About this Journal Submit a Manuscript Table of Contents
ISRN Machine Vision
Volume 2012 (2012), Article ID 505974, 7 pages
http://dx.doi.org/10.5402/2012/505974
Research Article

Analysis of Facial Images across Age Progression by Humans

1Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
2Department of Psychology, Temple University, Philadelphia, PA 19122, USA
3CSEE Department, West Virginia University, Morgantown, WV 26506, USA

Received 25 July 2011; Accepted 25 August 2011

Academic Editors: O. Ghita and R.-H. Park

Copyright © 2012 Jingting Zeng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The appearance of human faces can undergo large variations over aging progress. Analysis of facial image taken over age progression recently attracts increasing attentions in computer-vision community. Human abilities for such analysis are, however, less studied. In this paper, we conduct a thorough study of human ability on two tasks, face verification and age estimation, for facial images taken at different ages. Detailed and rigorous experimental analysis is provided, which helps understanding roles of different factors including age group, age gap, race, and gender. In addition, our study also leads to an interesting observation: for age estimation, photos from adults are more challenging than that from young people. We expect the study to provide a reference for machine-based solutions.