A least-squares method for simultaneous synchronization and relative calibration of overlapped videos

In this paper, a straightforward mathematical model is proposed to synchronize and estimate the relative parameters of videos taken with a fixed relative orientation. The foundation of this model was the well-known coplanarity condition that prevails between matched points of two perspective images. Nevertheless, the synchronization problem has also been incorporated into it by making the matched points dependent on time. In this method, the required control data provides by tracking the positions of moving points in the temporal and spatial overlaps of the videos. Also, the unknown parameters are estimated through the least-squares estimation of a constrained system of linearized equations. The results of implementations on different datasets have demonstrated the efficiency of the proposed method in the temporal and relative calibration of stereo videos; as it has reached on average to the one frame accuracy in synchronization and 4.3 pixels precision in generalization of relative calibrations.