Extrinsic Camera Calibration with Line-Laser Projection

Knowledge of precise camera poses is vital for multi-camera setups. Camera intrinsics can be obtained for each camera separately in lab conditions. For fixed multi-camera setups, the extrinsic calibration can only be done in situ. Usually, some markers are used, like checkerboards, requiring some level of overlap between cameras. In this work, we propose a method for cases with little or no overlap. Laser lines are projected on a plane (e.g., floor or wall) using a laser line projector. The pose of the plane and cameras is then optimized using bundle adjustment to match the lines seen by the cameras. To find the extrinsic calibration, only a partial overlap between the laser lines and the field of view of the cameras is needed. Real-world experiments were conducted both with and without overlapping fields of view, resulting in rotation errors below 0.5°. We show that the accuracy is comparable to other state-of-the-art methods while offering a more practical procedure. The method can also be used in large-scale applications and can be fully automated.

[1]  William H. Sanders,et al.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2014 .

[2]  Maciej Nikodem,et al.  Multi-Camera Vehicle Tracking Using Edge Computing and Low-Power Communication , 2020, Sensors.

[3]  Rudi Penne,et al.  Camera Calibration Using Gray Code , 2019, Sensors.

[4]  Michael Felsberg,et al.  Robust Accurate Extrinsic Calibration of Static Non-overlapping Cameras , 2017, CAIP.

[5]  Guangjun Zhang,et al.  A calibration method for stereo vision sensor with large FOV based on 1D targets , 2011 .

[6]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[7]  Zhen Liu,et al.  External parameter calibration of widely distributed vision sensors with non-overlapping fields of view , 2013 .

[8]  Ju Shen,et al.  A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks † , 2018, Sensors.

[9]  Rudi Penne,et al.  An Exact Robust Method to Localize a Known Sphere by Means of One Image , 2018, International Journal of Computer Vision.

[10]  Rudi Penne,et al.  Extrinsic camera calibration for non-overlapping cameras with Gray code projection , 2020 .

[11]  Wilfried Philips,et al.  Extrinsic Calibration of Camera Networks Based on Pedestrians , 2016, Sensors.

[12]  Guangjun Zhang,et al.  Global calibration method of multi-sensor vision system using skew laser lines , 2012 .

[13]  Guangjun Zhang,et al.  A global calibration method for multiple vision sensors based on multiple targets , 2011 .

[14]  Junhua Sun,et al.  Calibration method for geometry relationships of nonoverlapping cameras using light planes , 2013 .

[15]  Andrew Zisserman,et al.  MLESAC: A New Robust Estimator with Application to Estimating Image Geometry , 2000, Comput. Vis. Image Underst..

[16]  Feng Gao,et al.  A calibration method for non-overlapping cameras based on mirrored absolute phase target , 2019 .

[17]  Chen Zhu,et al.  Robust Plane-Based Calibration of Multiple Non-Overlapping Cameras , 2016, 2016 Fourth International Conference on 3D Vision (3DV).

[18]  Simon Thibault,et al.  Influence of camera calibration conditions on the accuracy of 3D reconstruction. , 2016, Optics express.

[19]  Jack Dongarra,et al.  Special Issue on Program Generation, Optimization, and Platform Adaptation , 2005, Proc. IEEE.

[20]  Hideo Saito,et al.  Extrinsic Camera Calibration Without Visible Corresponding Points Using Omnidirectional Cameras , 2018, IEEE Transactions on Circuits and Systems for Video Technology.

[21]  Jibin Zhao,et al.  Global calibration of non-overlapping cameras: State of the art , 2018 .

[22]  Shyan-Ming Yuan,et al.  STAM-CCF: Suspicious Tracking Across Multiple Camera Based on Correlation Filters , 2019, Sensors.

[23]  Xu Chen,et al.  Flexible and Accurate Calibration Method for Non-Overlapping Vision Sensors Based on Distance and Reprojection Constraints , 2019, Sensors.

[24]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..