Age Estimation Based on AAM and 2D-DCT Features of Facial Images
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, vol.6, no.2, pp.113-119, 2015 (ESCI, Scopus)
- Publication Type: Article / Article
- Volume: 6 Issue: 2
- Publication Date: 2015
- Journal Name: INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
- Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Index Islamicus, INSPEC
- Page Numbers: pp.113-119
- Keywords: 2D-DCT, AAM, Age estimation, PCA, Regression, CLASSIFICATION, RECOGNITION, FRAMEWORK, LDA
- Karadeniz Technical University Affiliated: Yes
Abstract
This paper proposes a novel age estimation method - Global and Local feAture based Age estiMation (GLAAM) - relying on global and local features of facial images. Global features are obtained with Active Appearance Models (AAM). Local features are extracted with regional 2D-DCT (2-dimensional Discrete Cosine Transform) of normalized facial images. GLAAM consists of the following modules: face normalization, global feature extraction with AAM, local feature extraction with 2D-DCT, dimensionality reduction by means of Principal Component Analysis (PCA) and age estimation with multiple linear regression. Experiments have shown that GLAAM outperforms many methods previously applied to the FG-NET database.