Inventi Impact: Machine Vision
ANALYSIS OF FACIAL IMAGES ACROSS AGE PROGRESSION BY HUMANS.
Jingting Zeng, Haibin Ling, Longin Jan Latecki, Shanon Fitzhugh, Guodong Guo
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.
CC Compliant Citation: Jingting Zeng, Haibin Ling, Longin Jan Latecki, Shanon Fitzhugh, and Guodong Guo, “Analysis of Facial Images across Age Progression by Humans,” ISRN Machine Vision, vol. 2012, Article ID 505974, 7 pages, 2012. doi:10.5402/2012/505974