Robust Camera Motion Estimation In Video Sequences

Camera motion estimation of video sequences requires robust recovery of camera parameters and is a cumbersome task concerning arbitrarily complex scenes in video sequences. In this paper, we present a novel algorithm for robust and accurate estimation of camera motion. We insert a virtual frame between each pair of consecutive frames, through which the in-between camera motion is decomposed into two separate components, i.e., pure rotation and pure translation. Given matched feature points between two frames, one point set corresponding to the far scene is chosen, which is used to estimate initial camera motion. We further refine it recursively by a non-linear optimizer, yielding the final camera motion parameters. Our approach achieves accurate estimation of camera motion and avoids instability of camera tracking. We demonstrate high stability, accuracy and performance of our algorithm with a set of augmented reality applications based on acquired video sequences.