For humans, to view a scene with two eyes is clearly more advantageous than to do that with one eye. In computer vision however, most of high-level vision tasks, an example of which is face tracking, are still done with one camera only. This is due to the fact that, unlike in human brains, the relationship between the images observed by two arbitrary video cameras, in many cases, is not known. Recent advances in projective vision theory however have produced the methodology which allows one to compute this relationship. This relationship is naturally obtained while observing the same scene with both cameras and knowing this relationship not only makes it possible to track features in 3D, but also makes tracking much more robust and precise. In this paper, we establish a framework based on projective vision for tracking faces in 3D using two arbitrary cameras, and describe a stereo tracking system, which uses the proposed framework to track faces in 3D with the aid of two USB cameras. While being very affordable, our stereotracker exhibits pixel size precision and is robust to head's rotation in all three axis of rotation.