A stable vision system for moving vehicles

This paper presents a novel approach to stabilize the output of video camera installed on a moving vehicle in a rugged environment. A 2.5-D interframe motion model is proposed so that the stabilization system can perform in situations where significant depth changes are present and the camera has both rotation and translation. Inertial motion filtering is proposed in order to eliminate the vibration of the video sequences with enhanced perceptual properties. The implementation of this new approach integrates four modules: pyramid-based motion detection, motion identification and 2.5-D motion parameter estimation, inertial motion filtering, and affine-based motion compensation. The stabilization system can smooth unwanted vibrations or shakes of video sequences and achieve real-time speed. We test the system on IBM PC compatible machines and the experimental results show that our algorithm outperforms many algorithms which require parallel pipeline image processing machines.