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Investigates the use of Euclidean invariants in the iterative closest point registration of range images. Invariants are used in a modified distance function for the selection of point correspondences. Theoretical results show that under ideal conditions, using invariants can only improve the chance of a making correct correspondences. In addition, monotonic convergence to a local minimum is preserved. Experimental results show that using invariant features accelerates the registration and decreases the probability of being trapped in a local minimum.
Sharp et al. (Mon,) studied this question.
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