MORPH: development and optimization of a longitudinal age progression database

Authors:
Allen W. Rawls;Karl Ricanek, Jr.
Affiliations:
Department of Computer Science, University of North Carolina Wilmington, Wilmington, NC;Department of Computer Science, University of North Carolina Wilmington, Wilmington, NC
Venue:
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Year:
2009

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MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition

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Abstract

This paper details recent improvement to MORPH, a longitudinal face database, developed for age progression and age estimation research. This database is primarily used to solve age-related problems of facial recognition systems. The data corpus provides the largest set of publicly available longitudinal adult images with supporting metadata and is still expanding; longitudinal spans range from several days to over twenty years. The metadata provided aids in classification by age, gender, and race and includes other key parameters that affect aging appearance.