A joint calibration system of lidar and binocular cameras based on an improved calibration board and DON algorithm

Zhibin Huang; Guochu Chen; Xichao Wang; Baojiang Li

doi:10.1117/12.2660421

3 February 2023 A joint calibration system of lidar and binocular cameras based on an improved calibration board and DON algorithm

Zhibin Huang, Guochu Chen, Xichao Wang, Baojiang Li

Author Affiliations +

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251129 (2023) https://doi.org/10.1117/12.2660421
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

For calibration of lidar and vision, the point cloud data is irregular and noisy. Meanwhile, the outliers need to be removed due to the occlusion caused by the simple calibration plate. A joint calibration method of binocular cameras and lidar based on improved calibration plate and DON algorithm is proposed. Firstly, circular bulges of different sizes are added to the rectangular calibration plate, and then the point cloud data is filtered and segmented by the DON (Difference of Normal) algorithm. In addition, the random sample consistency (RANSAC) algorithm is used to estimate the plane and edge parameters of the triangle plate by retaining point clouds to obtain the three-dimensional positions of vertices. Finally, the projection matrix between the camera and lidar is estimated using 2D-3D corresponding points at different positions. The projection errors and root mean square errors of different frames and corresponding points are calculated. The results show that the average error of 100 frames is reduced by 5.3% compared with 1 frame. The root means square error (RMSE) of this method is 1.415cm. Compared with other advanced methods, the reliability and superiority of this method are verified.

Citation Download Citation

Zhibin Huang, Guochu Chen, Xichao Wang, and Baojiang Li "A joint calibration system of lidar and binocular cameras based on an improved calibration board and DON algorithm", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251129 (3 February 2023); https://doi.org/10.1117/12.2660421

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available