Improved auto-extrinsic calibration between stereo vision camera and laser range finder

• Published in: International journal of image and data fusion 2021-04, Vol.12 (2), p.122-154
• Main Authors: Khurana, Archana, Nagla, K. S.
• Format: Article
• Language: English
• Subjects: automatic feature extraction; Calibration; Cameras; Experimentation; Feature extraction; Image reconstruction; Laser range finders; laser-camera calibration; Lasers; Parameter estimation; Parameter identification; plane-line correspondences; Range-reflectivity-bias
• ISSN: 1947-9832; 1947-9824
• DOI: 10.1080/19479832.2020.1727574

This study identifies a way to accurately estimate extrinsic calibration parameters between stereo vision camera and 2D laser range finder (LRF) based on 3D reconstruction of monochromatic calibration board and geometric co-planarity constraints between the views from these two sensors. It supports automatic extraction of plane-line correspondences between camera and LRF using monochromatic board, which is further improved by selecting optimal threshold values for laser scan dissection to extract line features from LRF data. Calibration parameters are then obtained by solving co-planarity constraints between the estimated plane and line. Furthermore, the obtained parameters are refined by minimising reprojection error and error from the co-planarity constraints. Moreover, calibration accuracy is achieved because of extraction of reliable plane-line correspondence using monochromatic board which reduces the impact of range-reflectivity-bias observed in LRF data on checkerboard . As the proposed method supports to automatically extract feature correspondences, it provides a major reduction in time required from an operator in comparison to manual methods. The performance is validated by extensive experimentation and simulation, and estimated parameters from the proposed method demonstrate better accuracy than conventional methods.