Plane based multi camera calibration under unknown correspondence using ICP-like approach

In the present paper, we propose a plane based multi camera calibration method in the case that point correspondences among camera images are not given afore-hand. One can encounter this situation when calibrating a set of fixed cameras by observing a partial region of a large reference plane with a repeated pattern. Basically, all the camera parameters except relative poses are estimated by applying a homography based calibration to a set of observed reference planes in different poses for each camera. The problem is how to obtain fine correspondences among camera images to estimate the relative poses even though there were no common observed points. When a set of cameras simultaneously observe a part of a large reference plane with an infinitely repeating pattern, the problem can be considered as alignment of sets of the large reference planes in different pose observed by different cameras while optimizing camera parameters. Therefore, we integrate the iterative closest point (ICP) approach for estimating (virtual) corresponding points onto optimization process. This approach works well with the low quality initial value by a linear solver. Our experiment shows our method overwhelms a standard nonlinear optimization approach over the all camera parameters in corresponding point detection.