This paper presents a novel face tracking control scheme for human-robot interaction control in image plane. This control scheme is robust to the velocity quantization error in practical implementation. A visual tracking controller is designed for ensuring global asymptotic stability of the closed-loop visual tracking system based on an error-state control model in image plane. In order to overcome the quantization uncertainty encountered in practical systems, an image-based robust control law is proposed to guarantee the stability of the robotic control system based on Lyapunov theory. This design provides a useful solution for smooth visual tracking control of slow-motion robots in a home setting. Simulation and Experimental results verify the effectiveness of the proposed visual tracking control scheme, both in terms of tracking performance and system convergence.