Achieving effective facial emotional expressivity within a real-time rendering constraint requests to leverage on all possible inspiration sources and especially from the observations of real individuals. One of them is the frequent asymmetry of facial expressions of emotions, which allows to express complex emotional feelings such as suspicion, smirk, and hidden emotion due to social conventions. To achieve such a higher degree of facial expression, we propose a new model for mapping emotions onto a small set of 1D Facial Part Actions (FPA)s that act on antagonist muscle groups or on individual head orientation degree of freedoms. The proposed linear model can automatically drive a large number of autonomous virtual humans or support the interactive design of complex facial expressions over time.