Monogenic multi-characteristic face expression identification method based on sparse fusion

The invention discloses a monogenic multi-characteristic face expression identification method based on sparse fusion. The method comprises the following steps of: 1, carrying out monogenic filtering on an expression image after pre-processing, and obtaining monogenic amplitude information, monogenic direction information, monogenic phase information, transverse conversion information and longitudinal conversion information in three dimensions; 2, utilizing five kinds of monogenic information to extract a monogenic binary mode histogram characteristic, a monogenic direction histogram characteristic and a monogenic phase histogram characteristic of the face expression image, wherein the three kinds of characteristics respectively construct corresponding sparse dictionaries; and 3, utilizing a l1 regularization least square method to optimize weights of the three sparse dictionaries, and realizing face expression identification by means of weighted fusion. According to the invention, the texture, shape and dire