Display-Camera Calibration from Eye Reflections

Abstract

We present a novel technique for calibrating display-camera systems from reflections in the user's eyes. Display-camera systems enable a range of vision applications that need controlled illumination, including 3D object reconstruction, facial modeling and human computer interaction. One important issue, though, is the geometric calibration of the display, which requires additional hardware and tedious user interaction. The proposed approach eliminates this requirement by analyzing patterns that are reflected in the cornea, a mirroring device that naturally exists in any display-camera system. We introduce an optimization strategy that is able to refine eye and spherical mirror calibration results. When applied to the eye, it even outperforms spherical mirror calibration unoptimized. Furthermore, we obtain a robust estimation of eye poses which can be used for eye tracking applications. Despite the difficult working conditions, the calibration results are good and should be sufficient for many applications.