Outlier Robust ICP for Minimizing Fractional RMSD

Jeff M. Phillips; Ran Liu; Carlo Tomasi

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arXiv · cs/0606098

Outlier Robust ICP for Minimizing Fractional RMSD

Jeff M. Phillips·Ran Liu·Carlo Tomasi

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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.

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BibTeX RIS

Jeff M. Phillips, Ran Liu, Carlo Tomasi. 2006-06-22. Outlier Robust ICP for Minimizing Fractional RMSD. https://arxiv.org/abs/cs/0606098

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