AgeGuess

AgeGuess collects crowdsourced perceived-age annotations from user-uploaded facial photographs to enable research linking perceived age with biological age and human aging trends.

Key Features:

• Citizen Science Engagement: Crowdsources age estimates from volunteer participants who upload facial images and guess the ages of others.
• Extensive Database: Houses approximately 220,000 perceived-age guesses covering birth cohorts from 1877 to 2012.
• Global Participation: Includes contributions from nearly 4,500 participants across over 120 countries.
• Facial Photograph Repository: Contains about 4,700 facial photographs paired with perceived-age annotations.

Scientific Applications:

• Aging Process Analysis: Enables analysis of temporal changes in perceived age and its correlation with biological age to study human aging and life expectancy trends.
• Perceived Age Studies: Supports investigation of facial-feature cues and perceptual factors underlying human age estimation across populations.
• Accuracy of Age Guessing: Permits study of inter-rater accuracy and demographic factors influencing age-guessing performance.

Methodology:

Collects user-uploaded facial photographs and stores crowdsourced perceived-age estimates in a database for downstream analysis.