A Two Step Face Alignment Approach Using Statistical Models

Abstract

Although face alignment using the Active Appearance Model (AAM) is relatively stable, it is known to be sensitive to initial values and not robust under inconstant circumstances. In order to strengthen the ability of AAM performance for face alignment, a two step approach for face alignment combining AAM and Active Shape Model (ASM) is proposed. In the first step, AAM is used to locate the inner landmarks of the face. In the second step, the extended ASM is used to locate the outer landmarks of the face under the constraint of the estimated inner landmarks by AAM. The two kinds of landmarks are then combined together to form the whole facial landmarks. The proposed approach is compared with the basic AAM and the progressive AAM methods. Experimental results show that the proposed approach gives a much more effective performance

A New Face Beauty Prediction Model based on Blocked LBP

“…In this paper, the active shape models (ASMs) algorithm (Cootes et al, 1995, Sukno et al, 2007 is used for landmark extraction. ASMs are statistical models of the shape of objects which deform iteratively to fit to an example of the object in a new image (Cui et al, 2012). Using this model, 77 landmarks are extracted to represent the face shape.…”