Age Simulation in Young Face Images

In this paper, an example-based aging simulation method is proposed for modeling the age effects on young images. The technique is based upon a statistical appearance model and age trajectories. The statistical appearance model is designed to capture the appearance variations due to the aging effect in the young images and the age trajectories provide a statistical definition of facial changes with age that are biologically consistent across a sample population. SVM is trained to predict the age of subject in the test image and the appearance parameters at the target age can be obtained according to the estimated age and age trajectories and then the desired image can be reconstructed. Experimental results show that the proposed age transformation method can effectively change the age of face images and produce plausible, near photo-quality images.