Flexible Extrinsic Parameter Calibration for Multicameras With Nonoverlapping Field of View

In many measurement applications using multi-cameras, there is often a non-overlapping field of view (nFOV) between multi-cameras. It benefits greatly from having all of the cameras unified in a single coordinate frame by means of common spatial constraints. However, it is very difficult to establish common spatial constraints for accurate and quick calibration of the extrinsic parameters between multi-cameras in the case of long working distance, asymmetric working angle or limited working space. To overcome these issues, we propose a flexible calibration method using a camera rig, which can be easily modeled as a hand-eye calibration problem and solved by only several sets of calibration images. To further improve the calibration accuracy, the camera intrinsic parameters, lens distortion coefficients, and extrinsic parameters are optimized simultaneously, similar to binocular calibration. However, this causes instability of multi-parameters. We extend the epipolar constraint to two images with nFOV and add it into the optimization objective function together with the re-projection error, which ensures the basic consistency of intrinsic parameters before and after optimization, and reduce the fluctuation caused by the number of images involved in calibration. Experiments and application have proved that the proposed new methods are feasible and effective.