Abstract
The acquisition of digital video usually suffers from undesirable camera jitters due to unstable camera motions. In this paper, we propose a robust real-time video stabilization algorithm that alleviates the undesirable jitter motions from the unstable video to produce a stabilized video. In the proposed algorithm, we first compute the sparse optical flow vectors between successive frames, followed by estimating the camera motion by fitting the computed optical flow vectors to a simplified affine motion model with a robust trimmed least squares method. Then the computed camera motion parameters are smoothed temporally to reduce the motion fluctuations by using a regularization method. Finally, we transform all frames in the video sequence based on the original and smoothed camera motions to obtain a stabilized video. Experimental results are given to demonstrate the stabilization performance and the efficiency of the proposed algorithm. © 2005 Elsevier Inc. All rights reserved.