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

Iqtait, M. and Mohamad, F.S. and Mamat, M. (2018) Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM). In: International Conference on Operations Research of the Indonesian-Operations-Research-Association (IORA), 12 Oct 2017, Tangerang Selatan, Indonesia.

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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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: face recognition, Active Shape Model (ASM), Active Appearance Model (AAM)
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions: Faculty of Informatics & Computing
Depositing User: Muhammad Akmal Azhar
Date Deposited: 22 Nov 2020 02:40
Last Modified: 22 Nov 2020 02:40
URI: http://eprints.unisza.edu.my/id/eprint/1710

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