Feature-based real-time video stabilization for vehicle video recorder system

This paper presents a fast and effective method based on features to obtain real-time video stabilization for vehicle video recorder system. The corresponding feature points are first obtained from two consecutive frames and then optical flows are calculated based on these points. Next, the obtained optical flows are mapped to polar coordinates to obtain clusters and remove incorrect optical flows. These obtained clusters are used to evaluate the global motion and rotation angle. Finally, the obtained global motion and rotation angle are smoothed and then compensated to obtain the stabilized video. Experimental results show that the proposed method has good performance for video stabilization.