Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

Indonesian Operations Research Association - International Conference on Operations Research 2017

Iqtait, M.^1 ; Mohamad, F.S.^1 ; Mamat, M.^1

Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, Besut, Terengganu

22200, Malaysia^1

关键词: Active appearance models;    Active shape model;    Automatic recognition;    Multi resolutions;    Point location;    Recognition rates;    Shape and textures;    Three phasis;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/332/1/012032/pdf
DOI  :  10.1088/1757-899X/332/1/012032

来源: IOP

【 摘 要 】

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.