Weighted total least squares for rigid body transformation and comparative study on heteroscedastic points

Yongjun Zhou; Caihua Deng; Jianjun Zhu

doi:10.1117/12.912746

24 October 2011 Weighted total least squares for rigid body transformation and comparative study on heteroscedastic points

Yongjun Zhou, Caihua Deng, Jianjun Zhu

Author Affiliations +

Proceedings Volume 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications; 82860X (2011) https://doi.org/10.1117/12.912746
Event: International Symposium on Lidar and Radar Mapping Technologies, 2011, Nanjing, China

Abstract

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.

Citation Download Citation

Yongjun Zhou, Caihua Deng, and Jianjun Zhu "Weighted total least squares for rigid body transformation and comparative study on heteroscedastic points", Proc. SPIE 8286, International Symposium on Lidar and Radar Mapping 2011: Technologies and Applications, 82860X (24 October 2011); https://doi.org/10.1117/12.912746

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