Montreal, Quebec, Canada
Aug. 21, 2007 to Aug. 23, 2007
Jeff M. Phillips , Duke University
Ran Liu , Duke University
Carlo Tomasi , Duke University
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/3DIM.2007.39
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.
Jeff M. Phillips, Ran Liu, Carlo Tomasi, "Outlier Robust ICP for Minimizing Fractional RMSD", 3DIM, 2007, 3D Digital Imaging and Modeling, International Conference on, 3D Digital Imaging and Modeling, International Conference on 2007, pp. 427-434, doi:10.1109/3DIM.2007.39