This paper presents a new linear velocity estimator based on the unscented Kalman filter and making use of image information aided with inertial measurements. The proposed technique is independent of the scale factor in case of planar observed scene and does not require a priori knowledge of the scene. Image moments of virtual objects, i.e. sets of classical image features such as corners collected online, are employed as the sole correcting information to be fed back to the estimator. Experimental results performed with a quadrotor equipped with a fisheye camera highlight the potential of the proposed approach.