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A 3D dynamic shape model to simulate rejuvenation & ageing trajectory of 3D face images

It is not only interesting to predict how an individual of a relatively young age will look in the future but also to reconstruct the facial appearance in the past during childhood. It can be even more desirable when different circumstances, behavior and lifestyle and their impacts on the facial shape appearance as a consequence are taken into account. Such may be applicable for many practical reasons in healthcare, forensics psychology, missing people and children, etc. This paper presents the 3D Face Time Machine Matrix (FT2M), a 3D Dynamic Shape Model which is a fusion of two models of ageing and rejuvenation with facial shape variations due to lifestyle and behavioral factors. This dynamic model is learned from a database of three dimensional facial images which is built by ten individual age groups between 3 to 75 years old. 3D facial aging modeling is a complex process since it affects both the shape and texture of the face. We propose a Dynamic face model to transform the given input face to his youthful or adulthood appearance by taking into account his lifestyle and behavioral traits and the probable changes may occur in perceptible appearance by altering its shape and texture simultaneously.