This paper addresses the application of active contours or snakes for location and tracking of facial features. Conventional snake approaches find the position of the snake by finding a minimum of its energy, composed of internal and external forces. The external forces pull the contours toward features such as lines and edges. However, in many applications this minimization leads to contours that do not represent correctly the feature we are looking for. We propose in this paper to introduce some higher level information by a statistical characterization of the snaxels that should represent the contour. This higher level information is introduced in the selection of candidates in a dynamic programming implementation of the active contours algorithm, as well as in the external energy. Furthermore, the same approach is used for tracking the contours using in this case motion estimation.