Aligning two point clouds is the iterated closest point algorithm which starts with two point clouds to estimate three
translates and rotations. Traditional registration are searching the optimal solutions at the cost function of the minimum
residual squares without consideration of points covariance. Closed-form or iterative least squares methods are
performed to search the solutions, and total least squares (TLS) methods are introduced in recent years. The ordinary
least squares (OLS) and OTLS methods can not work on the heteroscedastic cases. So element-wise weighted TLS
(EWTLS) and row-wise weighted TLS (RWTLS) methods are introduced to solve the rigid body transformation problem
after the initial values obtained by Procrustes analysis method. Comparative studies are made with the weighted and
unweighted estimators of OLS, TLS, mixed OLS and TLS, EWTLS and RWTLS. The results indicate that the RWTLS
method is the highest accuracy estimator, and be much more accurate than the unweighted OLS and TLS methods.
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