Robust motion and correspondence of noisy 3-D point sets with missing data

Abstract We describe RICP, a robust algorithm for registering and finding correspondences in sets of 3-D points with significant percentages of missing data, and therefore useful for both motion analysis and reverse engineering. RICP exploits LMedS robust estimation to withstand the effect of outliers. Our extensive experimental comparison of RICP with ICP shows RICP's superior robustness and reliability.

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