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This paper presents a visual tracking control design of a nonholonomic mobile robot equipped with a tilt camera. The proposed design enhances various image-tracking applications using an on-board monocular camera, such as human-robot interaction and surveillance. Based on Lyapunov theory, the proposed control scheme not only possesses some degree of robustness against parametric uncertainty, but also overcomes the external uncertainty caused by velocity quantization noise. Moreover, the proposed controller fully works in the image space; hence, the computational complexity and the effects of sensor/camera modeling errors can be greatly reduced. Experimental results validate the effectiveness of the proposed control scheme, in terms of tracking performance, system convergence, and robustness.