Local subspace video stabilization

Video stabilization enhances video quality by stabilizing unstable motion. This paper proposes a new video stabilization method that simultaneously factors and smooths motion trajectories. We model the trajectories with a time-variant local subspace constraint. Every column of the trajectory matrix is factored and smoothed in separate local subspace. This model makes our method more flexible and accurate than subspace video stabilization. In addition, we design a novel outlier detection technique that utilizes the relationship between consecutive local subspaces. Experiments on synthetic data validate the numerical performance of our factorization. Quantitative comparisons on real videos show that our local method is better than subspace video stabilization. Moreover, our stabilized videos are comparable with the public results from some other state-of-the-art methods.