High-precision and rapid binocular camera calibration method using a single image per camera

Significance 

High-precision binocular camera calibration (BCC) is a significant technique for improving the precision of stereo three-dimensional (3D) measurement, robot navigation and 3D visual positioning. There are two main categories of BCC method: self-calibration and target-based calibration. The constraints of the camera motion make it difficult to implement self-calibration methods in practical applications, leading to inaccurate extraction of feature points in images. On the other hand, target-based calibration also experiences challenges that limit its application scope.

Generally, the calibration objects commonly used in target-based calibration usually include 1D-, 2D- and 3D targets. Among them, 2D target is widely used for camera calibration owing to their high flexibility. A good example is Zhang’s camera calibration method based on chessboard patterns. Although Zhang’s method is a prominent calibration method, it fails to match homonymous corners constituting the BCC process accurately. While recently proposed target methods have been successful in addressing this issue associated with incomplete target projection, they require several calibration images making the calibration processes complicated. Such methods are unsuitable for some applications, like underwater scenarios with motion limits.

Although the calibration process can be simplified by adopting diverse 3D-target-based calibration, the fabrication difficulty of the 3D targets remains the main obstacle. To address this challenge, multi-plane-based stereo target has become an attractive research topic. This can be attributed to its ability to calibrate multiple cameras using only a single target image for individual cameras and the use of the low-cost 3D target. Whereas most of these methods, including Zhang’s method, rely on the reprojection error to evaluate the BCC accuracy, the reprojection error fails to reflect the precision of the camera calibration comprehensively. Therefore, developing a more effective parameter optimization approach to evaluate the precision of BCC is highly desirable.

On this account, Dr. Yulong Yin, Professor Huabing Zhu, Mr. Pei Yang, Mr. Zhaohui Yang, Mr. Kai Liu and Mr. Hongwei Fu from Hefei University of Technology proposed a new high-precision and rapid BCC method. This scheme was based on a stereo target comprising 12 coded planar targets, where each of the calibration corners was assigned a unique coded number. Consequently, a multi-constraint optimization method was proposed to improve the accuracy of BCC by fully utilizing the 3D features of the target. Their work is currently published in the journal, Optics Express.

The authors demonstrated the proposed method’s capability to implement accurate BCC using only a single calibration image per camera as well as allowing the matching of homonymous calibration corners for partial and incomplete target projection cases. Due to the speed, stability and precision advantages of the decoding method, the coded number of calibration corners and sub-pixel coordinates were obtained even in the complex backgrounds. A compressive evaluation of the precision of BCC was performed by combining the 3D measurement error and the reprojection errors, while its accuracy was improved using the proposed optimization method. Compared with Zhang’s method, the proposed calibration method achieved higher precision with significantly reduced 3D measurement and reprojection errors.

In summary, a rapid and high-precision BCC scheme based on a single image per camera was reported. It significantly decreased the complexity of the calibration process, allowing the calibration of both intrinsic and extrinsic parameters of the binocular camera using a single pair of target images. Nevertheless, the optimization of distortion coefficients could be impacted by the localized position of the target projected on the imaging sensor. In a statement to the Advances in Engineering, the authors provided important data for addressing emerging challenges to further improve the performance of BCC method.

About the author

Yulong Yin received his B.S. and M.E. degrees from the Hefei University of Technology, Hefei, China, in 2012 and 2015, respectively, and received his Ph.D. degree from the University of Science and Technology of China, Hefei, China, in 2019. He then joined the School of Mechanical Engineering, Hefei University of Technology, China, as a Postdoctoral Researcher. His research interests are camera calibration, machine vision and optical metrology.

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About the author

Huabing Zhu received the Ph.D. degree in mechanical manufacturing and automation from the Hefei University of Technology, China. From 1993 to 1998, he worked as a Lecturer at the Hefei University of Technology, China. From 1999 to 2007, he worked as an Associate Professor at the Hefei University of Technology, China. He has worked as a professor with the school of mechanical engineering, Hefei University of Technology since 2008. His main research fields  are manufacturing system engineering theory and application technology and green design and green manufacturing of mechanical and electrical products. He is currently deputy head of engineering training discipline group of National Experimental Teaching Demonstration Center of the Chinese Ministry of Education.

About the author

Pei Yang received the B.S. degree in mechanical engineering from the Hefei University of Technology, in 2022. He is currently pursuing the Ph.D. degree with the School of Instrument Science and Opto-Electronics Engineering. His research interests are computer vision and 3D vision measurement.

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Reference

Yin, Y., Zhu, H., Yang, P., Yang, Z., Liu, K., & Fu, H. (2022). High-precision and rapid binocular camera calibration method using a single image per cameraOptics Express, 30(11), 18781-18799.

Go To Optics Express

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