1. A method comprising: determining an eye state classification of an input image; selecting, using a processor, a texture model for a global shape and an associated mean shape based on eye center positions and the eye state classification, wherein the mean shape comprises all feature points and the global shape model comprises a face frame based on a plurality of fixed points in the input image, wherein the texture model for the global shape is a local binary pattern model determined based on a probability density; and adjusting locations of feature points defined by the mean shape based on the texture model for the global shape and an associated global shape model.