Parameters estimation-based calibration method for rotational axis of line-structured light 3D reconstruction
Tianyu Li, Fajie Duan, Changwen Liu, Xiao Fu, Anqi Chen, Chunjiang Liang, Jiaxin Li, Hao Zheng, Guanghui Guo
Abstract
Rotation is a critical component in 3D reconstruction systems, where accurate calibration of rotation axis parameters is essential for 3D stitching. In this study, what we believe to be a novel parameters estimation-based method for calibrating rotation axis parameters using 2D planar targets is proposed. Compared to traditional circle fitting methods, this method takes both orientation and position information into account, resulting in better precision performance. By leveraging the transmission of spatial pose relationships, the parameters estimation-based calibration method also effectively mitigates the impact of noise for more accurate calibration of rotation axis parameters. Error validation and 3D reconstruction experiments proved the superior performance of the proposed method. The experiment results demonstrate the effectiveness and applicability of the approach in enhancing the calibration of rotation axis parameters for 3D reconstruction systems.