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Robust point-cloud registration based on the maximum-likelihood method

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Abstract

This paper proposes a robust iterative algorithm intended for registering three-dimensional point clouds. The data to be equalized are regarded as an implementation of random quantities whose distributions are modeled by means of Gaussian mixtures. Various strategies for processing outliers in the data are considered.

© 2017 Optical Society of America

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