Face alignment is an essential task for many applications. Its objective is to locate feature points on the face, in order to identify its geometric structure. Under unconstrained conditions, the different variations that may occur in the visual context, together with the instability of face detection, make it a difficult problem to solve. While many methods have been proposed, their performances under these constraints are still not satisfactory. In this article, we claim that face alignment should be studied using image sequences rather than still images, as it has been done so far. We show the importance of taking into consideration the temporal information under unconstrained conditions.