Multiple Classifiers for Age Prediction Against AAM and ASM
Musab Iqtait1, Fatma Susilawati Mohamad2

1Musab Iqtait, Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, Besut, Terengganu, Malaysia.
2Fatma Susilawati Mohamad, Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, Besut, Terengganu, Malaysia.
Manuscript received on 18 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 456-461 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B10800782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1080.0782S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In recent years, the researchers on age prediction relied on face pictures to get more attention, due to their important applications in security control and human computer interaction. Age prediction incorporates two processes: traits elicitation and prediction of machine learning. In the aspect of face traits elicitation, accurate and robust location for the trait point is convoluted and becoming a challenging issue in age prediction. Active Shape Model (ASM) can elicit the facial shape effectively and correctly. Furthermore, as the improvement of ASM, Active Appearance Models (AAM) is proposed to elicit both shape and texture traits from facial images simultaneously. In this paper, the two models are tested and compared for their performance against 6 algorithms which are Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Support Vector Regression (SVR), Canonical Correlation Analysis (CCA), Linear Discriminant Analysis (LDA), and Projection Twin Support Vector Machine (PTSVM). The experiments show that ASM is faster and gains more precise result than the AAM.
Keywords: Active Appearance Model (AAM), Active Shape Model (ASM), Age Prediction, Machine Learning.
Scope of the Article: Regression and Prediction