This article considers visual servoing-based motion control of multirotor unmanned aerial vehicles. We employ output feedback and image-based visual servoing to control the vehicle's pose with respect to a static planar visual target with a linear structure (e.g., electric transmission lines or pipelines). The method uses measurements from inexpensive sensors typically found on-board: an inertial measurement unit, and a monocular computer vision system. Unlike existing work, it does not require linear velocity, position measurements, or an optical flow sensor. The method directly controls the relative pose to the visual target and does not require global navigation satellite system measurements of the vehicle or target. The visual servoing method ensures the vehicle flies centered above the lines at specified height and yaw. Such motion control is important in a number of applications such as efficient data collection for infrastructure inspection. Our article exploits the inherent robustness of an image-based approach where feature error is computed directly in the image plane. A virtual camera is combined with output feedback and convergence of the closed loop is proven. The method is adaptive to vehicle mass, thrust constant, desired depth, and a constant disturbance force. Simulation and experimental results illustrate the method's performance and robustness to model uncertainty.