Although hand tracking algorithm has been widely used in virtual reality and HCI system, it is still a challenging problem in vision-based research area. Due to the robustness and real-time requirements in VR applications, most hand tracking algorithms require special device to achieve satisfactory results. In this paper, we propose an easy-to-use and inexpensive approach to track the hands accurately with a single normal webcam. Outstretched hand is detected by contour & curvature based detection techniques to initialize the tracking region. Robust multi-cue hand tracking is then achieved by velocity-weighted features and color cue. Experiments show that the proposed multi-cue hand tracking approach achieves continuous real-time results even for the situation of cluttered background. The approach fulfills the speed and accuracy requirements of frontal-view vision-based human computer interactions.