A Central Sub-image Based Global Motion Estimation Method for In-Car Video Stabilization

This paper presents a novel global motion estimation method based on the phase correlation of central sub-image. In this study, we consider the case that the In-Car videos are captured from the cameras placed in front of a car. The backgrounds of these In-Car videos usually vary with the moving car, which result in the inaccuracy of classical image stabilization method. As a result, a central sub-image based image stabilization method is presented in this paper. The simulation results show that the proposed method is efficient in improving the accuracy of detecting global motion vectors of In-Car videos.