Robust Point Matching with Distance Profiles
While matching procedures based on pairwise distances are conceptually appealing and thus favored in practice, theoretical guarantees for such procedures are rarely found in the literature. We propose and analyze matching procedures based on distance profiles that are easily implementable in practice, showing these procedures are robust to outliers and noise. We demonstrate the performance of the proposed method using a real data example and provide simulation studies to complement the theoretical findings.
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