Global point tracking based panoramic image stabilization system

A novel image stabilization system is presented, which consists of a global feature point tracking based motion estimation, a Kalman filtering based motion smoothing and an image mosaic based panoramic compensation. The global motion is estimated using feature point matching and iteration with the least-square method. Then, the Kalman filter is applied to smooth the original motion vectors to effectively alleviate unwanted camera vibrations and follow the intentional camera scan. Lastly, the loss information of image boundary due to the motion compensation is reconstructed with image mosaic to improve the visual quality. The experimental results show that this system can smooth unwanted translation or rotation of the video sequences and realize a panoramic stabilization at real-time speed. This work has been supported by the National “863 Program” on High Technology Research and Development of China (Grant No. 2006AA01Z127)