Vision-based motion variable estimation has been an area of intensive interest, especially for emerging applications in space robotics such as satellite maintenance, refueling and the removal of space debris. For each of these tasks, accurate kinematic motion estimates of an object are required before a robot can approach or interact with the object. In this paper, a technique is presented for autonomous identification of an object against a cluttered background and simultaneous estimation of kinematic variables of the object undergoing general 3D motion using an eye-in-hand robot camera system. The object and marker identification strategy has been partially validated by using a spherical balloon with circular markers and a stationary camera. While the validation of the kinematic variables estimation algorithm has been completed against simulated data.