Age Estimation Based on AAM and 2D-DCT Features of Facial Images


GÜNAY YILMAZ A., NABIYEV V.

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, vol.6, no.2, pp.113-119, 2015 (Peer-Reviewed Journal) identifier

  • 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, Scopus, Index Islamicus, INSPEC
  • Page Numbers: pp.113-119
  • Keywords: 2D-DCT, AAM, Age estimation, PCA, Regression, CLASSIFICATION, RECOGNITION, FRAMEWORK, LDA

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.