http://ktisis.cut.ac.cy/handle/10488/29 Search the Channel search http://ktisis.cut.ac.cy/simple-search http://ktisis.cut.ac.cy/handle/10488/811 Title: Automatic Age Progression: Methodologies and Performance Evaluation<br/><br/>Authors: Lanitis, Andreas<br/><br/>Abstract: Age progression is the process of predicting the future facial appearance of facesappearing in images. The ability to produce accurate age progressed faces is importantin a number of key applications including the identification of missing persons,development of age-invariant face recognition systems and automatic update ofphotographs in smart documents. Automatic age-progression is a challenging task,mainly due to the diversity of aging variation and the dependence of the aging processon external factors that include health conditions and hereditary trends.Recently an escalated research interest in the area is recorded and as a result a numberof face aging algorithms were reported in the literature. In this paper we present keytechniques reported in the literature with emphasis on techniques developed by theauthor. In particular we present a face-aging algorithm based on the definition ofaging trajectories (the so called aging functions) and algorithms based on modellingthe distributions of faces belonging to different subjects and different age groups.Special emphasis is given to the topic of performance evaluation of age progressionmethodologies based on dedicated metrics. Work in this area is considered animportant research direction in the field, since it will enable the evolution of the mostpromising age progression methodologies.