Free age progression2/26/2023 ![]() The first is the prototype-based age progression, which transfers the differences between two prototypes (average faces) of the pre-divided source-age group and target-age group into the input individual face (whose age belongs to the source-age group). There are two main categories for the age progression task solution. The framework takes into account face pairs from neighboring age groups for a particular subject, since it is almost impossible to collect faces of all age groups for a particular subject. The personalized part is reflected with taking into account personalized facial characteristics, for example moles, which are invariant in the process of aging. A linear combination of these patterns express a particular personalized aging process. The model consists in learning a set of age-group specific dictionaries, where the dictionary bases correspond to the same index, and these form a particular aging process pattern. Researchers from the National University of Singapore have recently developed a method to render aging faces in a personalized way. This analysis can be used in cross-age face analysis, various authentication system, entertainment, but in finding lost children after a couple of years or more. Age progression or age synthesis (face aging) is defined as aesthetically rendering a face image with natural aging and rejuvenating effects for a certain face of an individual. ![]()
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