Facial age simulation using age-specific 3D models and recursive PCA

Abstract

Facial age simulation is a topic that has been gaining increasing interest in computer vision. In this paper, a novel age simulation method that utilizes age-specific shape and texture models is proposed. During the process of generating age-specific shape models, 3D face measurements acquired from real human faces are used in order to tune a generic 3D face shape model to represent face shapes belonging to certain age groups. A number of diagnostic studies have been conducted in order to validate the compatibility of the tuned shape models with the corresponding age groups. The shape age-simulation process utilizes agespecific shape models that incorporate age-related constraints during a 3D shape reconstruction phase. Age simulation is completed by predicting the texture at the target age based on a recursive PCA method that aims to superimpose age-related texture modifications in a way that preserves identity-related characteristics of the subject in the source image. Preliminary results indicate the potential of the proposed method.