Age progression based on facial aging patterns

Age progression based on facial aging patterns is an important problem that has not been widely addressed. This project is based on studying the problem by designing and evaluating discriminative approaches. First, find the gradient orientation (GO) which provides an effective representation. This representation is further improved when hierarchical information is used, which results in the use of the gradient orientation pyramid (GOP), which is then combined with SVM (Support vector machine) to give better performance. These experiments are conducted on the FGnet dataset and two large passport datasets.