Abstract
Digital videos often suffer from undesirable camera jitters because of unstable camera motions. In this paper we present a novel video stabilization algorithm by mixed L1-L2 optimization, aiming at removing unwanted camera movements as well as keeping the original video information to the greatest extent. In the proposed algorithm, we compute smoothed camera paths that are composed of constant, linear and parabolic segments by L1 constraints, meanwhile using the L2 norm of the difference between smoothed and original camera paths to retain the video information. Different from other existing methods, there is only one parameter to control effects of two terms, which is both flexible and easy to meet different requirements in practice. We further design an efficient moving window scheme to support online processing or unlimited length video. Experimental results demonstrate the good performance of our proposed algorithm.
Li Song
Professor, IEEE Senior Member
Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.