Feature-based video stabilization for vehicular applications

Abstract

This paper describes a method to stabilize video for vehicular applications based on Harris features and adaptive resolution. Lucas-Kanade method is applied to match feature points of consecutive frames and construct the feature motion flow. A damping filer is utilized to model the unwanted motion and global motion is separated by extracting oscillation. 92% correct rate with 0.54 second per frame is achieved. The provided benchmark shows outperformance of the proposed method.