Multiple nonoverlapping camera pose estimation
Mohammad Ehab Ragab, Ka‐Hing Wong · 2010
In this paper, we solve the pose estimation problem in real time using multiple nonoverlapping cameras and the Extended Kalman Filter (EKF). Four cameras arranged in two back-to-back pairs are put on the platform of a moving robot. The two axes passing through the camera centers of each pair are perpendicular. This arrangement aims to maximize the benefits of the back-to-back setting whose accuracy is shown in literature. Each camera has its individual EKF for pose estimation which enables accurate short base-line feature tracking and parallel processing. A model for multiple nonoverlapping cameras is formulated which improves the estimate of rotation parameters with the help of a median arbiter. Accordingly, the translational parameters of pose are estimated accurately and the scale factor ambiguity related to single camera methods is solved using a low-dimensional speedy optimization.