Video Stabilization Using Scale-Invariant Features

Abstract

Video Stabilization is one of those important video processing techniques to remove the unwanted camera vibration in a video sequence. In this paper, we present a practical method to remove the annoying shaky motion and reconstruct a stabilized video sequence with good visual quality. Here, the scale invariant (SIFT) features, proved to be invariant to image scale and rotation, is applied to estimate the camera motion. The unwanted vibrations are separated from the intentional camera motion with the combination of Gaussian kernel filtering and parabolic fitting. It is demonstrated that our method effectively removes the high frequency 'noise' motion, but also minimize the missing area as much as possible. To reconstruct the undefined areas, resulting from motion compensation, we adopt the mosaicing method with Dynamic Programming. The proposed method has been confirmed to be effective over a widely variety of videos.