Experimental Verification of Formulas For Variances of Plane Parameters Fitted to 3D Imaging Data

Published

January 7, 2011

Author(s)

Marek Franaszek, Geraldine S. Cheok, Kamel S. Saidi

Abstract

Nonlinear Least Squares method is applied to fit a plane to 3D imaging data. Two different error functions used in fitting are tested: orthogonal and directional. Variances of fitted parameters are calculated either from a single dataset using derived earlier analytical formulas or by repeating the scans at the same experimental settings. In the latter case, the variance is equal to the square of the standard deviation from the repeated scans. The results show that the orthogonal error function severely underestimates the variances calculated with the mathematical formulas when compared to variances calculated from multiple scans. The variances calculated from formulas based on the directional error function are in good agreement with estimates calculated from multiple scans. Thus, the variances of the fitted plane parameter can be determined correctly from a single scan when proper formulas are used. This is important because multiple scans from the same location are typically not performed in the field.

Citation

IEEE Transactions on Instrumentation and Measurement

Volume

16

Pub Type

Journals

Download Paper

https://doi.org/10.1109/TIM.2011.2157720

Local Download

Keywords

Nonlinear Least Squares, 3D imaging systems, variances of fitted plane parameters, orthogonal error function, directional error function

Citation

Franaszek, M. , Cheok, G. and Saidi, K. (2011), Experimental Verification of Formulas For Variances of Plane Parameters Fitted to 3D Imaging Data, IEEE Transactions on Instrumentation and Measurement, [online], https://doi.org/10.1109/TIM.2011.2157720 (Accessed October 28, 2025)