Electronic image stabilization using multiple visual cues

Image stabilization is a key preprocessing step in dynamic image analysis and deals with the removal of unwanted image motion in a video sequence. This paper presents an integrated algorithm for the problem of image stabilization. The algorithm combines various visual cues such as points and horizon lines, and relies on an extended Kalman filter for the estimation of parameters of interest. We study both calibrated and uncalibrated stabilization cases, and consider the problem of the selection of model dynamics for the estimation of warping parameters. Experimental results from video sequences generated from off-road vehicle platforms show good performance of stabilization algorithm.