A high-accuracy online calibration method for structured light 3D measurement

Abstract

Traditional offline calibration of a structured light 3D measurement system is cumbersome, ineffective, and dependent on calibration targets, whereas state-of-the-art (SoTA) online calibration methods are often haunted by low-precision matching points and thus exhibit poor accuracy and reliability. To this end, we present an automated and high-precision online calibration approach for structured light probes from a multi-camera-projector structured light system(MCPSLS). At the core of the approach, a new criterion for matching points filtration is constructed based on local point set topological similarity, which demonstrates higher accuracy and more robustness than typical RANSAC to outliers. Moreover, the fundamental matrix is optimized based on trinocular epipolar constraints, which further prevents the extrinsic parameter solution from being inaccurate and unreliable due to the small number of filtered matching points. Besides, to achieve a simultaneous and automated online calibration, the MCPSLS’s registration objects are served as spatial constraint fields to solve scale factors. Finally, all calibration parameters are nonlinearly optimized for their global optimal solutions. Experimental results show that the proposed approach outperforms SoTA online methods in robustness and accuracy and achieves comparable performance as the traditional offline calibration method.