Efficient real-time robotic tasks using a monocular vision system were previously developed with simple objects (e.g. white points on a black background), within a visual servoing context. Due to recent developments, it is now possible to design real-time visual tasks exploiting motion information in the image, estimated by robust algorithms. This paper proposes such an approach to track complex objects, such as a pedestrian. It consists in integrating the measured 2D motion of the object to recover its 2D-position in the image. The principle of the tracking task is to control the camera pan and tilt such that the estimated center of the object appears at the center of the image. Real-time experimental results demonstrate the efficiency and the robustness of the method.