We aim at developing autonomous miniature hov- ering flying robots capable of navigating in unstructured GPS- denied environments. A major challenge is the miniaturization of the embedded sensors and processors allowing such platforms to fly autonomously. In this paper, we propose a novel ego-motion estimation algorithm for hovering robots equipped with inertial and optic-flow sensors that runs in real- time on a microcontroller. Unlike many vision-based methods, this algorithm does not rely on feature tracking, structure estimation, additional distance sensors or assumptions about the environment. Key to this method is the introduction of the translational optic-flow direction constraint (TOFDC), which does not use the optic-flow scale, but only its direction to correct for inertial sensor drift during changes of direction. This solution requires comparatively much simpler electronics and sensors and works in environments of any geometries. We demonstrate the implementation of this algorithm on a miniature 46g quadrotor for closed-loop position control.