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.

Asuman Günay and Vasif V. Nabiyev, “Age Estimation Based on AAM and 2D-DCT Features of Facial Images” International Journal of Advanced Computer Science and Applications(IJACSA), 6(2), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060217

@article{Günay2015,
title = {Age Estimation Based on AAM and 2D-DCT Features of Facial Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060217},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060217},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {2},
author = {Asuman Günay and Vasif V. Nabiyev}
}