Pose estimation for multiple camera systems

Pose estimation of a multiple camera system (MCS) is usually achieved by either solving the PnP problem or finding the least-squared-error rigid transformation between two 3D point sets. These methods employ partial information of an MCS, in which only a small number of features in one or two cameras can be utilized. To overcome this limitation, we propose a new pose estimation method for an MCS that uses complete information of an MCS. In our method, we treat the MCS as a single generalized camera and formulate this problem in a least-squared manner. An iterative algorithm is proposed for solving the least-squared problem. From the experimental results, it shows that the proposed method is accurate for pose estimation of MCS.