IMAGE MOMENTS BASED VISUAL TRACKING OF 3D TRANSLATIONAL MOTION

This paper describes a visual tracking method which uses image moment as image feature for tracking a target that moves in 3D with translational motion. According to the specific tasks, a set of moment is selected as image feature. Then, the moment-based Jacobian is deduced. With the moment-based Jacobian, the visual servoing controller composed of image-based feedback and adaptive motion compensation is designed to track the moving target. In the tracking process, the knowledge of camera focus and depth of object is unnecessary. The simulation results show that using image moment as image feature can avoid the complex feature matching process, and acquire a satisfied tracking accuracy.