Abstract
The acquisition of digital video usually suffers from undesirable camera jitters due to unstable random camera motions, which are produced by a hand-held camera or a camera in a vehicle moving on a non-smooth road or terrain. In this paper, we propose a real-time robust video stabilization algorithm to remove undesirable jitter motions and produce a stabilized video. In our algorithm, we first compute the optical flows between successive frames, followed by estimating the camera motion by fitting the computed optical flow field to a simplified affine motion model with a trimmed least squares method. Then the computed camera motions are smoothed temporally to reduce the motion vibrations by using a regularization method. Finally, we transform all frames of the video based on the original and smoothed motions to obtain a stabilized video. Experimental results are given to demonstrate the stabilization performance and the efficiency of the proposed algorithm.