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.
Demo for video stabilization
Software available for cloud based stabilization
 Hui Qu, Li Song, Gengjian Xue, "Shaking Video Synthesis for Video Stabilization Performance Assessment
", IEEE Visual Communications and Image Processing (VCIP 2013)
, Kuching, Malaysia, Nov. 12-20, 2013. (PDF
 Hui Qu, Li Song, "Video stabilization with L1-L2 optimization
", 2013 20th IEEE International Conference on Image Processing (ICIP2013)
, Melbourne, Australia, Sep. 15-18, 2013. (PDF