Conversing with others is one of the most central of human behaviours. In any conversation, humans use facial motion to help modify what is said, to control the flow of a dialog, or to convey complex intentions without saying a word. Here, we employ a custom, image-based, stereo motion-tracking algorithm to track and selectively "freeze" portions of an actor or actress's face in video recordings in order to determine the necessary and sufficient facial motions for nine conversational expressions. The results show that most expressions rely primarily on a single facial area to convey meaning, with different expressions using different facial areas. The results also show that the combination of rigid head, eye, eyebrow, and mouth motion is sufficient to produce versions of these expressions that are as easy to recognize as the original recordings. Finally, the results show that the manipulation technique introduced few perceptible artifacts into the altered video sequences. The use of advanced computer graphics techniques provided a means to systematically examine real facial expressions. This provides not only fundamental insights into human perception and cognition, but also yields the basis for a systematic description of what needs to be animated in order to produce realistic, recognizable facial expressions.