Analysis of Facial Images across Age Progression by Humans. (1st November 2011)

• Record Type: Journal Article
• Authors: Zeng, Jingting; Ling, Haibin; Latecki, Longin Jan; Fitzhugh, Shanon; Guo, Guodong
• Other Names: Ghita O. Academic Editor.; Park R.-H. Academic Editor.
• Is Part Of: ISRN machine vision. Volume 2012(2012)
• Publication Date: 2011-11-01
• Subjects: Computer vision -- Periodicals; Computer vision; Periodicals; Electronic journals; 006.37
• DOI: 10.5402/2012/505974
• Languages: English
• ISSNs: 2090-7796

Abstract

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.