff M. Phillips,
Ran Liu,
Carlo Tomasi,
"Outlier Robust ICP for Minimizing Fractional RMSD",

*3D Digital Imaging and Modeling, International Conference on*, vol. 00, no. , pp. 427-434, 2007, doi:10.1109/3DIM.2007.39CITATIONS