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.
Highlights
In recent years, with the rapid development of biometrics, artificial intelligence and the new generation of human‐computer interaction technology, the face‐ related image processing techniques, such as face recognition, facial expression analysis, face pose estimation, face image encoding, etc., have attracted the attention of many researchers
As pointed out by Cootes et al [13], Active Shape Model (ASM) is faster and achieves more accurate feature point location than Appearance Model (AAM); so we can turn to ASM, which is the source of AAM, to find a better solution
Both ASM and AAM are based on the Point Distribution Model (PDM) and construct two models: the shape model and the texture model
Summary
With the rapid development of biometrics, artificial intelligence and the new generation of human‐computer interaction technology, the face‐ related image processing techniques, such as face recognition, facial expression analysis, face pose estimation, face image encoding, etc., have attracted the attention of many researchers. As pointed out by Cootes et al [13], ASM is faster and achieves more accurate feature point location than AAM; so we can turn to ASM, which is the source of AAM, to find a better solution Both ASM and AAM are based on the Point Distribution Model (PDM) and construct two models: the shape model and the texture model. In this paper we make use of the idea of “progressive” and propose a two step approach for face alignment by combining AAM and ASM.
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