Reconfigurable omnidirectional camera array calibration with a linear moving object

Reconfigurable omnidirectional camera arrays are useful for applications where multiple cameras working together are to be deployed at a short notice. This paper proposes a multi-camera calibration approach for such arrays using a 1D object such as a person, moving parallel to itself. The moving object is separated from the background and correspondences between multiple cameras are obtained using location of the object in all the cameras in multiple frames. The approximate orientation of the cameras is individually determined using vanishing points. The non-linear 3D problem of multi-camera calibration can then be approximated by a 2D problem in plan view. An initial solution for the relative positions and orientations of multiple cameras is obtained using the factorization approach. A non-linear optimization stage is then used to correct the approximations, and to minimize the geometric error between the observed and the projected omni pixel coordinates. Numerous experiments are performed with simulated data sets as well as real image sequences to evaluate the performance of this approach.