Extended Kalman filtering approach to stereo video stabilization

Processing of stereo images has become more and more important in recent years because of the availability of various stereo displaying devices. In particular, stabilizing of stereo images is important and useful especially when the images are obtained from cameras held by inexperienced hands or placed on unstable platforms. In this paper, we propose a new frame warping method for such a problem. Most video stabilization methods to date use 2-D geometric transform to approximate the changes between frames. However, these methods fail when there is a large depth variation between the foreground and the background in the scene. We try to solve this by estimating the 3-D motion parameters of the cameras by tri-focal tensor and the extended Kalman filter. And use the motion parameters to stabilize the images. We test the method using synthetic and real images and the results show that the performance of our proposed method is accurate even if the background contains large relative depth variations.