Video Stabilization


Video stabilization seeks to create stable versions of casually shot video, which can not only improve people’s visual comfort but also be a preprocessing of some other procedures, such as object tracking, object detection, video compression and so on, resulting in increas- ed precision and robustness. The project focuses on improving the efficiency of video stabilization algorithms as well as developing bet- ter deshaking assessment tools to identify shaking and evaluate the exsiting algorithms.

We have proposed a video stabilization algorithm based on L1-L2 optimization, which can remove unwanted camera movements as well as keep the original video information to the greatest extent, and a video stabilization algorithm based on attitude sensors, which can stabilize shaky videos using gyroscope sensors. We also designed a shaking video synthesis method for performance evaluation. We have applied our stabilization algorithm into cloud-based stabilization, in which the stabilization process is on the server, and users only need to upload their shaky videos and download the stabilized ones after a while.

Online Demo

Demo for video stabilization


Software available for cloud based stabilization

Li Song
Li Song
Professor, IEEE Senior Member

Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.